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A novel in-bed body posture monitoring for decubitus ulcer prevention using body pressure distribution mapping BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-03-15 Lindsay Stern, Geoff Fernie, Atena Roshan Fekr
Decubitus ulcers are prevalent among the aging population due to a gradual decline in their overall health, such as nutrition, mental health, and mobility, resulting in injury to the skin and tissue. The most common technique to prevent these ulcers is through frequent repositioning to redistribute body pressures. Therefore, the main goal of this study is to facilitate the timely repositioning of patients
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Construction of in vitro liver-on-a-chip models and application progress BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-03-15 Jie Liu, Yimei Du, Xinxin Xiao, Daopeng Tan, Yuqi He, Lin Qin
The liver is the largest internal organ of the human body. It has a complex structure and function and plays a vital role in drug metabolism. In recent decades, extensive research has aimed to develop in vitro models that can simulate liver function to demonstrate changes in the physiological and pathological environment of the liver. Animal models and in vitro cell models are common, but the data
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Evaluating imaging repeatability of fully self-service fundus photography within a community-based eye disease screening setting BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-03-12 Juzhao Zhang, Xuan Luo, Deshang Li, Yajun Peng, Guiling Gao, Liangwen Lei, Meng Gao, Lina Lu, Yi Xu, Tao Yu, Senlin Lin, Yingyan Ma, Chunxia Yao, Haidong Zou
This study aimed to investigate the imaging repeatability of self-service fundus photography compared to traditional fundus photography performed by experienced operators. Prospective cross-sectional study. In a community-based eye diseases screening site, we recruited 65 eyes (65 participants) from the resident population of Shanghai, China. All participants were devoid of cataract or any other conditions
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Three-dimensional visualization of thyroid ultrasound images based on multi-scale features fusion and hierarchical attention BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-03-11 Junyu Mi, Rui Wang, Qian Feng, Lin Han, Yan Zhuang, Ke Chen, Zhong Chen, Zhan Hua, Yan luo, Jiangli Lin
Ultrasound three-dimensional visualization, a cutting-edge technology in medical imaging, enhances diagnostic accuracy by providing a more comprehensive and readable portrayal of anatomical structures compared to traditional two-dimensional ultrasound. Crucial to this visualization is the segmentation of multiple targets. However, challenges like noise interference, inaccurate boundaries, and difficulties
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Effects of hyperbaric oxygen combined cabin ventilator on critically ill patients with liberation difficulty after tracheostomy BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-03-07 Yinliang Qi, Jixiang Xu, Hui Liu, Xiaomei Zhou
Critically ill patients undergoing liberation often encounter various physiological and clinical complexities and challenges. However, whether the combination of hyperbaric oxygen and in-cabin ventilator therapy could offer a comprehensive approach that may simultaneously address respiratory and potentially improve outcomes in this challenging patient population remain unclear. This retrospective study
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Diagnostic value of bedside lung ultrasound and 12-zone score in the 65 cases of neonatal respiratory distress syndrome and its severity BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-03-06 Peipei Huang, Deng Chen, Xiuxiang Liu, Xiang Zhang, Xiazi Song
To explore the predictive value of bedside lung ultrasound score in the severity of neonatal respiratory distress syndrome (NRDS) and mechanical ventilation and extubation. The clinical data of 65 neonates with NRDS and invasive mechanical ventilation diagnosed in the neonatal intensive care unit of our hospital from July 2021 to July 2022 were retrospectively analyzed. 65 neonates were included in
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Designing and validating an experimental protocol to induce airway narrowing in older adults with and without asthma BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-03-06 Shaghayegh Chavoshian, Xiaoshu Cao, Anirudh Thommandram, Matthew B. Stanbrook, Susan M. Tarlo, Yan Fossat, Azadeh Yadollahi
Persons with asthma may experience excessive airway narrowing due to exercise or exposure to cold air, worsening their daily functionality. Exercise has several benefits for asthma control, but it may induce airway narrowing in some persons with asthma. When combined with cold temperatures, it introduces another layer of challenges. Therefore, managing this interaction is crucial to increase the quality
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Application of visual transformer in renal image analysis BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-03-05 Yuwei Yin, Zhixian Tang, Huachun Weng
Deep Self-Attention Network (Transformer) is an encoder–decoder architectural model that excels in establishing long-distance dependencies and is first applied in natural language processing. Due to its complementary nature with the inductive bias of convolutional neural network (CNN), Transformer has been gradually applied to medical image processing, including kidney image processing. It has become
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A concept for human use of real-time and remote monitoring of diabetic subjects using intermittent scanned continuous glucose measurement BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-28 Jhon E. Goez-Mora, Natalia Arbeláez-Córdoba, Norman Balcazar-Morales, Pablo S. Rivadeneira
Flash glucose monitoring systems like the FreeStyle Libre (FSL) sensor have gained popularity for monitoring glucose levels in people with diabetes mellitus. This sensor can be paired with an off-label converted real-time continuous glucose monitor (c-rtCGM) plus an ad hoc computer/smartphone interface for remote real-time monitoring of diabetic subjects, allowing for trend analysis and alarm generation
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HM_ADET: a hybrid model for automatic detection of eyelid tumors based on photographic images BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-28 Jiewei Jiang, Haiyang Liu, Lang He, Mengjie Pei, Tongtong Lin, Hailong Yang, Junhua Yang, Jiamin Gong, Xumeng Wei, Mingmin Zhu, Guohai Wu, Zhongwen Li
The accurate detection of eyelid tumors is essential for effective treatment, but it can be challenging due to small and unevenly distributed lesions surrounded by irrelevant noise. Moreover, early symptoms of eyelid tumors are atypical, and some categories of eyelid tumors exhibit similar color and texture features, making it difficult to distinguish between benign and malignant eyelid tumors, particularly
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Simulating impaired left ventricular–arterial coupling in aging and disease: a systematic review BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-22 Corina Cheng Ai Ding, Socrates Dokos, Azam Ahmad Bakir, Nurul Jannah Zamberi, Yih Miin Liew, Bee Ting Chan, Nor Ashikin Md Sari, Alberto Avolio, Einly Lim
Aortic stenosis, hypertension, and left ventricular hypertrophy often coexist in the elderly, causing a detrimental mismatch in coupling between the heart and vasculature known as ventricular−vascular (VA) coupling. Impaired left VA coupling, a critical aspect of cardiovascular dysfunction in aging and disease, poses significant challenges for optimal cardiovascular performance. This systematic review
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Non-invasive parameters of autonomic function using beat-to-beat cardiovascular variations and arterial stiffness in hypertensive individuals: a systematic review BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-20 Jia Hui Ooi, Renly Lim, Hansun Seng, Maw Pin Tan, Choon Hian Goh, Nigel H. Lovell, Ahmadreza Argha, Hooi Chin Beh, Nor Ashikin Md Sari, Einly Lim
Non-invasive, beat-to-beat variations in physiological indices provide an opportunity for more accessible assessment of autonomic dysfunction. The potential association between the changes in these parameters and arterial stiffness in hypertension remains poorly understood. This systematic review aims to investigate the association between non-invasive indicators of autonomic function based on beat-to-beat
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Kinematic difference and asymmetries during level walking in adolescent patients with different types of mild scoliosis BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-19 Run Ji, Xiaona Liu, Yang Liu, Bin Yan, Jiemeng Yang, Wayne Yuk-wai Lee, Ling Wang, Chunjing Tao, Shengzheng Kuai, Yubo Fan
Adolescent idiopathic scoliosis (AIS), three-dimensional spine deformation, affects body motion. Previous research had indicated pathological gait patterns of AIS. However, the impact of the curve number on the walking mechanism has not been established. Therefore, this study aimed to compare the gait symmetry and kinematics in AIS patients with different curve numbers to healthy control. In the spinal
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The effectiveness of simple heuristic features in sensor orientation and placement problems in human activity recognition using a single smartphone accelerometer BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-17 Arnab Barua, Xianta Jiang, Daniel Fuller
Human activity Recognition (HAR) using smartphone sensors suffers from two major problems: sensor orientation and placement. Sensor orientation and sensor placement problems refer to the variation in sensor signal for a particular activity due to sensors’ altering orientation and placement. Extracting orientation and position invariant features from raw sensor signals is a simple solution for tackling
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StairNet: visual recognition of stairs for human–robot locomotion BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-15 Andrew Garrett Kurbis, Dmytro Kuzmenko, Bogdan Ivanyuk-Skulskiy, Alex Mihailidis, Brokoslaw Laschowski
Human–robot walking with prosthetic legs and exoskeletons, especially over complex terrains, such as stairs, remains a significant challenge. Egocentric vision has the unique potential to detect the walking environment prior to physical interactions, which can improve transitions to and from stairs. This motivated us to develop the StairNet initiative to support the development of new deep learning
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Feasibility of using a depth camera or pressure mat for visual feedback balance training with functional electrical stimulation BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-12 Derrick Lim, William Pei, Jae W. Lee, Kristin E. Musselman, Kei Masani
Individuals with incomplete spinal-cord injury/disease are at an increased risk of falling due to their impaired ability to maintain balance. Our research group has developed a closed-loop visual-feedback balance training (VFBT) system coupled with functional electrical stimulation (FES) for rehabilitation of standing balance (FES + VFBT system); however, clinical usage of this system is limited by
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Screening ovarian cancer by using risk factors: machine learning assists BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-12 Raoof Nopour
Ovarian cancer (OC) is a prevalent and aggressive malignancy that poses a significant public health challenge. The lack of preventive strategies for OC increases morbidity, mortality, and other negative consequences. Screening OC through risk prediction could be leveraged as a powerful strategy for preventive purposes that have not received much attention. So, this study aimed to leverage machine learning
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Deep neural networks for wearable sensor-based activity recognition in Parkinson’s disease: investigating generalizability and model complexity BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-09 Shelly Davidashvilly, Maria Cardei, Murtadha Hssayeni, Christopher Chi, Behnaz Ghoraani
The research gap addressed in this study is the applicability of deep neural network (NN) models on wearable sensor data to recognize different activities performed by patients with Parkinson’s Disease (PwPD) and the generalizability of these models to PwPD using labeled healthy data. The experiments were carried out utilizing three datasets containing wearable motion sensor readings on common activities
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Abnormal interlimb coordination of motor developmental delay during infant crawling based on kinematic synergy analysis BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-07 Li Zhang, Chong Xu, Lin Chen, Yuan Liu, Nong Xiao, Xiaoying Wu, Yuxia Chen, Wensheng Hou
Previous studies have reported that abnormal interlimb coordination is a typical characteristic of motor developmental delay (MDD) during human movement, which can be visually manifested as abnormal motor postures. Clinically, the scale assessments are usually used to evaluate interlimb coordination, but they rely heavily on the subjective judgements of therapists and lack quantitative analysis. In
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Detecting bulbar amyotrophic lateral sclerosis (ALS) using automatic acoustic analysis BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-04 Leif E. R. Simmatis, Jessica Robin, Michael J. Spilka, Yana Yunusova
Automatic speech assessments have the potential to dramatically improve ALS clinical practice and facilitate patient stratification for ALS clinical trials. Acoustic speech analysis has demonstrated the ability to capture a variety of relevant speech motor impairments, but implementation has been hindered by both the nature of lab-based assessments (requiring travel and time for patients) and also
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Advantages of transformer and its application for medical image segmentation: a survey BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-02-03 Qiumei Pu, Zuoxin Xi, Shuai Yin, Zhe Zhao, Lina Zhao
Convolution operator-based neural networks have shown great success in medical image segmentation over the past decade. The U-shaped network with a codec structure is one of the most widely used models. Transformer, a technology used in natural language processing, can capture long-distance dependencies and has been applied in Vision Transformer to achieve state-of-the-art performance on image classification
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Beyond timing and step counting in 360° turning-in-place assessment: a scoping review BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-31 Slavka Netukova, Lucie Horakova, Zoltan Szabo, Radim Krupicka
Turning in place is a challenging motor task and is used as a brief assessment test of lower limb function and dynamic balance. This review aims to examine how research of instrumented analysis of turning in place is implemented. In addition to reporting the studied population, we covered acquisition systems, turn detection methods, quantitative parameters, and how these parameters are computed. Following
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Protocol for metadata and image collection at diabetic foot ulcer clinics: enabling research in wound analytics and deep learning BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-29 Reza Basiri, Karim Manji, Philip M. LeLievre, John Toole, Faith Kim, Shehroz S. Khan, Milos R. Popovic
The escalating impact of diabetes and its complications, including diabetic foot ulcers (DFUs), presents global challenges in quality of life, economics, and resources, affecting around half a billion people. DFU healing is hindered by hyperglycemia-related issues and diverse diabetes-related physiological changes, necessitating ongoing personalized care. Artificial intelligence and clinical research
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Joint angle estimation during shoulder abduction exercise using contactless technology BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-28 Ali Barzegar Khanghah, Geoff Fernie, Atena Roshan Fekr
Tele-rehabilitation, also known as tele-rehab, uses communication technologies to provide rehabilitation services from a distance. The COVID-19 pandemic has highlighted the importance of tele-rehab, where the in-person visits declined and the demand for remote healthcare rises. Tele-rehab offers enhanced accessibility, convenience, cost-effectiveness, flexibility, care quality, continuity, and communication
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A dry polymer nanocomposite transcutaneous electrode for functional electrical stimulation BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-26 Melissa Marquez-Chin, Zia Saadatnia, Yu-Chen Sun, Hani E. Naguib, Milos R. Popovic
Functional electrical stimulation (FES) can be used in rehabilitation to aid or improve function in people with paralysis. In clinical settings, it is common practice to use transcutaneous electrodes to apply the electrical stimulation, since they are non-invasive, and can be easily applied and repositioned as necessary. However, the current electrode options available for transcutaneous FES are limited
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Left main coronary artery morphological phenotypes and its hemodynamic properties BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-22 Qi Wang, Hua Ouyang, Lei Lv, Long Gui, Songran Yang, Ping Hua
Atherosclerosis may be linked to morphological defects that lead to variances in coronary artery hemodynamics. Few objective strategies exit at present for generalizing morphological phenotypes of coronary arteries in terms of hemodynamics. We used unsupervised clustering (UC) to classify the morphology of the left main coronary artery (LM) and looked at how hemodynamic distribution differed between
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Multimodal diagnosis model of Alzheimer’s disease based on improved Transformer BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-19 Yan Tang, Xing Xiong, Gan Tong, Yuan Yang, Hao Zhang
Recent technological advancements in data acquisition tools allowed neuroscientists to acquire different modality data to diagnosis Alzheimer’s disease (AD). However, how to fuse these enormous amount different modality data to improve recognizing rate and find significance brain regions is still challenging. The algorithm used multimodal medical images [structural magnetic resonance imaging (sMRI)
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Pulse wave-based evaluation of the blood-supply capability of patients with heart failure via machine learning BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-19 Sirui Wang, Ryohei Ono, Dandan Wu, Kaoruko Aoki, Hirotoshi Kato, Togo Iwahana, Sho Okada, Yoshio Kobayashi, Hao Liu
Pulse wave, as a message carrier in the cardiovascular system (CVS), enables inferring CVS conditions while diagnosing cardiovascular diseases (CVDs). Heart failure (HF) is a major CVD, typically requiring expensive and time-consuming treatments for health monitoring and disease deterioration; it would be an effective and patient-friendly tool to facilitate rapid and precise non-invasive evaluation
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Effects of workload and saddle height on muscle activation of the lower limb during cycling BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-16 Fangbo Bing, Guoxin Zhang, Yan Wang, Ming Zhang
Cycling workload is an essential factor in practical cycling training. Saddle height is the most studied topic in bike fitting, but the results are controversial. This study aims to investigate the effects of workload and saddle height on the activation level and coordination of the lower limb muscles during cycling. Eighteen healthy male participants with recreational cycling experience performed
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A neural network with a human learning paradigm for breast fibroadenoma segmentation in sonography BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-14 Yongxin Guo, Maoshan Chen, Lei Yang, Heng Yin, Hongwei Yang, Yufeng Zhou
Breast fibroadenoma poses a significant health concern, particularly for young women. Computer-aided diagnosis has emerged as an effective and efficient method for the early and accurate detection of various solid tumors. Automatic segmentation of the breast fibroadenoma is important and potentially reduces unnecessary biopsies, but challenging due to the low image quality and presence of various artifacts
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Unsupervised corneal contour extraction algorithm with shared model for dynamic deformation videos: improving accuracy and noise resistance BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-08 Zuoping Tan, Xuan Chen, Qiang Xu, Can Yang, Xiaomin Lin, Yan Huo, Mohammad Alzogool, Riwei Wang, Yan Wang
In this study, an automatic corneal contour extraction algorithm with a shared model is developed to extract contours from dynamic corneal videos containing noise, which improves the accuracy of corneal biomechanical evaluation and clinical diagnoses. The algorithm does not require manual labeling and completes the unsupervised semantic segmentation of each frame in corneal dynamic deformation videos
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Bioelectricity in dental medicine: a narrative review BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-03 Qingqing Min, Yajun Gao, Yao Wang
Bioelectric signals, whether exogenous or endogenous, play crucial roles in the life processes of organisms. Recently, the significance of bioelectricity in the field of dentistry is steadily gaining greater attention. This narrative review aims to comprehensively outline the theory, physiological effects, and practical applications of bioelectricity in dental medicine and to offer insights into its
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Effect of test duration and sensor location on the reliability of standing balance parameters derived using body-mounted accelerometers BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-02 Vahid Abdollah, Alireza Noamani, John Ralston, Chester Ho, Hossein Rouhani
Balance parameters derived from wearable sensor measurements during postural sway have been shown to be sensitive to experimental variables such as test duration, sensor number, and sensor location that influence the magnitude and frequency-related properties of measured center-of-mass (COM) and center-of-pressure (COP) excursions. In this study, we investigated the effects of test duration, the number
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Cycling using functional electrical stimulation therapy to improve motor function and activity in post-stroke individuals in early subacute phase: a systematic review with meta-analysis BioMed. Eng. OnLine (IF 3.9) Pub Date : 2024-01-02 Wagner Rodrigues Galvão, Luana Karoline Castro Silva, Magno Ferreira Formiga, George André Pereira Thé, Christina Danielli Coelho de Morais Faria, Ramon Távora Viana, Lidiane Andréa Oliveira Lima
Stroke necessitates interventions to rehabilitate individuals with disabilities, and the application of functional electrical stimulation therapy (FEST) has demonstrated potential in this regard. This study aimed to analyze the efficacy and effectiveness of cycling using FEST to improve motor function and lower limb activity in post-stroke individuals. We performed a systematic review according to
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A weakly supervised deep learning model integrating noncontrasted computed tomography images and clinical factors facilitates haemorrhagic transformation prediction after intravenous thrombolysis in acute ischaemic stroke patients BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-19 Xiaoshuang Ru, Shilong Zhao, Weidao Chen, Jiangfen Wu, Ruize Yu, Dawei Wang, Mengxing Dong, Qiong Wu, Daoyong Peng, Yang Song
Haemorrhage transformation (HT) is a serious complication of intravenous thrombolysis (IVT) in acute ischaemic stroke (AIS). Accurate and timely prediction of the risk of HT before IVT may change the treatment decision and improve clinical prognosis. We aimed to develop a deep learning method for predicting HT after IVT for AIS using noncontrast computed tomography (NCCT) images. We retrospectively
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RAGE plays key role in diabetic retinopathy: a review BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-19 ZhiWen Lu, Bin Fan, YunZhi Li, YiXin Zhang
RAGE is a multiligand receptor for the immunoglobulin superfamily of cell surface molecules and is expressed in Müller cells, vascular endothelial cells, nerve cells and RPE cells of the retina. Diabetic retinopathy (DR) is a multifactorial disease associated with retinal inflammation and vascular abnormalities and is the leading cause of vision loss or impairment in older or working-age adults worldwide
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Assessment of the functional severity of coronary lesions from optical coherence tomography based on ensembled learning BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-16 Irina-Andra Tache, Cosmin-Andrei Hatfaludi, Andrei Puiu, Lucian Mihai Itu, Nicoleta-Monica Popa-Fotea, Lucian Calmac, Alexandru Scafa-Udriste
Atherosclerosis is one of the most frequent cardiovascular diseases. The dilemma faced by physicians is whether to treat or postpone the revascularization of lesions that fall within the intermediate range given by an invasive fractional flow reserve (FFR) measurement. The paper presents a monocentric study for lesions significance assessment that can potentially cause ischemia on the large coronary
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Artificial intelligence in glaucoma: opportunities, challenges, and future directions BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-16 Xiaoqin Huang, Md Rafiqul Islam, Shanjita Akter, Fuad Ahmed, Ehsan Kazami, Hashem Abu Serhan, Alaa Abd-alrazaq, Siamak Yousefi
Artificial intelligence (AI) has shown excellent diagnostic performance in detecting various complex problems related to many areas of healthcare including ophthalmology. AI diagnostic systems developed from fundus images have become state-of-the-art tools in diagnosing retinal conditions and glaucoma as well as other ocular diseases. However, designing and implementing AI models using large imaging
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Radiotranscriptomics of non-small cell lung carcinoma for assessing high-level clinical outcomes using a machine learning-derived multi-modal signature BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-15 Eleftherios Trivizakis, Nikoletta-Maria Koutroumpa, John Souglakos, Apostolos Karantanas, Michalis Zervakis, Kostas Marias
Multi-omics research has the potential to holistically capture intra-tumor variability, thereby improving therapeutic decisions by incorporating the key principles of precision medicine. The purpose of this study is to identify a robust method of integrating features from different sources, such as imaging, transcriptomics, and clinical data, to predict the survival and therapy response of non-small
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Wireless capsule endoscopy multiclass classification using three-dimensional deep convolutional neural network model BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-15 Mehrdokht Bordbar, Mohammad Sadegh Helfroush, Habibollah Danyali, Fardad Ejtehadi
Wireless capsule endoscopy (WCE) is a patient-friendly and non-invasive technology that scans the whole of the gastrointestinal tract, including difficult-to-access regions like the small bowel. Major drawback of this technology is that the visual inspection of a large number of video frames produced during each examination makes the physician diagnosis process tedious and prone to error. Several computer-aided
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Prediction of non-perfusion volume ratio for uterine fibroids treated with ultrasound-guided high-intensity focused ultrasound based on MRI radiomics combined with clinical parameters BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-13 Ye Zhou, Jinwei Zhang, Chenghai Li, Jinyun Chen, Fajin Lv, Yongbin Deng, Siyao Chen, Yuling Du, Faqi Li
Prediction of non-perfusion volume ratio (NPVR) is critical in selecting patients with uterine fibroids who will potentially benefit from ultrasound-guided high-intensity focused ultrasound (HIFU) treatment, as it reduces the risk of treatment failure. The purpose of this study is to construct an optimal model for predicting NPVR based on T2-weighted magnetic resonance imaging (T2MRI) radiomics features
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Comparison of plugin and redundant marker sets to analyze gait kinematics between different populations BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-12 Run Ji, Wayne Yuk-wai Lee, Xinyu Guan, Bin Yan, Lei Yang, Jiemeng Yang, Ling Wang, Chunjing Tao, Shengzheng Kuai, Yubo Fan
Gait model consists of a marker set and a segment pose estimation algorithm. Plugin marker set and inverse kinematic algorithm (IK.) are prevalent in gait analysis, especially musculoskeletal motion analysis. Adding extra markers for the plugin marker set could increase the robustness to marker misplacement, motion artifacts, and even markers occlusion. However, how the different marker sets affect
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Effects of vibration therapy for post-stroke spasticity: a systematic review and meta-analysis of randomized controlled trials BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-12 Duchun Zeng, Wei Lei, Yurou Kong, Fenghao Ma, Kun Zhao, Xiangming Ye, Tongcai Tan
The efficacy of vibration therapy (VT) in people with post-stroke spasticity (PSS) remains uncertain. This study aims to conduct a comprehensive meta-analysis to assess the effectiveness of VT in PSS. PubMed, Embase, Cochrane Library, Physiotherapy Evidence Database, and Web of Science were searched from inception to October 2022 for randomized controlled trials (RCTs) of VT in people with PSS. The
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Evaluating the ability of a predictive vision-based machine learning model to measure changes in gait in response to medication and DBS within individuals with Parkinson’s disease BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-11 Andrea Sabo, Andrea Iaboni, Babak Taati, Alfonso Fasano, Carolina Gorodetsky
Gait impairments in Parkinson’s disease (PD) are treated with dopaminergic medication or deep-brain stimulation (DBS), although the magnitude of the response is variable between individuals. Computer vision-based approaches have previously been evaluated for measuring the severity of parkinsonian gait in videos, but have not been evaluated for their ability to identify changes within individuals in
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Bactericidal effect of low-temperature atmospheric plasma against the Shigella flexneri BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-09 Yan Chen, Yuanyuan He, Tao Jin, Chenwei Dai, Qinghua Xu, Zhengwei Wu
Shigella flexneri (S. flexneri) is a common intestinal pathogenic bacteria that mainly causes bacillary dysentery, especially in low socioeconomic countries. This study aimed to apply cold atmospheric plasma (CAP) on S. flexneri directly to achieve rapid, efficient and environmentally friendly sterilization. The operating parameters of the equipment were determined by plasma diagnostics. The plate
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Selective peripheral nerve recording using simulated human median nerve activity and convolutional neural networks BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-07 Taseen Jawad, Ryan G. L. Koh, José Zariffa
It is difficult to create intuitive methods of controlling prosthetic limbs, often resulting in abandonment. Peripheral nerve interfaces can be used to convert motor intent into commands to a prosthesis. The Extraneural Spatiotemporal Compound Action Potentials Extraction Network (ESCAPE-NET) is a convolutional neural network (CNN) that has previously been demonstrated to be effective at discriminating
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Deep learning-driven multi-view multi-task image quality assessment method for chest CT image BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-06 Jialin Su, Meifang Li, Yongping Lin, Liu Xiong, Caixing Yuan, Zhimin Zhou, Kunlong Yan
Chest computed tomography (CT) image quality impacts radiologists’ diagnoses. Pre-diagnostic image quality assessment is essential but labor-intensive and may have human limitations (fatigue, perceptual biases, and cognitive biases). This study aims to develop and validate a deep learning (DL)-driven multi-view multi-task image quality assessment (M $$^2$$ IQA) method for assessing the quality of chest
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Development of early prediction model of in-hospital cardiac arrest based on laboratory parameters BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-06 Xinhuan Ding, Yingchan Wang, Weiyi Ma, Yaojun Peng, Jingjing Huang, Meng Wang, Haiyan Zhu
In-hospital cardiac arrest (IHCA) is an acute disease with a high fatality rate that burdens individuals, society, and the economy. This study aimed to develop a machine learning (ML) model using routine laboratory parameters to predict the risk of IHCA in rescue-treated patients. This retrospective cohort study examined all rescue-treated patients hospitalized at the First Medical Center of the PLA
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Classification of lung pathologies in neonates using dual-tree complex wavelet transform BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-04 Sagarjit Aujla, Adel Mohamed, Ryan Tan, Karl Magtibay, Randy Tan, Lei Gao, Naimul Khan, Karthikeyan Umapathy
Undiagnosed and untreated lung pathologies are among the leading causes of neonatal deaths in developing countries. Lung Ultrasound (LUS) has been widely accepted as a diagnostic tool for neonatal lung pathologies due to its affordability, portability, and safety. However, healthcare institutions in developing countries lack well-trained clinicians to interpret LUS images, which limits the use of LUS
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Diagnostic test accuracy of machine learning algorithms for the detection intracranial hemorrhage: a systematic review and meta-analysis study BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-04 Masoud Maghami, Shahab Aldin Sattari, Marziyeh Tahmasbi, Pegah Panahi, Javad Mozafari, Kiarash Shirbandi
This systematic review and meta-analysis were conducted to objectively evaluate the evidence of machine learning (ML) in the patient diagnosis of Intracranial Hemorrhage (ICH) on computed tomography (CT) scans. Until May 2023, systematic searches were conducted in ISI Web of Science, PubMed, Scopus, Cochrane Library, IEEE Xplore Digital Library, CINAHL, Science Direct, PROSPERO, and EMBASE for studies
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Integrated particle image velocimetry and fluid–structure interaction analysis for patient-specific abdominal aortic aneurysm studies BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-12-03 Can Özcan, Özgür Kocatürk, Civan Işlak, Cengizhan Öztürk
Understanding the hemodynamics of an abdominal aortic aneurysm (AAA) is crucial for risk assessment and treatment planning. This study introduces a low-cost, patient-specific in vitro AAA model to investigate hemodynamics using particle image velocimetry (PIV) and flow-simulating circuit, validated through fluid–structure interaction (FSI) simulations. In this study, 3D printing was employed to manufacture
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Multi-classification model incorporating radiomics and clinic-radiological features for predicting invasiveness and differentiation of pulmonary adenocarcinoma nodules BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-11-30 Haitao Sun, Chunling Zhang, Aimei Ouyang, Zhengjun Dai, Peiji Song, Jian Yao
To develop a comprehensive multi-classification model that combines radiomics and clinic-radiological features to accurately predict the invasiveness and differentiation of pulmonary adenocarcinoma nodules. A retrospective analysis was conducted on a cohort comprising 500 patients diagnosed with lung adenocarcinoma between January 2020 and December 2022. The dataset included preoperative CT images
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Comparison of deep learning-based image segmentation methods for intravascular ultrasound on retrospective and large image cohort study BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-11-28 Liang Dong, Wei Lu, Xuzhou Lu, Xiaochang Leng, Jianping Xiang, Changling Li
The aim of this study was to investigate the generalization performance of deep learning segmentation models on a large cohort intravascular ultrasound (IVUS) image dataset over the lumen and external elastic membrane (EEM), and to assess the consistency and accuracy of automated IVUS quantitative measurement parameters. A total of 11,070 IVUS images from 113 patients and pullbacks were collected and
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Spatial mapping of tumor heterogeneity in whole-body PET–CT: a feasibility study BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-11-25 Hanna Jönsson, Håkan Ahlström, Joel Kullberg
Tumor heterogeneity is recognized as a predictor of treatment response and patient outcome. Quantification of tumor heterogeneity across all scales may therefore provide critical insight that ultimately improves cancer management. An image registration-based framework for the study of tumor heterogeneity in whole-body images was evaluated on a dataset of 490 FDG-PET–CT images of lung cancer, lymphoma
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Interpretable classification for multivariate gait analysis of cerebral palsy BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-11-22 Changwon Yoon, Yongho Jeon, Hosik Choi, Soon-Sun Kwon, Jeongyoun Ahn
The Gross Motor Function Classification System (GMFCS) is a widely used tool for assessing the mobility of people with Cerebral Palsy (CP). It classifies patients into different levels based on their gross motor function and its level is typically determined through visual evaluation by a trained expert. Although gait analysis is commonly used in CP research, the functional aspects of gait patterns
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Investigating gait-responsive somatosensory cueing from a wearable device to improve walking in Parkinson’s disease BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-11-16 Dongli Li, Andre Hallack, Sophie Gwilym, Dongcheng Li, Michele T. Hu, James Cantley
Freezing-of-gait (FOG) and impaired walking are common features of Parkinson’s disease (PD). Provision of external stimuli (cueing) can improve gait, however, many cueing methods are simplistic, increase task loading or have limited utility in a real-world setting. Closed-loop (automated) somatosensory cueing systems have the potential to deliver personalised, discrete cues at the appropriate time
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Moderate static magnetic field promotes fracture healing and regulates iron metabolism in mice BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-11-15 Shenghang Wang, Yuetong Liu, Chenge Lou, Chao Cai, Weihao Ren, Junyu Liu, Ming Gong, Peng Shang, Hao Zhang
Fractures are the most common orthopedic diseases. It is known that static magnetic fields (SMFs) can contribute to the maintenance of bone health. However, the effect and mechanism of SMFs on fracture is still unclear. This study is aim to investigate the effect of moderate static magnetic fields (MMFs) on bone structure and metabolism during fracture healing. Eight-week-old male C57BL/6J mice were
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A combined encoder–transformer–decoder network for volumetric segmentation of adrenal tumors BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-11-08 Liping Wang, Mingtao Ye, Yanjie Lu, Qicang Qiu, Zhongfeng Niu, Hengfeng Shi, Jian Wang
The morphology of the adrenal tumor and the clinical statistics of the adrenal tumor area are two crucial diagnostic and differential diagnostic features, indicating precise tumor segmentation is essential. Therefore, we build a CT image segmentation method based on an encoder–decoder structure combined with a Transformer for volumetric segmentation of adrenal tumors. This study included a total of
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Differences in intestinal motility during different sleep stages based on long-term bowel sounds BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-11-02 Guojing Wang, Yibing Chen, Hongyun Liu, Xiaohua Yu, Yi Han, Weidong Wang, Hongyan Kang
This study focused on changes in intestinal motility during different sleep stages based on long-term bowel sounds. A modified higher order statistics algorithm was devised to identify the effective bowel sound segments. Next, characteristic values (CVs) were extracted from each bowel sound segment, which included 4 time-domain, 4 frequency-domain and 2 nonlinear CVs. The statistical analysis of these
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Deep learning algorithm performance in contouring head and neck organs at risk: a systematic review and single-arm meta-analysis BioMed. Eng. OnLine (IF 3.9) Pub Date : 2023-11-01 Peiru Liu, Ying Sun, Xinzhuo Zhao, Ying Yan
The contouring of organs at risk (OARs) in head and neck cancer radiation treatment planning is a crucial, yet repetitive and time-consuming process. Recent studies have applied deep learning (DL) algorithms to automatically contour head and neck OARs. This study aims to conduct a systematic review and meta-analysis to summarize and analyze the performance of DL algorithms in contouring head and neck