Computerization of the Work of General Practitioners: Mixed Methods Survey of Final-Year Medical Students in Ireland.
Charlotte BleaseAnna KharkoMichael H BernsteinColin P BradleyMuiris HoustonIan WalshKenneth D MandlPublished in: JMIR medical education (2023)
We caution that without a firm curricular foundation on advances in AI/ML, students may rely on extreme perspectives involving self-preserving optimism biases that demote the impact of advances in technology on primary care on the one hand and technohype on the other. Ultimately, these biases may lead to negative consequences in health care. Improvements in medical education could help prepare tomorrow's doctors to optimize and lead the ethical and evidence-based implementation of AI/ML-enabled tools in medicine for enhancing the care of tomorrow's patients.
Keyphrases
- healthcare
- primary care
- medical students
- medical education
- end stage renal disease
- artificial intelligence
- ejection fraction
- chronic kidney disease
- newly diagnosed
- quality improvement
- prognostic factors
- palliative care
- climate change
- study protocol
- machine learning
- clinical trial
- decision making
- general practice
- health information