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A machine learning framework supporting prospective clinical decisions applied to risk prediction in oncology npj Digit. Med. (IF 15.357) Pub Date : 2022-08-16 Lorinda Coombs, Abigail Orlando, Xiaoliang Wang, Pooja Shaw, Alexander S. Rich, Shreyas Lakhtakia, Karen Titchener, Blythe Adamson, Rebecca A. Miksad, Kathi Mooney
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Fast and noninvasive electronic nose for sniffing out COVID-19 based on exhaled breath-print recognition npj Digit. Med. (IF 15.357) Pub Date : 2022-08-16 Dian Kesumapramudya Nurputra, Ahmad Kusumaatmaja, Mohamad Saifudin Hakim, Shidiq Nur Hidayat, Trisna Julian, Budi Sumanto, Yodi Mahendradhata, Antonia Morita Iswari Saktiawati, Hutomo Suryo Wasisto, Kuwat Triyana
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A systems approach towards remote health-monitoring in older adults: Introducing a zero-interaction digital exhaust npj Digit. Med. (IF 15.357) Pub Date : 2022-08-16 Narayan Schütz, Samuel E. J. Knobel, Angela Botros, Michael Single, Bruno Pais, Valérie Santschi, Daniel Gatica-Perez, Philipp Buluschek, Prabitha Urwyler, Stephan M. Gerber, René M. Müri, Urs P. Mosimann, Hugo Saner, Tobias Nef
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Leveraging reimbursement strategies to guide value-based adoption and utilization of medical AI npj Digit. Med. (IF 15.357) Pub Date : 2022-08-10 Kaushik P. Venkatesh, Marium M. Raza, James A. Diao, Joseph C. Kvedar
With the increasing number of FDA-approved artificial intelligence (AI) systems, the financing of these technologies has become a primary gatekeeper to mass clinical adoption. Reimbursement models adapted for current payment schemes, including per-use rates, are feasible for early AI products. Alternative and complementary models may offer future payment options for value-based AI. A successful reimbursement
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Interactive exploration of a global clinical network from a large breast cancer cohort npj Digit. Med. (IF 15.357) Pub Date : 2022-08-10 Nadir Sella, Anne-Sophie Hamy, Vincent Cabeli, Lauren Darrigues, Marick Laé, Fabien Reyal, Hervé Isambert
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A computational framework for discovering digital biomarkers of glycemic control npj Digit. Med. (IF 15.357) Pub Date : 2022-08-08 Abigail Bartolome, Temiloluwa Prioleau
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Developing machine learning algorithms for dynamic estimation of progression during active surveillance for prostate cancer npj Digit. Med. (IF 15.357) Pub Date : 2022-08-06 Changhee Lee, Alexander Light, Evgeny S. Saveliev, Mihaela van der Schaar, Vincent J. Gnanapragasam
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Clinical use of artificial intelligence in endometriosis: a scoping review npj Digit. Med. (IF 15.357) Pub Date : 2022-08-04 Brintha Sivajohan, Mohamed Elgendi, Carlo Menon, Catherine Allaire, Paul Yong, Mohamed A. Bedaiwy
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Diagnostic accuracy of telemedicine for detection of surgical site infection: a systematic review and meta-analysis npj Digit. Med. (IF 15.357) Pub Date : 2022-08-03 Ross Lathan, Misha Sidapra, Marina Yiasemidou, Judith Long, Joshua Totty, George Smith, Ian Chetter
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Localization-adjusted diagnostic performance and assistance effect of a computer-aided detection system for pneumothorax and consolidation npj Digit. Med. (IF 15.357) Pub Date : 2022-07-30 Sun Yeop Lee, Sangwoo Ha, Min Gyeong Jeon, Hao Li, Hyunju Choi, Hwa Pyung Kim, Ye Ra Choi, Hoseok I, Yeon Joo Jeong, Yoon Ha Park, Hyemin Ahn, Sang Hyup Hong, Hyun Jung Koo, Choong Wook Lee, Min Jae Kim, Yeon Joo Kim, Kyung Won Kim, Jong Mun Choi
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Identification of robust deep neural network models of longitudinal clinical measurements npj Digit. Med. (IF 15.357) Pub Date : 2022-07-27 Hamed Javidi, Arshiya Mariam, Gholamreza Khademi, Emily C. Zabor, Ran Zhao, Tomas Radivoyevitch, Daniel M. Rotroff
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Silhouette images enable estimation of body fat distribution and associated cardiometabolic risk npj Digit. Med. (IF 15.357) Pub Date : 2022-07-27 Marcus D. R. Klarqvist, Saaket Agrawal, Nathaniel Diamant, Patrick T. Ellinor, Anthony Philippakis, Kenney Ng, Puneet Batra, Amit V. Khera
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Machine learning for real-time aggregated prediction of hospital admission for emergency patients npj Digit. Med. (IF 15.357) Pub Date : 2022-07-26 Zella King, Joseph Farrington, Martin Utley, Enoch Kung, Samer Elkhodair, Steve Harris, Richard Sekula, Jonathan Gillham, Kezhi Li, Sonya Crowe
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Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations npj Digit. Med. (IF 15.357) Pub Date : 2022-07-22 Niccolò Marini, Stefano Marchesin, Sebastian Otálora, Marek Wodzinski, Alessandro Caputo, Mart van Rijthoven, Witali Aswolinskiy, John-Melle Bokhorst, Damian Podareanu, Edyta Petters, Svetla Boytcheva, Genziana Buttafuoco, Simona Vatrano, Filippo Fraggetta, Jeroen van der Laak, Maristella Agosti, Francesco Ciompi, Gianmaria Silvello, Henning Muller, Manfredo Atzori
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Age estimation from sleep studies using deep learning predicts life expectancy npj Digit. Med. (IF 15.357) Pub Date : 2022-07-22 Andreas Brink-Kjaer, Eileen B. Leary, Haoqi Sun, M. Brandon Westover, Katie L. Stone, Paul E. Peppard, Nancy E. Lane, Peggy M. Cawthon, Susan Redline, Poul Jennum, Helge B. D. Sorensen, Emmanuel Mignot
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Human–machine teaming is key to AI adoption: clinicians’ experiences with a deployed machine learning system npj Digit. Med. (IF 15.357) Pub Date : 2022-07-21 Katharine E. Henry, Rachel Kornfield, Anirudh Sridharan, Robert C. Linton, Catherine Groh, Tony Wang, Albert Wu, Bilge Mutlu, Suchi Saria
While a growing number of machine learning (ML) systems have been deployed in clinical settings with the promise of improving patient care, many have struggled to gain adoption and realize this promise. Based on a qualitative analysis of coded interviews with clinicians who use an ML-based system for sepsis, we found that, rather than viewing the system as a surrogate for their clinical judgment, clinicians
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Effectiveness of automated alerting system compared to usual care for the management of sepsis npj Digit. Med. (IF 15.357) Pub Date : 2022-07-19 Zhongheng Zhang, Lin Chen, Ping Xu, Qing Wang, Jianjun Zhang, Kun Chen, Casey M. Clements, Leo Anthony Celi, Vitaly Herasevich, Yucai Hong
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A Delphi consensus statement for digital surgery npj Digit. Med. (IF 15.357) Pub Date : 2022-07-19 Kyle Lam, Michael D. Abràmoff, José M. Balibrea, Steven M. Bishop, Richard R. Brady, Rachael A. Callcut, Manish Chand, Justin W. Collins, Markus K. Diener, Matthias Eisenmann, Kelly Fermont, Manoel Galvao Neto, Gregory D. Hager, Robert J. Hinchliffe, Alan Horgan, Pierre Jannin, Alexander Langerman, Kartik Logishetty, Amit Mahadik, Lena Maier-Hein, Esteban Martín Antona, Pietro Mascagni, Ryan K. Mathew
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A systematic review of healthcare provider-targeted mobile applications for non-communicable diseases in low- and middle-income countries npj Digit. Med. (IF 15.357) Pub Date : 2022-07-19 Pascal Geldsetzer, Sergio Flores, Grace Wang, Blanca Flores, Abu Bakarr Rogers, Aditi Bunker, Andrew Y. Chang, Rebecca Tisdale
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A randomized controlled trial enhancing viral hepatitis testing in primary care via digital crowdsourced intervention npj Digit. Med. (IF 15.357) Pub Date : 2022-07-19 William C. W. Wong, Gifty Marley, Jingjing Li, Weihui Yan, Po-lin Chan, Joseph D. Tucker, Weiming Tang, Yuxin Ni, Dan Dan Cheng, Lou Cong, Wai-Kay Seto
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Automated video-based assessment of facial bradykinesia in de-novo Parkinson’s disease npj Digit. Med. (IF 15.357) Pub Date : 2022-07-18 Michal Novotny, Tereza Tykalova, Hana Ruzickova, Evzen Ruzicka, Petr Dusek, Jan Rusz
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Dynamic prediction of mortality after traumatic brain injury using a machine learning algorithm npj Digit. Med. (IF 15.357) Pub Date : 2022-07-18 Rahul Raj, Jenni M. Wennervirta, Jonathan Tjerkaski, Teemu M. Luoto, Jussi P. Posti, David W. Nelson, Riikka Takala, Stepani Bendel, Eric P. Thelin, Teemu Luostarinen, Miikka Korja
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Multisite implementation of a workflow-integrated machine learning system to optimize COVID-19 hospital admission decisions npj Digit. Med. (IF 15.357) Pub Date : 2022-07-16 Jeremiah S. Hinson, Eili Klein, Aria Smith, Matthew Toerper, Trushar Dungarani, David Hager, Peter Hill, Gabor Kelen, Joshua D. Niforatos, R. Scott Stephens, Alexandra T. Strauss, Scott Levin
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Identifying and characterising sources of variability in digital outcome measures in Parkinson’s disease npj Digit. Med. (IF 15.357) Pub Date : 2022-07-15 George Roussos, Teresa Ruiz Herrero, Derek L. Hill, Ariel V. Dowling, Martijn L. T. M. Müller, Luc J. W. Evers, Jackson Burton, Adrian Derungs, Katherine Fisher, Krishna Praneeth Kilambi, Nitin Mehrotra, Roopal Bhatnagar, Sakshi Sardar, Diane Stephenson, Jamie L. Adams, E. Ray Dorsey, Josh Cosman
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Multi-center validation of machine learning model for preoperative prediction of postoperative mortality npj Digit. Med. (IF 15.357) Pub Date : 2022-07-12 Seung Wook Lee, Hyung-Chul Lee, Jungyo Suh, Kyung Hyun Lee, Heonyi Lee, Suryang Seo, Tae Kyong Kim, Sang-Wook Lee, Yi-Jun Kim
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Integrating digital pathology and mathematical modelling to predict spatial biomarker dynamics in cancer immunotherapy npj Digit. Med. (IF 15.357) Pub Date : 2022-07-12 L. G. Hutchinson, O. Grimm
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Medical domain knowledge in domain-agnostic generative AI npj Digit. Med. (IF 15.357) Pub Date : 2022-07-11 Jakob Nikolas Kather, Narmin Ghaffari Laleh, Sebastian Foersch, Daniel Truhn
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Machine learning-based quantitative prediction of drug exposure in drug-drug interactions using drug label information npj Digit. Med. (IF 15.357) Pub Date : 2022-07-11 Ha Young Jang, Jihyeon Song, Jae Hyun Kim, Howard Lee, In-Wha Kim, Bongki Moon, Jung Mi Oh
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The promise of machine learning applications in solid organ transplantation npj Digit. Med. (IF 15.357) Pub Date : 2022-07-11 Neta Gotlieb, Amirhossein Azhie, Divya Sharma, Ashley Spann, Nan-Ji Suo, Jason Tran, Ani Orchanian-Cheff, Bo Wang, Anna Goldenberg, Michael Chassé, Heloise Cardinal, Joseph Paul Cohen, Andrea Lodi, Melanie Dieude, Mamatha Bhat
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The performance of artificial intelligence-driven technologies in diagnosing mental disorders: an umbrella review npj Digit. Med. (IF 15.357) Pub Date : 2022-07-07 Alaa Abd-alrazaq, Dari Alhuwail, Jens Schneider, Carla T. Toro, Arfan Ahmed, Mahmood Alzubaidi, Mohannad Alajlani, Mowafa Househ
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Blood pressure measurement using only a smartphone npj Digit. Med. (IF 15.357) Pub Date : 2022-07-06 Lorenz Frey, Carlo Menon, Mohamed Elgendi
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Cross-Platform Omics Prediction procedure: a statistical machine learning framework for wider implementation of precision medicine npj Digit. Med. (IF 15.357) Pub Date : 2022-07-04 Kevin Y. X. Wang, Gulietta M. Pupo, Varsha Tembe, Ellis Patrick, Dario Strbenac, Sarah-Jane Schramm, John F. Thompson, Richard A. Scolyer, Samuel Muller, Garth Tarr, Graham J. Mann, Jean Y. H. Yang
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The IDentif.AI-x pandemic readiness platform: Rapid prioritization of optimized COVID-19 combination therapy regimens npj Digit. Med. (IF 15.357) Pub Date : 2022-06-30 Agata Blasiak, Anh T. L. Truong, Alexandria Remus, Lissa Hooi, Shirley Gek Kheng Seah, Peter Wang, De Hoe Chye, Angeline Pei Chiew Lim, Kim Tien Ng, Swee Teng Teo, Yee-Joo Tan, David Michael Allen, Louis Yi Ann Chai, Wee Joo Chng, Raymond T. P. Lin, David C. B. Lye, John Eu-Li Wong, Gek-Yen Gladys Tan, Conrad En Zuo Chan, Edward Kai-Hua Chow, Dean Ho
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A novel AI device for real-time optical characterization of colorectal polyps npj Digit. Med. (IF 15.357) Pub Date : 2022-06-30 Carlo Biffi, Pietro Salvagnini, Nhan Ngo Dinh, Cesare Hassan, Prateek Sharma, Andrea Cherubini
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A systematic review of engagement reporting in remote measurement studies for health symptom tracking npj Digit. Med. (IF 15.357) Pub Date : 2022-06-29 Katie M. White, Charlotte Williamson, Nicol Bergou, Carolin Oetzmann, Valeria de Angel, Faith Matcham, Claire Henderson, Matthew Hotopf
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Smartphone camera based assessment of adiposity: a validation study npj Digit. Med. (IF 15.357) Pub Date : 2022-06-29 Maulik D. Majmudar, Siddhartha Chandra, Kiran Yakkala, Samantha Kennedy, Amit Agrawal, Mark Sippel, Prakash Ramu, Apoorv Chaudhri, Brooke Smith, Antonio Criminisi, Steven B. Heymsfield, Fatima Cody Stanford
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International electronic health record-derived post-acute sequelae profiles of COVID-19 patients npj Digit. Med. (IF 15.357) Pub Date : 2022-06-29 Harrison G. Zhang, Arianna Dagliati, Zahra Shakeri Hossein Abad, Xin Xiong, Clara-Lea Bonzel, Zongqi Xia, Bryce W. Q. Tan, Paul Avillach, Gabriel A. Brat, Chuan Hong, Michele Morris, Shyam Visweswaran, Lav P. Patel, Alba Gutiérrez-Sacristán, David A. Hanauer, John H. Holmes, Malarkodi Jebathilagam Samayamuthu, Florence T. Bourgeois, Sehi L’Yi, Sarah E. Maidlow, Bertrand Moal, Shawn N. Murphy, Zachary
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Pandemic-proof recruitment and engagement in a fully decentralized trial in atrial fibrillation patients (DeTAP) npj Digit. Med. (IF 15.357) Pub Date : 2022-06-28 Ashish Sarraju, Clark Seninger, Vijaya Parameswaran, Christina Petlura, Tamara Bazouzi, Kiranbir Josan, Upinder Grewal, Thomas Viethen, Hardi Mundl, Joachim Luithle, Leonard Basobas, Alexis Touros, Michael J. T. Senior, Koen De Lombaert, Kenneth W. Mahaffey, Mintu P. Turakhia, Rajesh Dash
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Enhancing self-management in type 1 diabetes with wearables and deep learning npj Digit. Med. (IF 15.357) Pub Date : 2022-06-27 Taiyu Zhu, Chukwuma Uduku, Kezhi Li, Pau Herrero, Nick Oliver, Pantelis Georgiou
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Distributed learning for heterogeneous clinical data with application to integrating COVID-19 data across 230 sites npj Digit. Med. (IF 15.357) Pub Date : 2022-06-14 Jiayi Tong, Chongliang Luo, Md Nazmul Islam, Natalie E. Sheils, John Buresh, Mackenzie Edmondson, Peter A. Merkel, Ebbing Lautenbach, Rui Duan, Yong Chen
Integrating real-world data (RWD) from several clinical sites offers great opportunities to improve estimation with a more general population compared to analyses based on a single clinical site. However, sharing patient-level data across sites is practically challenging due to concerns about maintaining patient privacy. We develop a distributed algorithm to integrate heterogeneous RWD from multiple
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Harmonization and standardization of data for a pan-European cohort on SARS- CoV-2 pandemic npj Digit. Med. (IF 15.357) Pub Date : 2022-06-14 Eugenia Rinaldi, Caroline Stellmach, Naveen Moses Raj Rajkumar, Natascia Caroccia, Chiara Dellacasa, Maddalena Giannella, Mariana Guedes, Massimo Mirandola, Gabriella Scipione, Evelina Tacconelli, Sylvia Thun
The European project ORCHESTRA intends to create a new pan-European cohort to rapidly advance the knowledge of the effects and treatment of COVID-19. Establishing processes that facilitate the merging of heterogeneous clusters of retrospective data was an essential challenge. In addition, data from new ORCHESTRA prospective studies have to be compatible with earlier collected information to be efficiently
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Computational drug repurposing based on electronic health records: a scoping review npj Digit. Med. (IF 15.357) Pub Date : 2022-06-14 Nansu Zong, Andrew Wen, Sungrim Moon, Sunyang Fu, Liwei Wang, Yiqing Zhao, Yue Yu, Ming Huang, Yanshan Wang, Gang Zheng, Michelle M. Mielke, James R. Cerhan, Hongfang Liu
Computational drug repurposing methods adapt Artificial intelligence (AI) algorithms for the discovery of new applications of approved or investigational drugs. Among the heterogeneous datasets, electronic health records (EHRs) datasets provide rich longitudinal and pathophysiological data that facilitate the generation and validation of drug repurposing. Here, we present an appraisal of recently published
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Watching Parkinson’s disease with wrist-based sensors npj Digit. Med. (IF 15.357) Pub Date : 2022-06-13 James A. Diao, Marium M. Raza, Kaushik P. Venkatesh, Joseph C. Kvedar
Parkinson’s disease (PD) lacks sensitive, objective, and reliable measures for disease progression and response. This presents a challenge for clinical trials given the multifaceted and fluctuating nature of PD symptoms. Innovations in digital health and wearable sensors promise to more precisely measure aspects of patient function and well-being. Beyond research trials, digital biomarkers and clinical
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International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality npj Digit. Med. (IF 15.357) Pub Date : 2022-06-13 Griffin M. Weber, Chuan Hong, Zongqi Xia, Nathan P. Palmer, Paul Avillach, Sehi L’Yi, Mark S. Keller, Shawn N. Murphy, Alba Gutiérrez-Sacristán, Clara-Lea Bonzel, Arnaud Serret-Larmande, Antoine Neuraz, Gilbert S. Omenn, Shyam Visweswaran, Jeffrey G. Klann, Andrew M. South, Ne Hooi Will Loh, Mario Cannataro, Brett K. Beaulieu-Jones, Riccardo Bellazzi, Giuseppe Agapito, Mario Alessiani, Bruce J. Aronow
Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents.
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A reimbursement framework for artificial intelligence in healthcare npj Digit. Med. (IF 15.357) Pub Date : 2022-06-09 Michael D. Abràmoff, Cybil Roehrenbeck, Sylvia Trujillo, Juli Goldstein, Anitra S. Graves, Michael X. Repka, Ezequiel “Zeke” Silva III
Responsible adoption of healthcare artificial intelligence (AI) requires that AI systems which benefit patients and populations, including autonomous AI systems, are incentivized financially at a consistent and sustainable level. We present a framework for analytically determining value and cost of each unique AI service. The framework’s processes involve affected stakeholders, including patients,
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Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials npj Digit. Med. (IF 15.357) Pub Date : 2022-06-08 Andre Esteva, Jean Feng, Douwe van der Wal, Shih-Cheng Huang, Jeffry P. Simko, Sandy DeVries, Emmalyn Chen, Edward M. Schaeffer, Todd M. Morgan, Yilun Sun, Amirata Ghorbani, Nikhil Naik, Dhruv Nathawani, Richard Socher, Jeff M. Michalski, Mack Roach, Thomas M. Pisansky, Jedidiah M. Monson, Farah Naz, James Wallace, Michelle J. Ferguson, Jean-Paul Bahary, James Zou, Matthew Lungren, Serena Yeung, Ashley
Prostate cancer is the most frequent cancer in men and a leading cause of cancer death. Determining a patient’s optimal therapy is a challenge, where oncologists must select a therapy with the highest likelihood of success and the lowest likelihood of toxicity. International standards for prognostication rely on non-specific and semi-quantitative tools, commonly leading to over- and under-treatment
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Highlighting uncertainty in clinical risk prediction using a model of emergency laparotomy mortality risk npj Digit. Med. (IF 15.357) Pub Date : 2022-06-08 Jakob F. Mathiszig-Lee, Finneas J. R. Catling, S. Ramani Moonesinghe, Stephen J. Brett
Clinical prediction models typically make point estimates of risk. However, values of key variables are often missing during model development or at prediction time, meaning that the point estimates mask significant uncertainty and can lead to over-confident decision making. We present a model of mortality risk in emergency laparotomy which instead presents a distribution of predicted risks, highlighting
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Machine learning generalizability across healthcare settings: insights from multi-site COVID-19 screening npj Digit. Med. (IF 15.357) Pub Date : 2022-06-07 Jenny Yang, Andrew A. S. Soltan, David A. Clifton
As patient health information is highly regulated due to privacy concerns, most machine learning (ML)-based healthcare studies are unable to test on external patient cohorts, resulting in a gap between locally reported model performance and cross-site generalizability. Different approaches have been introduced for developing models across multiple clinical sites, however less attention has been given
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Improving preeclampsia risk prediction by modeling pregnancy trajectories from routinely collected electronic medical record data npj Digit. Med. (IF 15.357) Pub Date : 2022-06-06 Shilong Li, Zichen Wang, Luciana A. Vieira, Amanda B. Zheutlin, Boshu Ru, Emilio Schadt, Pei Wang, Alan B. Copperman, Joanne L. Stone, Susan J. Gross, Yu-Han Kao, Yan Kwan Lau, Siobhan M. Dolan, Eric E. Schadt, Li Li
Preeclampsia is a heterogeneous and complex disease associated with rising morbidity and mortality in pregnant women and newborns in the US. Early recognition of patients at risk is a pressing clinical need to reduce the risk of adverse outcomes. We assessed whether information routinely collected in electronic medical records (EMR) could enhance the prediction of preeclampsia risk beyond what is achieved
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Aligning mission to digital health strategy in academic medical centers npj Digit. Med. (IF 15.357) Pub Date : 2022-06-02 Adam B. Cohen, Lisa Stump, Harlan M. Krumholz, Margaret Cartiera, Sanchita Jain, L. Scott Sussman, Allen Hsiao, Walter Lindop, Anita Kuo Ying, Rebecca L. Kaul, Thomas J. Balcezak, Welela Tereffe, Matthew Comerford, Daniel Jacoby, Neema Navai
The strategies of academic medical centers arise from core values and missions that aim to provide unmatched clinical care, patient experience, research, education, and training. These missions drive nearly all activities. They should also drive digital health activities – and particularly now given the rapid adoption of digital health, marking one of the great transformations of healthcare; increasing
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Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare npj Digit. Med. (IF 15.357) Pub Date : 2022-05-31 Jean Feng, Rachael V. Phillips, Ivana Malenica, Andrew Bishara, Alan E. Hubbard, Leo A. Celi, Romain Pirracchio
Machine learning (ML) and artificial intelligence (AI) algorithms have the potential to derive insights from clinical data and improve patient outcomes. However, these highly complex systems are sensitive to changes in the environment and liable to performance decay. Even after their successful integration into clinical practice, ML/AI algorithms should be continuously monitored and updated to ensure
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Virtual exam for Parkinson’s disease enables frequent and reliable remote measurements of motor function npj Digit. Med. (IF 15.357) Pub Date : 2022-05-23 Maximilien Burq, Erin Rainaldi, King Chung Ho, Chen Chen, Bastiaan R. Bloem, Luc J. W. Evers, Rick C. Helmich, Lance Myers, William J. Marks, Ritu Kapur
Sensor-based remote monitoring could help better track Parkinson’s disease (PD) progression, and measure patients’ response to putative disease-modifying therapeutic interventions. To be useful, the remotely-collected measurements should be valid, reliable, and sensitive to change, and people with PD must engage with the technology. We developed a smartwatch-based active assessment that enables unsupervised
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Building digital twins of the human immune system: toward a roadmap npj Digit. Med. (IF 15.357) Pub Date : 2022-05-20 R. Laubenbacher, A. Niarakis, T. Helikar, G. An, B. Shapiro, R. S. Malik-Sheriff, T. J. Sego, A. Knapp, P. Macklin, J. A. Glazier
Digital twins, customized simulation models pioneered in industry, are beginning to be deployed in medicine and healthcare, with some major successes, for instance in cardiovascular diagnostics and in insulin pump control. Personalized computational models are also assisting in applications ranging from drug development to treatment optimization. More advanced medical digital twins will be essential
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Paying for artificial intelligence in medicine npj Digit. Med. (IF 15.357) Pub Date : 2022-05-20 Ravi B. Parikh, Lorens A. Helmchen
Over the past 7 years, regulatory agencies have approved hundreds of artificial intelligence (AI) devices for clinical use. In late 2020, payers began reimbursing clinicians and health systems for each use of select image-based AI devices. The experience with traditional medical devices has shown that per-use reimbursement may result in the overuse use of AI. We review current models of paying for
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Potential reduction in healthcare carbon footprint by autonomous artificial intelligence npj Digit. Med. (IF 15.357) Pub Date : 2022-05-12 Risa M. Wolf, Michael D. Abramoff, Roomasa Channa, Chris Tava, Warren Clarida, Harold P. Lehmann
Healthcare is a large contributor to greenhouse gas (GHG) emissions around the world, given current power generation mix. Telemedicine, with its reduced travel for providers and patients, has been proposed to reduce emissions. Artificial intelligence (AI), and especially autonomous AI, where the medical decision is made without human oversight, has the potential to further reduce healthcare GHG emissions
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Multinational landscape of health app policy: toward regulatory consensus on digital health npj Digit. Med. (IF 15.357) Pub Date : 2022-05-11 James A. Diao, Kaushik P. Venkatesh, Marium M. Raza, Joseph C. Kvedar
Due to its enormous capacity for benefit, harm, and cost, health care is among the most tightly regulated industries in the world. But with the rise of smartphones, an explosion of direct-to-consumer mobile health applications has challenged the role of centralized gatekeepers. As interest in health apps continue to climb, national regulatory bodies have turned their attention toward strategies to
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Effect of self-managed lifestyle treatment on glycemic control in patients with type 2 diabetes npj Digit. Med. (IF 15.357) Pub Date : 2022-05-11 Chinmay Dwibedi, Emelia Mellergård, Amaru Cuba Gyllensten, Kristoffer Nilsson, Annika S. Axelsson, Malin Bäckman, Magnus Sahlgren, Stephen H. Friend, Sofie Persson, Stefan Franzén, Birgitta Abrahamsson, Katarina Steen Carlsson, Anders H. Rosengren
The lack of effective, scalable solutions for lifestyle treatment is a global clinical problem, causing severe morbidity and mortality. We developed a method for lifestyle treatment that promotes self-reflection and iterative behavioral change, provided as a digital tool, and evaluated its effect in 370 patients with type 2 diabetes (ClinicalTrials.gov identifier: NCT04691973). Users of the tool had
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Algorithmic fairness in pandemic forecasting: lessons from COVID-19 npj Digit. Med. (IF 15.357) Pub Date : 2022-05-10 Thomas C. Tsai, Sercan Arik, Benjamin H. Jacobson, Jinsung Yoon, Nate Yoder, Dario Sava, Margaret Mitchell, Garth Graham, Tomas Pfister
Racial and ethnic minorities have borne a particularly acute burden of the COVID-19 pandemic in the United States. There is a growing awareness from both researchers and public health leaders of the critical need to ensure fairness in forecast results. Without careful and deliberate bias mitigation, inequities embedded in data can be transferred to model predictions, perpetuating disparities, and exacerbating
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Opportunities and counterintuitive challenges for decentralized clinical trials to broaden participant inclusion npj Digit. Med. (IF 15.357) Pub Date : 2022-05-05 Noah Goodson, Paul Wicks, Jayne Morgan, Leen Hashem, Sinéad Callinan, John Reites
Traditional clinical trials have often failed to recruit representative participant populations. Just 5% of eligible patients participate in clinical research. Participants, particularly those from minority groups, cite geographical constraints, mistrust, miscommunication, and discrimination as barriers. Here, an intersectional view of inclusion in clinical trials provides significant insights into
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Evaluation of an artificial intelligence-based medical device for diagnosis of autism spectrum disorder npj Digit. Med. (IF 15.357) Pub Date : 2022-05-05 Jonathan T. Megerian, Sangeeta Dey, Raun D. Melmed, Daniel L. Coury, Marc Lerner, Christopher J. Nicholls, Kristin Sohl, Rambod Rouhbakhsh, Anandhi Narasimhan, Jonathan Romain, Sailaja Golla, Safiullah Shareef, Andrey Ostrovsky, Jennifer Shannon, Colleen Kraft, Stuart Liu-Mayo, Halim Abbas, Diana E. Gal-Szabo, Dennis P. Wall, Sharief Taraman
Autism spectrum disorder (ASD) can be reliably diagnosed at 18 months, yet significant diagnostic delays persist in the United States. This double-blinded, multi-site, prospective, active comparator cohort study tested the accuracy of an artificial intelligence-based Software as a Medical Device designed to aid primary care healthcare providers (HCPs) in diagnosing ASD. The Device combines behavioral