Published on in Vol 23, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26646, first published .
Future Medical Artificial Intelligence Application Requirements and Expectations of Physicians in German University Hospitals: Web-Based Survey

Future Medical Artificial Intelligence Application Requirements and Expectations of Physicians in German University Hospitals: Web-Based Survey

Future Medical Artificial Intelligence Application Requirements and Expectations of Physicians in German University Hospitals: Web-Based Survey

Journals

  1. Haleem A, Javaid M, Singh R, Suman R. Applications of Artificial Intelligence (AI) for cardiology during COVID-19 pandemic. Sustainable Operations and Computers 2021;2:71 View
  2. Ji M, Chen X, Genchev G, Wei M, Yu G. Status of AI-Enabled Clinical Decision Support Systems Implementations in China. Methods of Information in Medicine 2021;60(05/06):123 View
  3. Feduniw S, Golik D, Kajdy A, Pruc M, Modzelewski J, Sys D, Kwiatkowski S, Makomaska-Szaroszyk E, Rabijewski M. Application of Artificial Intelligence in Screening for Adverse Perinatal Outcomes—A Systematic Review. Healthcare 2022;10(11):2164 View
  4. Weichert J, Welp A, Scharf J, Dracopoulos C, Becker W, Gembicki M. The Use of Artificial Intelligence in Automation in the Fields of Gynaecology and Obstetrics – an Assessment of the State of Play. Geburtshilfe und Frauenheilkunde 2021;81(11):1203 View
  5. Monteith S, Glenn T, Geddes J, Whybrow P, Achtyes E, Bauer M. Expectations for Artificial Intelligence (AI) in Psychiatry. Current Psychiatry Reports 2022;24(11):709 View
  6. Mayta-Tovalino F, Munive-Degregori A, Luza S, Cárdenas-Mariño F, Guerrero M, Barja-Ore J. Applications and perspectives of artificial intelligence, machine learning and “dentronics” in dentistry: A literature review. Journal of International Society of Preventive and Community Dentistry 2023;13(1):1 View
  7. Kamradt M, Poß-Doering R, Szecsenyi J. Exploring Physician Perspectives on Using Real-world Care Data for the Development of Artificial Intelligence–Based Technologies in Health Care: Qualitative Study. JMIR Formative Research 2022;6(5):e35367 View
  8. Miró Catalina Q, Fuster-Casanovas A, Solé-Casals J, Vidal-Alaball J. Developing an Artificial Intelligence Model for Reading Chest X-rays: Protocol for a Prospective Validation Study. JMIR Research Protocols 2022;11(11):e39536 View
  9. van der Meijden S, de Hond A, Thoral P, Steyerberg E, Kant I, Cinà G, Arbous M. Intensive Care Unit Physicians’ Perspectives on Artificial Intelligence–Based Clinical Decision Support Tools: Preimplementation Survey Study. JMIR Human Factors 2023;10:e39114 View
  10. van der Zander Q, van der Ende - van Loon M, Janssen J, Winkens B, van der Sommen F, Masclee A, Schoon E. Artificial intelligence in (gastrointestinal) healthcare: patients’ and physicians’ perspectives. Scientific Reports 2022;12(1) View
  11. Fritsch S, Blankenheim A, Wahl A, Hetfeld P, Maassen O, Deffge S, Kunze J, Rossaint R, Riedel M, Marx G, Bickenbach J. Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients. DIGITAL HEALTH 2022;8:205520762211167 View
  12. Henckert D, Malorgio A, Schweiger G, Raimann F, Piekarski F, Zacharowski K, Hottenrott S, Meybohm P, Tscholl D, Spahn D, Roche T. Attitudes of Anesthesiologists toward Artificial Intelligence in Anesthesia: A Multicenter, Mixed Qualitative–Quantitative Study. Journal of Clinical Medicine 2023;12(6):2096 View
  13. Amann J, Vayena E, Ormond K, Frey D, Madai V, Blasimme A, Canzan F. Expectations and attitudes towards medical artificial intelligence: A qualitative study in the field of stroke. PLOS ONE 2023;18(1):e0279088 View
  14. Teng M, Singla R, Yau O, Lamoureux D, Gupta A, Hu Z, Hu R, Aissiou A, Eaton S, Hamm C, Hu S, Kelly D, MacMillan K, Malik S, Mazzoli V, Teng Y, Laricheva M, Jarus T, Field T. Health Care Students’ Perspectives on Artificial Intelligence: Countrywide Survey in Canada. JMIR Medical Education 2022;8(1):e33390 View
  15. Wenderott K, Gambashidze N, Weigl M. Integration of Artificial Intelligence Into Sociotechnical Work Systems—Effects of Artificial Intelligence Solutions in Medical Imaging on Clinical Efficiency: Protocol for a Systematic Literature Review. JMIR Research Protocols 2022;11(12):e40485 View
  16. Nawaz F, Barr A, Desai M, Tsagkaris C, Singh R, Klager E, Eibensteiner F, Parvanov E, Hribersek M, Kletecka-Pulker M, Willschke H, Atanasov A. Promoting Research, Awareness, and Discussion on AI in Medicine Using #MedTwitterAI: A Longitudinal Twitter Hashtag Analysis. Frontiers in Public Health 2022;10 View
  17. Matthiesen S, Diederichsen S, Hansen M, Villumsen C, Lassen M, Jacobsen P, Risum N, Winkel B, Philbert B, Svendsen J, Andersen T. Clinician Preimplementation Perspectives of a Decision-Support Tool for the Prediction of Cardiac Arrhythmia Based on Machine Learning: Near-Live Feasibility and Qualitative Study. JMIR Human Factors 2021;8(4):e26964 View
  18. Al-Medfa M, Al-Ansari A, Darwish A, Qreeballa T, Jahrami H. Physicians’ attitudes and knowledge toward artificial intelligence in medicine: Benefits and drawbacks. Heliyon 2023;9(4):e14744 View
  19. Hofer B, Kittler M, Laukens K. How deep learning influences workflows and roles in virtual surgical planning. Discover Health Systems 2023;2(1) View
  20. Chen Y, Wu Z, Wang P, Xie L, Yan M, Jiang M, Yang Z, Zheng J, Zhang J, Zhu J. Radiology Residents’ Perceptions of Artificial Intelligence: Nationwide Cross-Sectional Survey Study. Journal of Medical Internet Research 2023;25:e48249 View
  21. Ghayda R, Cannarella R, Calogero A, Shah R, Rambhatla A, Zohdy W, Kavoussi P, Avidor-Reiss T, Boitrelle F, Mostafa T, Saleh R, Toprak T, Birowo P, Salvio G, Calik G, Kuroda S, Kaiyal R, Ziouziou I, Crafa A, Phuoc N, Russo G, Durairajanayagam D, Al-Hashimi M, Hamoda T, Pinggera G, Adriansjah R, Maldonado Rosas I, Arafa M, Chung E, Atmoko W, Rocco L, Lin H, Huyghe E, Kothari P, Solorzano Vazquez J, Dimitriadis F, Garrido N, Homa S, Falcone M, Sabbaghian M, Kandil H, Ko E, Martinez M, Nguyen Q, Harraz A, Serefoglu E, Karthikeyan V, Tien D, Jindal S, Micic S, Bellavia M, Alali H, Gherabi N, Lewis S, Park H, Simopoulou M, Sallam H, Ramirez L, Colpi G, Agarwal A. Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics. The World Journal of Men's Health 2024;42(1):39 View
  22. Polzin R, Fritsch S, Sharafutdinov K, Marx G, Schuppert A. Diagnostic Expert Advisor: A platform for developing machine learning models on medical time-series data. SoftwareX 2023;23:101517 View
  23. 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
  24. Wac M, Craddock I, Chantziara S, Campbell T, Santos-Rodriguez R, Davidson B, McWilliams C. Design and Evaluation of an Intensive Care Unit Dashboard Built in Response to the COVID-19 Pandemic: Semistructured Interview Study. JMIR Human Factors 2023;10:e49438 View
  25. Gül M, Russo G, Kandil H, Boitrelle F, Saleh R, Chung E, Kavoussi P, Mostafa T, Shah R, Agarwal A. Male Infertility: New Developments, Current Challenges, and Future Directions. The World Journal of Men's Health 2024;42(3):502 View
  26. Göndöcs D, Dörfler V. AI in medical diagnosis: AI prediction & human judgment. Artificial Intelligence in Medicine 2024;149:102769 View
  27. Hudecek M, Lermer E, Gaube S, Cecil J, Heiss S, Batz F. Fine for others but not for me: The role of perspective in patients’ perception of artificial intelligence in online medical platforms. Computers in Human Behavior: Artificial Humans 2024;2(1):100046 View
  28. Evans R, Bryant L, Russell G, Absolom K. Trust and acceptability of data-driven clinical recommendations in everyday practice: A scoping review. International Journal of Medical Informatics 2024;183:105342 View
  29. Hu Z, Wang M, Zheng S, Xu X, Zhang Z, Ge Q, Li J, Yao Y. Clinical Decision Support Requirements for Ventricular Tachycardia Diagnosis: A Survey within the Framework of Knowledge and Practice (Preprint). JMIR Human Factors 2023 View
  30. Wu H, Jin K, Yip C, Koh V, Ye J. A systematic review of economic evaluation of artificial intelligence-based screening for eye diseases: From possibility to reality. Survey of Ophthalmology 2024;69(4):499 View
  31. Yao Y, Wang H, Zhang Q, Teng H, Qi H, Zhang Q, Chaudhary P. Learning curves for itinerant nurses to master the operation skill of Ti-robot-assisted spinal surgery equipment by CUSUM analysis: A pilot study. PLOS ONE 2024;19(3):e0291147 View
  32. Artsi Y, Sorin V, Konen E, Glicksberg B, Nadkarni G, Klang E. Large language models for generating medical examinations: systematic review. BMC Medical Education 2024;24(1) View
  33. Giavina-Bianchi M, Amaro Jr E, Machado B. Medical Expectations of Physicians on AI Solutions in Daily Practice: Cross-Sectional Survey Study. JMIRx Med 2024;5:e50803 View
  34. Esmaeilzadeh P. Challenges and strategies for wide-scale artificial intelligence (AI) deployment in healthcare practices: A perspective for healthcare organizations. Artificial Intelligence in Medicine 2024;151:102861 View
  35. Alkhatieb M, Subke A. Artificial Intelligence in Healthcare: A Study of Physician Attitudes and Perceptions in Jeddah, Saudi Arabia. Cureus 2024 View
  36. Aljamaan F, Malki K, Alhasan K, Jamal A, Altamimi I, Khayat A, Alhaboob A, Abdulmajeed N, Alshahrani F, Saad K, Al-Eyadhy A, Al-Tawfiq J, Temsah M. ChatGPT-3.5 System Usability Scale early assessment among Healthcare Workers: Horizons of adoption in medical practice. Heliyon 2024;10(7):e28962 View
  37. Daniyal M, Qureshi M, Marzo R, Aljuaid M, Shahid D. Exploring clinical specialists’ perspectives on the future role of AI: evaluating replacement perceptions, benefits, and drawbacks. BMC Health Services Research 2024;24(1) View
  38. Mahmoudi H, Moradi M. The Progress and Future of Artificial Intelligence in Nursing Care: A Review. The Open Public Health Journal 2024;17(1) View
  39. 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
  40. Wichmann J, Gesk T, Leyer M. Acceptance of AI in Health Care for Short- and Long-Term Treatments: Pilot Development Study of an Integrated Theoretical Model. JMIR Formative Research 2024;8:e48600 View
  41. Desolda G, Dimauro G, Esposito A, Lanzilotti R, Matera M, Zancanaro M. A Human–AI interaction paradigm and its application to rhinocytology. Artificial Intelligence in Medicine 2024;155:102933 View
  42. Esfandiari E, Kalroozi F, Mehrabi N, Hosseini Y. Knowledge and acceptance of artificial intelligence and its applications among the physicians working in military medical centers affiliated with Aja University: A cross-sectional study. Journal of Education and Health Promotion 2024;13(1) View
  43. Banerjee A, Sarangi P, Kumar S. Medical Doctors’ Perceptions of Artificial Intelligence (AI) in Healthcare. Cureus 2024 View
  44. Purohit R, Saineni S, Chalise S, Mathai R, Sambandam R, Medina-Perez R, Bhanusali N. Artificial intelligence in rheumatology: perspectives and insights from a nationwide survey of U.S. rheumatology fellows. Rheumatology International 2024;44(12):3053 View
  45. Lundsten S, Jacobsson M, Rydén P, Mattsson L, Lindgren L, Schirle L. Using AI to Predict Patients’ Length of Stay: PACU Staff’s Needs and Expectations for Developing and Implementing an AI System. Journal of Nursing Management 2024;2024(1) View
  46. Boaro A, Mezzalira E, Siddi F, Bagattini C, Gabrovsky N, Marchesini N, Broekman M, Sala F, Ivanov M, Ringel F, Tessitore E, Sampron N, Boaro A, Staartjes V. Knowledge, interest and perspectives on Artificial Intelligence in Neurosurgery. A global survey. Brain and Spine 2024:104156 View

Books/Policy Documents

  1. Zohdy W, Agarwal A. Current and Future Advances in Male Infertility. View
  2. Singh B, Jermsittiparsert K, Lal S, Arora M. Physical Health, Mental Health, and Human Well-Being in the Age of AI. View
  3. Singh B. Physical Health, Mental Health, and Human Well-Being in the Age of AI. View