Abstract
John W Coen, Stephen D McCarthy, Helen C Anderson
Abstract
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Artificial intelligence: a powerful paradigm for scientific research
10.1016/j.xinn.2021.100179 · 2021
Pushing the boundaries of scientific research with the use of artificial intelligence tools: navigating risks and unleashing possibilities
10.3126/nje.v13i1.53721 · 2023
Unresolved referenced work
Kept as external metadata until matched
Artificial intelligence in medicine: current trends and future possibilities
10.3399/bjgp18x695213 · 2018
Artificial intelligence in medicine: where are we now?
10.1016/j.acra.2019.10.001 · 2020
Unresolved referenced work
Kept as external metadata until matched
Effects of artificial intelligence implementation on efficiency in medical imaging-a systematic literature review and meta-analysis
10.1038/s41746-024-01248-9 · 2024
AI as a tool, not a replacement, in vascular medicine
10.1177/1358863x251399581 · 2026
Will AI replace physicians in the near future? AI adoption barriers in medicine
10.3390/diagnostics16030396 · 2026
Awareness, perceptions, and opinions of artificial intelligence among undergraduate medical students at Umm Al-Qura University, Saudi Arabia, in 2025: a cross-sectional study
10.7759/cureus.89741 · 2025
Smartphone applications for triaging adults with skin lesions that are suspicious for melanoma
10.1002/14651858.cd013192 · 2018
The use of smartphones by junior doctors
10.3402/meo.v20.28189 · 2015
Healthcare workers’ informal uses of mobile devices to support their work: a qualitative evidence synthesis
10.1002/14651858.cd015705 · 2023
Artificial intelligence in healthcare: a study of physician attitudes and perceptions in Jeddah, Saudi Arabia
10.7759/cureus.57256 · 2024
Unresolved referenced work
Kept as external metadata until matched
Artificial Intelligence for Patient Flow: Emerging Health Technologies
2024
Medical expectations of physicians on AI solutions in daily practice: cross-sectional survey study
10.2196/50803 · 2024
Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden
10.1186/s12913-022-08215-8 · 2022
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
The future is bright: artificial intelligence for trainee medical officers in Australia and New Zealand
10.1111/imj.16518 · 2024
First do no harm: legal principles regulating the future of artificial intelligence in health care in South Africa
10.17159/1727-3781/2022/v25ia11118 · 2022
Using artificial intelligence in patient care-some considerations for doctors and medical regulators
10.1007/s41649-024-00291-8 · 2024
Ten reasons why—the case for more and better AI regulation
10.1007/s43681-025-00865-8 · 2026
Impact of using an AI scribe on clinical documentation and clinician-patient interactions in allied health private practice: perspectives of clinicians and patients
10.1016/j.msksp.2025.103333 · 2025
Clinician experiences with ambient scribe technology to assist with documentation burden and efficiency
10.1001/jamanetworkopen.2024.60637 · 2025
Does artificial intelligence outperform natural intelligence in interpreting musculoskeletal radiological studies? A systematic review
10.1097/corr.0000000000001360 · 2020
Benefits and risks of AI in health care: narrative review
10.2196/53616 · 2024
Efficiency and quality of generative AI-assisted radiograph reporting
10.1001/jamanetworkopen.2025.13921 · 2025
Evaluation of artificial intelligence techniques in disease diagnosis and prediction
10.1007/s44163-023-00049-5 · 2023
COVID-DSNet: a novel deep convolutional neural network for detection of coronavirus (SARS-CoV-2) cases from CT and chest X-ray images
10.1016/j.artmed.2022.102427 · 2022
Comparative performance of artificial intelligence and radiologists in detecting lung nodules and breast lesions on CT and MRI: a systematic review
10.7759/cureus.95943 · 2025
Comparison between artificial intelligence solution and radiologist for the detection of pelvic, hip and extremity fractures on radiographs in adult using CT as standard of reference
10.1016/j.diii.2024.09.004 · 2025
A systematic review and meta-analysis of diagnostic performance comparison between generative AI and physicians
10.1038/s41746-025-01543-z · 2025
Implementation of AI in radiology: the perspective of referring physicians
10.1186/s13244-025-02120-4 · 2025
Health professionals' perspectives on the use of artificial intelligence in healthcare: a systematic review
10.1016/j.pec.2025.108680 · 2025
AI in diagnostic imaging: revolutionising accuracy and efficiency
10.1016/j.cmpbup.2024.100146 · 2024
The future of radiology: the path towards multimodal AI and superdiagnostics
10.1016/j.ejrai.2025.100014 · 2025
Medical student experiences and perceptions of ChatGPT and artificial intelligence: cross-sectional study
10.2196/51302 · 2023
Multinational attitudes toward AI in health care and diagnostics among hospital patients
10.1001/jamanetworkopen.2025.14452 · doi-reference
Patients' views on the use of artificial intelligence in healthcare: Artificial Intelligence Survey Aachen (AISA)-a prospective survey
10.1186/s13244-025-02159-3 · doi-reference
Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review
10.1016/s2589-7500(21)00132-1 · doi-reference
Physicians’ attitudes toward artificial intelligence in medicine: mixed methods survey and interview study
10.2196/74187 · doi-reference
Artificial intelligence in medical education: transforming learning and practice
10.7759/cureus.80852 · doi-reference
Medical students' attitudes toward AI in education: perception, effectiveness, and its credibility
10.1186/s12909-025-06704-y · doi-reference
Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study
10.1186/s12909-022-03896-5 · doi-reference
Western Australian medical students' attitudes towards artificial intelligence in healthcare
10.1371/journal.pone.0290642 · doi-reference