cirpublications.com-T89Q-1790899041-n552358828 1790899041 Clinical Intelligence Research Press info@cirpublications.com Clinical Intelligence Research Press Journal of Health Informatics and Digital Systems J. Health Inform. Digit. Syst. 3149-8973 2022 2 2 Hiroshi Nakamura Yuta Kato 2022 10.68159/n552358828 https://cirpublications.com/pub/journal/2/article/n552358828 Chen H, Gao C. Explainable medical imaging AI needs human-centered design: guidelines and evidence from a systematic review. npj Digit Med. 2022;5(1):156. 10.1038/s41746-022-00699-2 Soenksen LR, Ma Y, Zeng C, Boussioux L, Villalobos Carballo K, Na L, et al. Integrated multimodal artificial intelligence framework for healthcare applications. npj Digit Med. 2022;5(1):149. 10.1038/s41746-022-00689-4 Bajwa J, Munir U, Nori A, Williams B. Artificial intelligence in healthcare: transforming the practice of medicine. Future Healthc J. 2021;8(2):e188-e194. 10.7861/fhj.2021-0095 Shah P, Kendall F, Khozin S, Goosen R, Hu J, Laramie J, et al. Artificial intelligence and machine learning in clinical development: a translational perspective. npj Digit Med. 2019;2(1):69. 10.1038/s41746-019-0148-3 Acosta JN, Falcone GJ, Rajpurkar P, Topol EJ. Multimodal biomedical AI. Nat Med. 2022;28(9):1773-84. 10.1038/s41591-022-01981-2 Zhang J, Budhdeo S, William W, Cerrato P, Shuaib H, Sood H, et al. Moving towards vertically integrated artificial intelligence development. npj Digit Med. 2022;5(1):143. 10.1038/s41746-022-00690-x Xu Y, Liu X, Cao X, Huang C, Liu E, Qian S, et al. Artificial intelligence: A powerful paradigm for scientific research. Innovation (Camb). 2021;2(4):100179. 10.1016/j.xinn.2021.100179 Shamout FE, Shen Y, Wu N, Kaku A, Park J, Makino T, et al. An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. npj Digit Med. 2021;4(1):80. 10.1038/s41746-021-00453-0 Zhang K, Liu X, Shen J, Li Z, Sang Y, Wu X, et al. Clinically applicable AI system for accurate diagnosis, quantitative measurements, and prognosis of COVID-19 pneumonia using computed tomography. Cell. 2020;181(6):1423-33. 10.1016/j.cell.2020.04.045 Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019;6(2):94-8. 10.7861/futurehosp.6-2-94 Ciecierski-Holmes T, Singh R, Axt M, Brenner S, Barteit S. Artificial intelligence for strengthening healthcare systems in low- and middle-income countries: a systematic scoping review. npj Digit Med. 2022;5(1):162. 10.1038/s41746-022-00700-y Panch T, Mattie H, Celi LA. The “inconvenient truth” about AI in healthcare. npj Digit Med. 2019;2(1):77. 10.1038/s41746-019-0155-4 Ayala Solares JR, Raimondi FED, Zhu Y, Rahimian F, Canoy D, Tran J, et al. Deep learning for electronic health records: A comparative review of multiple deep neural architectures. J Biomed Inform. 2020;101:103337. 10.1016/j.jbi.2019.103337 Martinez-Millana A, Saez-Saez A, Tornero-Costa R, Azzopardi-Muscat N, Traver V, Novillo-Ortiz D. Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews. Int J Med Inform. 2022;166:104855. 10.1016/j.ijmedinf.2022.104855 Coiera E, Liu S. Evidence synthesis, digital scribes, and translational challenges for artificial intelligence in healthcare. Cell Rep Med. 2022;3(12):100860. 10.1016/j.xcrm.2022.100860 London AJ. Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care? Cell Rep Med. 2022;3(5):100622. 10.1016/j.xcrm.2022.100622 Fennelly O, Cunningham C, Grogan L, Cronin H, O’Shea C, Roche M, et al. Successfully implementing a national electronic health record: a rapid umbrella review. Int J Med Inform. 2020;144:104281. 10.1016/j.ijmedinf.2020.104281 Cutillo CM, Sharma KR, Foschini L, Kundu S, Mackintosh M, Mandl KD, et al. Machine intelligence in healthcare—perspectives on trustworthiness, explainability, usability, and transparency. npj Digit Med. 2020;3:47. 10.1038/s41746-020-0254-2 Chu J, Arkorful VE, Zhao S. Electronic health records adoption: Do institutional pressures and organizational culture matter? Technol Soc. 2021;65:101571. 10.1016/j.techsoc.2021.101571 Rieke N, Hancox J, Li W, Milletari F, Roth HR, Albarqouni S, et al. The future of digital health with federated learning. npj Digit Med. 2020;3(1):119. 10.1038/s41746-020-00323-1 Marwaha JS, Landman AB, Brat GA, Dunn T, Gordon WJ. Deploying digital health tools within large, complex health systems: key considerations for adoption and implementation. npj Digit Med. 2022;5(1):13. 10.1038/s41746-022-00557-1 Dunn P, Hazzard E. Technology approaches to digital health literacy. Int J Cardiol. 2019;293:294-6. 10.1016/j.ijcard.2019.06.039 Chada BV, Summers L. AI in the NHS: a framework for adoption. Future Healthc J. 2022;9(3):313-6. 10.7861/fhj.2021-0134 Feng J, Phillips RV, Malenica I, Bishara A, Hubbard AE, Celi LA, et al. Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare. npj Digit Med. 2022;5(1):66. 10.1038/s41746-022-00611-y Zhang J, Budhdeo S, Ashrafian H, Lane T, Cowling TE, Thomas C, et al. Addressing the “elephant in the room” of AI clinical decision support through organisation-level regulation. PLoS Digit Health. 2022;1(7):e0000111. 10.1371/journal.pdig.0000111 Fontes C, Hohmann E. AI-powered public surveillance systems: why we (might) need them and how we want them. Technol Soc. 2022;71:102110. 10.1016/j.techsoc.2022.102110 Siala H, Wang Y. SHIFTing artificial intelligence to be responsible in healthcare: A systematic review. Soc Sci Med. 2022;296:114782. 10.1016/j.socscimed.2022.114782