Published on in Vol 23, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29812, first published .
Analyzing Patient Trajectories With Artificial Intelligence

Analyzing Patient Trajectories With Artificial Intelligence

Analyzing Patient Trajectories With Artificial Intelligence

Journals

  1. Schallmoser S, Zueger T, Kraus M, Saar-Tsechansky M, Stettler C, Feuerriegel S. Machine Learning for Predicting Micro- and Macrovascular Complications in Individuals With Prediabetes or Diabetes: Retrospective Cohort Study. Journal of Medical Internet Research 2023;25:e42181 View
  2. Naumzik C, Feuerriegel S, Nielsen A. Data-driven dynamic treatment planning for chronic diseases. European Journal of Operational Research 2023;305(2):853 View
  3. Kovács A, Tokodi M. Refining Echocardiographic Surveillance of Aortic Stenosis Using Machine Learning. JACC: Cardiovascular Imaging 2023;16(6):745 View
  4. Alkhodari M, Xiong Z, Khandoker A, Hadjileontiadis L, Leeson P, Lapidaire W. The role of artificial intelligence in hypertensive disorders of pregnancy: towards personalized healthcare. Expert Review of Cardiovascular Therapy 2023;21(7):531 View
  5. Denck J, Ozkirimli E, Wang K. Machine-learning-based adverse drug event prediction from observational health data: A review. Drug Discovery Today 2023;28(9):103715 View
  6. Annareddy S, Ghewade B, Jadhav U, Wagh P. Unraveling the Predictive Potential of Rapid Scoring in Pleural Infection: A Critical Review. Cureus 2023 View
  7. Carrasco-Ribelles L, Llanes-Jurado J, Gallego-Moll C, Cabrera-Bean M, Monteagudo-Zaragoza M, Violán C, Zabaleta-del-Olmo E. Prediction models using artificial intelligence and longitudinal data from electronic health records: a systematic methodological review. Journal of the American Medical Informatics Association 2023;30(12):2072 View
  8. Kraus M, Feuerriegel S, Saar-Tsechansky M. Data-Driven Allocation of Preventive Care with Application to Diabetes Mellitus Type II. Manufacturing & Service Operations Management 2024;26(1):137 View
  9. Shi J, Bendig D, Vollmar H, Rasche P. Mapping the Bibliometrics Landscape of AI in Medicine: Methodological Study. Journal of Medical Internet Research 2023;25:e45815 View
  10. Pingi S, Zhang D, Bashar M, Nayak R. Joint Representation Learning with Generative Adversarial Imputation Network for Improved Classification of Longitudinal Data. Data Science and Engineering 2024;9(1):5 View
  11. Wang Y, Li N, Chen L, Wu M, Meng S, Dai Z, Zhang Y, Clarke M. Guidelines, Consensus Statements, and Standards for the Use of Artificial Intelligence in Medicine: Systematic Review. Journal of Medical Internet Research 2023;25:e46089 View
  12. Qian Y, Alhaskawi A, Dong Y, Ni J, Abdalbary S, Lu H. Transforming medicine: artificial intelligence integration in the peripheral nervous system. Frontiers in Neurology 2024;15 View
  13. Palmowski L, Nowak H, Witowski A, Koos B, Wolf A, Weber M, Kleefisch D, Unterberg M, Haberl H, von Busch A, Ertmer C, Zarbock A, Bode C, Putensen C, Limper U, Wappler F, Köhler T, Henzler D, Oswald D, Ellger B, Ehrentraut S, Bergmann L, Rump K, Ziehe D, Babel N, Sitek B, Marcus K, Frey U, Thoral P, Adamzik M, Eisenacher M, Rahmel T, Lazzeri C. Assessing SOFA score trajectories in sepsis using machine learning: A pragmatic approach to improve the accuracy of mortality prediction. PLOS ONE 2024;19(3):e0300739 View
  14. Wang K, Barton D, McQuillan L, Kobeissy F, Cai G, Xu H, Yang Z, Trifilio E, Williamson J, Rubenstein R, Robertson C, Wagner A. Parallel Cerebrospinal Fluid and Serum Temporal Profile Assessment of Axonal Injury Biomarkers Neurofilament-Light Chain and Phosphorylated Neurofilament-Heavy Chain: Associations With Patient Outcome in Moderate-Severe Traumatic Brain Injury. Journal of Neurotrauma 2024;41(13-14):1609 View
  15. Zwaag S, Hunault C, de Lange D. Predicting the outcome in poisoned patients: look at the past!. Clinical Toxicology 2024;62(3):139 View
  16. Kurasawa H, Waki K, Seki T, Chiba A, Fujino A, Hayashi K, Nakahara E, Haga T, Noguchi T, Ohe K. Enhancing Type 2 Diabetes Treatment Decisions With Interpretable Machine Learning Models for Predicting Hemoglobin A1c Changes: Machine Learning Model Development. JMIR AI 2024;3:e56700 View
  17. Jørgensen I, Haue A, Placido D, Hjaltelin J, Brunak S. Disease Trajectories from Healthcare Data: Methodologies, Key Results, and Future Perspectives. Annual Review of Biomedical Data Science 2024;7(1):251 View
  18. Lisik D, Milani G, Salisu M, Özuygur Ermis S, Goksör E, Basna R, Wennergren G, Kankaanranta H, Nwaru B. Machine learning-derived phenotypic trajectories of asthma and allergy in children and adolescents: protocol for a systematic review. BMJ Open 2024;14(8):e080263 View
  19. SENMAN B, SINGH A, KADOSH B, KATZ J. How Steep is Your Slide? I Really Mean to Learn. Journal of Cardiac Failure 2024;30(10):1208 View
  20. Patharkar A, Cai F, Al-Hindawi F, Wu T. Predictive modeling of biomedical temporal data in healthcare applications: review and future directions. Frontiers in Physiology 2024;15 View
  21. Muyama L, Neuraz A, Coulet A. Machine learning approaches for the discovery of clinical pathways from patient data: A systematic review. Journal of Biomedical Informatics 2024;160:104746 View
  22. Bathgate C, Fedele D, Tillman E, He J, Everhart R, Reznikov L, Liu F, Kirby K, Raffensperger K, Traver K, Riekert K, Powers S, Georgiopoulos A. Elexacaftor/tezacaftor/ivacaftor and mental health: A workshop report from the Cystic Fibrosis Foundation's Prioritizing Research in Mental Health working group. Journal of Cystic Fibrosis 2025;24(2):301 View
  23. Mwogosi A. AI-driven optimisation of EHR systems implementation in Tanzania’s primary health care. Transforming Government: People, Process and Policy 2025;19(2):288 View
  24. Zuo Y, Jiang J, Yada K. Application of hybrid gate recurrent unit for in-store trajectory prediction based on indoor location system. Scientific Reports 2025;15(1) View
  25. Efendioglu E, Cigiloglu A. An artificial intelligence perspective on geriatric syndromes: assessing the information accuracy and readability of ChatGPT. European Geriatric Medicine 2025;16(3):1063 View
  26. He R, Chiang J. Simultaneous forecasting of vital sign trajectories in the ICU. Scientific Reports 2025;15(1) View
  27. Tajirian T, Lo B, Strudwick G, Tasca A, Kendell E, Poynter B, Kumar S, Chang P, Kung C, Schachter D, Zai G, Kiang M, Hoppe T, Ling S, Haider U, Rabel K, Coombe N, Jankowicz D, Sockalingam S. Assessing the Impact on Electronic Health Record Burden After Five Years of Physician Engagement in a Canadian Mental Health Organization: Mixed-Methods Study. JMIR Human Factors 2025;12:e65656 View
  28. du Sartz de Vigneulles B, Lan R, Mick G, Dussart C, Carrouel F. Improving care pathways through evidence-based modeling strategies: a scoping review. Public Health 2025;244:105751 View
  29. Sokol K, Fackler J, Vogt J. Artificial intelligence should genuinely support clinical reasoning and decision making to bridge the translational gap. npj Digital Medicine 2025;8(1) View
  30. Pepito J, Acaso N, Merioles R, Ismael J. The Integration of Automation in Nursing Practice: Opportunities, Challenges, and Future Directions: Discursive Paper (Preprint). JMIR Nursing 2025 View
  31. Lee Y, Lee Y, Ha I. Predicting nonsurgical treatment outcomes in lumbar disc herniation: leveraging sparse electronic health records for patient phenotyping. International Journal of Medical Informatics 2025;204:106056 View
  32. Taheri Hosseinkhani N. Economic Evaluation of Artificial Intelligence Integration in Global Healthcare: Balancing Costs, Outcomes, and Investment Value. SSRN Electronic Journal 2025 View
  33. Trottet C, Schürch M, Allam A, Petelytska L, Castellví I, Bečvář R, de Vries-Bouwstra J, Iannone F, Carreira P, Truchetet M, Cuomo G, Rezus E, Cantatore F, Simeón-Aznar C, Parvu M, Dzhus M, Distler O, Hoffmann-Vold A, Krauthammer M, Bellando-Randone S, Walker U, Cutolo M, Rednic S, Allanore Y, Montecucco C, Novak S, Kumánovics G, Kotyla P, Zanatta E, Pirkmajer K, Moroncini G, Airó P, Radic M, Balbir-Gurman A, Hunzelmann N, Idolazzi L, Mitrovic J, Denton C, Vonk M, Colic J, Henes J, Foeldvari I, Bajocchi G, Santiago T, Stamenkovic B, De Santis M, Ickinger C, Ananieva L, Sondergaard K, Szucs G, Launay D, Riccieri V, Balanescu A, Gheorghiu A, Bergmann C, Mouthon L, Smith V, Mogensen M, Vanthuyne M, Alegre Sancho J, Granel B, de Souza Müller C, Agachi S, Cauli A, Solanki K, Soliman E, Rosato E, Foti R, Maurer B, Olesinska M, Awad N, Blaise S, Senet P, Chatelus E, Litinsky I, Del Galdo F, Kerzberg E, Milas-Ahic J, Limonta M, Marcoccia A, Martin T, Wojteczek A, Riemekasten G, Conceição Santos L, Levy Y, de Araujo D, Brzosko M, Epis O, Sfikakis P, Ramazan A, Lescoat A, Cerinic M, Spierings J, Atzeni F, Kuwana M, Mekinian A, Martin M, Boleto G, Del Papa N, Selvi E, Mosca M, Gerth U, Karadag D, Batalov A, Ginosyan K, Manukyan N, Naffaa M, Maglio C, Retuerto M, Iwata F, Hinchcliff M, Giacomelli R, Benvenuti F, Santos Carneiro H, Rabaneda E, Györfi A, Lopez Nunez L, De Angelis R, Carrión-Barberà I, Brigante A, Miedany Y, Mu R, Daniel A, de Paulis A, Derk C, Zhang L, Batko B, Sole I, Lewandowska-Polak A, Yan Q, Duruöz T, Colak S, Guzmán J, Mora-Trujillo C, Chimenti M, El-Bakry S, Alibaz-Oner F. Deep hierarchical subtyping of multi-organ systemic sclerosis trajectories - a EUSTAR study. npj Digital Medicine 2025;8(1) View
  34. Alrashed F, Ahmad T, Alsabih A, Mahmoud S, Almurdi M, Abdulghani H. Exploring Medical Doctors’ Confidence in Artificial Intelligence: The Role of Specialty, Experience, and Perceived Job Security. Healthcare 2025;13(18):2377 View
  35. Georgiou G. Transforming Speech-Language Pathology with AI: Opportunities, Challenges, and Ethical Guidelines. Healthcare 2025;13(19):2460 View
  36. Pham M, Mai T, Crane M, Brennan R, Ward M, Geary U, Byrne D, O’Connell B, Bergin C, Creagh D, McDonald N, Bezbradica M. Explainable AI for infection prevention and control: modeling CPE acquisition and patient outcomes in an Irish hospital with transformers. BMC Medical Informatics and Decision Making 2025;25(1) View
  37. Zyryanov S, Parshenkov M, Yavorskiy A. Clinical trial digitalization: new opportunities for the use of artificial intelligence. Kachestvennaya Klinicheskaya Praktika = Good Clinical Practice 2025;(3):62 View
  38. Boudreault J, Lamothe F, Campagna C, Chebana F. Machine learning for modelling the health impacts of extreme heat: A comprehensive literature review. Environment International 2025;206:109965 View
  39. Pollington F, Denaxas S, Li K, Thygesen J, Lyratzopoulos G, White B. Evaluation of trajectory analysis for disease risk assessment: a scoping review. Journal of the American Medical Informatics Association 2025 View

Books/Policy Documents

  1. D’hondt R, Moylett S, Goris A, Vens C. Artificial Intelligence in Medicine. View
  2. Shukla D, Tripathi R. Tracking Tourism Patterns and Improving Travel Experiences With Innovative Technologies. View
  3. Ben Khizzou N, Aarabe M, Bouizgar M, Alla L, Benjelloun A. AI Innovations for Customer Experience Optimization in the Service Sector. View
  4. Alqaidoom M, Ateeq A. Tech Fusion in Business and Society. View
  5. van der Linden R, Amarti K, Ciharova M, Kleiboer A, Riper H, Lisowska A, Hoogendoorn M. Artificial Intelligence in Medicine. View
  6. Kumar A, Singh D. Artificial Intelligence in Modern Healthcare System. View
  7. Provost S, Freitas A. Artificial Intelligence XLII. View

Conference Proceedings

  1. Li M, Zhang X, Ying H, Li Y, Han X, Yu D. 2023 IEEE International Conference on Data Mining (ICDM). Data Quality Aware Hierarchical Federated Reinforcement Learning Framework for Dynamic Treatment Regimes View
  2. Krieg S, Chawla N, Feldman K. 2024 IEEE 12th International Conference on Healthcare Informatics (ICHI). Representing Outcome-Driven Higher-Order Dependencies in Graphs of Disease Trajectories View
  3. Provost S, Freitas A. 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Auto-Sklong: A New AutoML System for Longitudinal Classification View
  4. Fathy G, Soliman A, Etminani F, Ohlsson M. 2025 IEEE Conference on Artificial Intelligence (CAI). Leveraging Temporal Aggregation and Graph Structures to Analyze EHR Trajectories View
  5. Zhang W, Peng H, Liao Z. 2025 International Joint Conference on Neural Networks (IJCNN). CMSPA-Former: Causal Multi-Scale Pyramid Attention Former for Estimating Counterfactual Outcomes View