Artificial Intelligence in Medicine publishes original articles from a wide variety of interdisciplinary perspectives concerning the theory and practice of artificial intelligence (AI) in medicine, medically-oriented human biology, and health care.
Artificial intelligence in medicine may be characterized as the scientific discipline pertaining to research studies, projects, and applications that aim at supporting decision-based medical tasks through knowledge- and/or data-intensive computer-based solutions that ultimately support and improve the performance of a human care provider.
Artificial Intelligence in Medicine considers for publication manuscripts that have both:
• Potential high impact in some medical or healthcare domain;
• Strong novelty of method and theory related to AI and computer science techniques.
Artificial Intelligence in Medicine papers must refer to real-world medical domains, considered and discussed at the proper depth, from both the technical and the medical points of view. The inclusion of a clinical assessment of the usefulness and potential impact of the submitted work is strongly recommended.
Artificial Intelligence in Medicine is looking for novelty in the methodological and/or theoretical content of submitted papers. Such kind of novelty has to be mainly acknowledged in the area of AI and Computer Science. Methodological papers deal with the proposal of some strategy and related methods to solve some scientific issues in specific domains. They must show, usually through an experimental evaluation, how the proposed methodology can be applied to medicine, medically-oriented human biology, and health care, respectively. They have also to provide a comparison with other proposals, and explicitly discuss elements of novelty. Theoretical papers focus on more fundamental, general and formal topics of AI and must show the novel expected effects of the proposed solution in some medical or healthcare field.
Following the information explosion brought by the diffusion of Internet, social networks, cloud computing, and big-data platforms, Artificial Intelligence in Medicine has broadened its perspective. Particular attention is given to novel research work pertaining to:
- AI-based clinical decision making;
- Medical knowledge engineering;
- Knowledge-based and agent-based systems;
- Computational intelligence in bio- and clinical medicine;
- Intelligent and process-aware information systems in healthcare and medicine;
- Natural language processing in medicine;
- Data analytics and mining for biomedical decision support;
- New computational platforms and models for biomedicine;
- Intelligent exploitation of heterogeneous data sources aimed at supporting decision-based and data-intensive clinical tasks;
- Intelligent devices and instruments;
- Automated reasoning and meta-reasoning in medicine;
- Machine learning in medicine, medically-oriented human biology, and healthcare;
- AI and data science in medicine, medically-oriented human biology, and healthcare;
- AI-based modeling and management of healthcare pathways and clinical guidelines;
- Models and systems for AI-based population health;
- AI in medical and healthcare education;
- Methodological, philosophical, ethical, and social issues of AI in healthcare, medically-oriented human biology, and medicine.
If you are considering submitting to Artificial Intelligence in Medicine, make sure that your paper meets the quality requirements mentioned above. English exposition must also be clear and revised with due care. Authors are kindly requested to revise their manuscripts with the help of co-authors that are fluent in English or language editing services before submitting their contribution. Papers written in poor English are likely to be rejected.
The mere application of well-known or already published algorithms and techniques to medical data is not regarded as original research work of interest for Artificial Intelligence in Medicine, but it may be suitable for other venues.
Artificial Intelligence in Medicine features the following kinds of papers:
- Original research contributions: Theoretical and/or methodological papers about novel approaches;
- Methodological reviews/surveys: Papers that collect, classify, describe, and critically analyze research designs, methods and procedures;
- Position papers: Papers that gather, describe, and analyze the scientific challenges of a specific field, founding them on the related literature;
- Editorials: Editors will occasionally publish editorials;
- Guest editorials: Editors can invite guest editors of special issues to publish editorials. Unsolicited editorials will not be considered;
- Letters to the editor: Letters from readers shortly discussing and commenting on a topic of interest, for example based on recently published articles in the journal Artificial Intelligence in Medicine;
- Book reviews: A critical review of recently published books;
- Erratum: Some specific corrections to results previously published in the journal Artificial Intelligence in Medicine;
- Historical perspectives: Papers that describe and critically review some specific aspects in the history of scientific contributions and applications;
- In memoriam: Papers describing the life and the main scientific contributions of scientists passed away, having had an important role in the area of artificial intelligence in medicine;
- PhD projects: Early publications about more recent research trends, having the goal of allowing PhD candidates to explain their PhD research project and to share it with other scientists interested in the topic. Such type of papers should focus on the overall goals and approaches of PhD research projects, without considering in detail the specific scientific results obtained, which would be the focus of other research articles.
Special Issues are regularly published and included among regular issues. Artificial Intelligence in Medicine is looking for special issues about current theoretical/methodological research or convincing applications related to AI in medicine. Special Issues compiled by one or more guest editors who are outstanding experts on the selected topic.
Artificial Intelligence in Medicine does not publish conference volumes or conference papers. However, selected and high-quality research results presented earlier at conferences may be published in Artificial Intelligence in Medicine, in the form of a thoroughly revised (rephrased) and extended (including new research results) original research paper.
Information for authors and further details about the editorial process can be found in the Guide for Authors section of the Artificial Intelligence in Medicine web page.
Carlo CombiUniversity of Verona Department of Computer Science, strada Le Grazie 15, 37134, Verona, Italy Email Carlo Combi
Zhengxing HuangZhejiang University College of Biomedical Engineering and Instrument Science, 866 Yuhangtang Road, 310027, Hangzhou, China
Zhiyong LuNational Library of Medicine, Bethesda, Maryland, 20894-0001, United States Dr. Lu serves in his personal capacity and does not represent the opinions or policies of his employer.
Gregor StiglicUniversity of Maribor Faculty of Health Sciences, Žitna ulica 15, 2000, Maribor, Slovenia
Ameen Abu-HannaAcademic Medical Center, Amsterdam, Netherlands
Enrico Gugliemo CoieraMacquarie University Australian Institute of Health Innovation, Level 6, 75 Talavera Road, North Ryde, 2113, New South Wales, Australia
Alan RectorThe University of Manchester, Kilburn Building-2.88A - Oxford Road, M13 9PL, Manchester, United Kingdom
James ReggiaUniversity of Maryland at College Park Department of Computer Science, A.V. Williams Building, 8223 Paint Branch Drive, College Park, Maryland, 20742, United States
Eytan RuppinUniversity of Maryland at College Park Center for Bioinformatics and Computational Biology, College Park, Maryland, 20742-0001, United States
Shusaku TsumotoShimane University Faculty of Medicine Graduate School of Medicine Department of Medical Informatics, 89-1 Enya-cho, 693-8501, Izumo, Japan
Francesca ZerbatoUniversity of Verona Department of Computer Science, strada Le Grazie 15, 37134, Verona, Italy Email Francesca Zerbato
K. Sadegh-ZadehUniversity of Münster Institute of Ethics History and Theory of Medicine, Münster, Germany
Klaus-Peter AdlassnigMedical University of Vienna Centre for Medical Statistics Informatics and Intelligent Systems, Spitalgasse 23 Vienna, 1090, Wien, Austria
Anna FabijańskaLodz University of Technology Institute of Applied Computer Science, 18/22 Stefanowskiego Str., 90-537, Łódź, Poland Computer vision, Image processing and analysis, Machine learning, Neural networks and Deep learning
Germain ForestierIRIMAS - University of Haute-Alsace, 12 rue des freres Lumiere, 68093, Mulhouse, France Data science, Artificial intelligence, Machine learning, Data mining, Time series classification, Big data, Deep learning
Peter HaddawyMahidol University Faculty of Information and Communication Technology, ICT Building, 999 Phuttamonthon 4 Road, Salaya, 73170, Nakhon Pathom, Thailand
Udo HahnFriedrich Schiller University Jena, 07743, Jena, Germany
Frank van HarmelenFree University of Amsterdam Computational Intelligence Group, de Boelelaan 1081a, 1081HV, Amsterdam, Netherlands
Milos HauskrechtUniversity of Pittsburgh Department of Computer Science, 5329 Sennott Square, Pittsburgh, Pennsylvania, 15260, United States
John HolmesUniversity of Pennsylvania Department of Biostatistics and Epidemiology, 423 Guardian Drive, Philadelphia, Pennsylvania, 19104-6021, United States
Andreas HolzingerMedical University of Graz, Institute for Medical Informatics/Statistics, Graz, AustriaExplainable AI
Elpida Keravnou-PapailiouUniversity of Cyprus Department of Computer Science, 75 Kallipoleos St, P.O Box 20537, CY 1678, Lefkosia, Cyprus
Jiao LiChinese Academy of Medical Sciences & Peking Union Medical College Medical Library, 3rd Yabao Road, Chaoyang District, 100020, Beijing, China Medical Informatics, Data Mining, Knowledge Engineering, Natural Language Processing
Peter LucasLeiden University, 2300 RA, Leiden, Netherlands Biomedical artificial intelligence; Bayesian networks; Model-based reasoning; Statistical machine learning
Mar MarcosJaume I University Department of Computer Engineering and Science, Campus de Riu Sec, 12071, Castellón de la Plana, Spain
Arnau OliverUniversity of Girona, Institute of Computer Vision and Robotics, Department Computer Architecture and Technology, Polytechnical School, P-IV building (Office 015)Campus Montilivi, Edifici P-IV, Av, Lluís Santaló, s/n,, 17003, Girona, Spain Medical Image Computing, Medical Image Analysis, Computer-Aided Diagnosis
Jyotishman PathakCornell University Division of Health Informatics, 425 E. 61st., Suite 301, New York, New York, 10065, United States
Niels PeekUniversity of Manchester Health e-Research Centre, Oxford Rd, M13 9PL, Manchester, United Kingdom
Giuseppe PozziPolytechnic of Milan Department of Electronics Information and Bioengineering, Piazza Leonardo Da Vinci, 32, 20133, Milano, Italy
Balakrishnan PrabhakaranUniversity of Texas at Dallas Erik Jonsson School of Engineering and Computer Science, 800 W. Campbell Road, Richardson, Texas, Texas 75080, United States
Lucia SacchiUniversity of Pavia, Department of Electrical, Computer and Biomedical Engineering, Pavia, Italy Medical Informatics; Machine Learning; Data Mining; Clinical Decision Support Systems
Yuval ShaharBen-Gurion University of the Negev Medical Informatics Research Center, Israel, 84105, Beer-Sheva, Israel
Constantine SpyropoulosInstitute of Informatics & Telecommunications, N.C.S.R. Demokritos 15310, Aghia Paraskevi, Greece
Annette ten TeijeVU Amsterdam, Faculty of Science, Computer Sciences, Amsterdam, NetherlandsArtificial Intelligence; Knowledge Representation and Reasoning; Medical Knowledge Representation
Mauro VallatiUniversity of Huddersfield School of Computing and Engineering, Queensgate, HD1 3DH, Huddersfield, United Kingdom Artificial Intelligence: Planning and Argumentation, Innovative applications of AI in Medicine
Shyam VisweswaranUniversity of Pittsburgh, Pittsburgh, Pennsylvania, 15261, United States
Fei WangCornell University Division of Health Informatics, 425 E. 61st., Suite 301, New York, New York, 10065, United States
Chris YangDrexel University, 3141 Chestnut Street, Philadelphia, Philadelphia, 19104-2816, Pennsylvania, USA
Marinka ZitnikStanford University Department of Computer Science, 353 Serra Mall, Stanford, California, CA 94305, United States Representation learning for biomedicine, Network embedding methods, Next-generation algorithms for networks, Contextually adaptive AI
Blaz ZupanBioinformatics Laboratory,Fac. of Computer and Information Science,University of Ljubljana, Večna pot 113, 1000, Ljubljana, Slovenia
Pierre ZweigenbaumComputing Laboratory for Mechanics and Engineering Sciences, Campus universitaire bât 508, Rue John Von Neumann, 91400, Orsay, France Natural Language Processing
PhD students and postdocs - Editorial Board
Ye YeUniversity of Pittsburgh Department of Biomedical Informatics, 5607 Baum Boulevard, Pittsburgh, Pennsylvania, 15213-3305, United States