ArticleCanadian family physician Medecin de famille canadien2024
Artificial intelligence for family medicine research in Canada: current state and future directions: Report of the CFPC AI Working Group.
Article in Canadian family physician Medecin de famille canadien, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 16 citations in OpenAlex.
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- AIFM-ed Curriculum Framework for Postgraduate Family Medicine Education on Artificial Intelligence: Mixed Methods Study.JMIR medical education · 2025Article
- Use of AI in Family Medicine Publications: A Joint Editorial From Journal Editors.Annals of family medicine · 2025Article
- Use of AI in family medicine publications: a joint editorial from journal editors.Family medicine and community health · 2025Article
- Use of artificial intelligence in family medicine publications: Joint statement from journal editors.Canadian family physician Medecin de famille canadien · 2025Article
- Use of AI in Family Medicine Publications: A Joint Editorial From Journal Editors.Family medicine · 2025Article
- Use of AI in Family Medicine Publications: A Joint Editorial From Journal Editors.PRiMER (Leawood, Kan.) · 2025Article
- Strength in family medicine research: New CFPC efforts identify opportunities and set priorities.Canadian family physician Medecin de famille canadien · 2024Article
- Future-proofing family medicine.Canadian family physician Medecin de famille canadien · 2024Article
- Could artificial intelligence improve patient care and physician workload?Canadian family physician Medecin de famille canadien · 2024Article
- Artificial Intelligence in Medicine: A Specialty-Level Overview of Emerging AI Trends.JSLS : Journal of the Society of Laparoendoscopic SurgeonsReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo understand the current landscape of artificial intelligence (AI) for family medicine (FM) research in Canada, identify how the College of Family Physicians of Canada (CFPC) could support near-term positive progress in this field, and strengthen the community working in this field. COMPOSITION OF THE COMMITTEE: Members of a scientific planning committee provided guidance alongside members of a CFPC staff advisory committee, led by the CFPC-AMS TechForward Fellow and including CFPC, FM, and AI leaders.
methodsThis initiative included 2 projects. First, an environmental scan of published and gray literature on AI for FM produced between 2018 and 2022 was completed. Second, an invitational round table held in April 2022 brought together AI and FM experts and leaders to discuss priorities and to create a strategy for the future. REPORT: The environmental scan identified research related to 5 major domains of application in FM (preventive care and risk profiling, physician decision support, operational efficiencies, patient self-management, and population health). Although there had been little testing or evaluation of AI-based tools in practice settings, progress since previous reviews has been made in engaging stakeholders to identify key considerations about AI for FM and opportunities in the field. The round-table discussions further emphasized barriers to and facilitators of high-quality research; they also indicated that while there is immense potential for AI to benefit FM practice, the current research trajectory needs to change, and greater support is needed to achieve these expected benefits and to avoid harm.
conclusionTen candidate action items that the CFPC could adopt to support near-term positive progress in the field were identified, some of which an AI working group has begun pursuing. Candidate action items are roughly divided into avenues where the CFPC is well-suited to take a leadership role in tackling priority issues in AI for FM research and specific activities or initiatives the CFPC could complete. Strong FM leadership is needed to advance AI research that will contribute to positive transformation in FM.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.