AI for Doctors / Practical / Every doctor

AI in Every doctor

Most doctors meet AI first as a chat assistant, an evidence-search tool or an ambient note-taker. Evidence-search tools and chatbots are in daily use but still make errors, so every answer needs a source check. Ambient scribes are spreading fast in US health systems and are just starting in India. Journals and the ICMR now set clear rules on disclosure and responsibility.

What AI does in everyday practice

Quick evidence lookup at the bedsideroutine

Ask a clinical question and get a short answer with linked papers and guidelines. Open the sources before acting.

Examples: OpenEvidence (US-verified clinicians), Consensus, Elicit

Language help for manuscriptsroutine

Fix grammar and clarity in your own writing. You must disclose it to the journal and you stay responsible for every word.

Examples: General chat assistants

Literature search and screening for a thesisearly adoption

Find papers, pull study details into a table and check whether later papers support or contradict a finding.

Examples: Elicit, Consensus, scite

Ambient clinical note draftingearly adoption

The tool turns the doctor-patient conversation into a structured note. Studies in US centres report less documentation time.

Examples: EkaScribe (Eka Care, India), Abridge

Patient information in plain languageearly adoption

Draft leaflets and consent explanations in simple Hindi, Marathi or English, then check them yourself.

Examples: General chat assistants

Teaching and exam practiceearly adoption

Generate practice questions and case vignettes. Verify every fact against a textbook.

Examples: General chat assistants

routine = in everyday use in many centres · early adoption = in use at some sites, evidence still building · research = studies only

Key ideas for this specialty

Large language model (LLM): A program that predicts the next word after reading huge amounts of text. It sounds fluent whether it is right or wrong, so you must check its facts.
Hallucination: When an AI states something false with confidence, such as a reference that does not exist. Always open the cited paper before you rely on it.
Retrieval-augmented answer: The tool first searches a library of papers, then writes an answer from what it found and links the sources. This is how evidence tools like OpenEvidence, Elicit and Consensus work, and it lowers (but does not remove) made-up facts.
Prompt: The instruction you type. Give the role, the patient or question details, the format you want, and ask it to say when it is unsure.
Ambient scribe: A tool that listens to the consultation and drafts the clinical note. You still read, correct and sign the note.
No-code machine learning: Point-and-click tools that train a simple prediction model from a spreadsheet without writing Python. Useful for learning, not for patient care without validation.

New to the basics? Start with the theory lessons.

Tools

Clinical question answers with citations from medical journals. Free for verified clinicians in the US; a search I ran found no sign that it verifies Indian doctors.

Regulatory status: Not listed

Elicitfreemium

Searches 138 million papers and extracts study details. The free tier has unlimited search and summaries; paid plans start at $49 a month.

Regulatory status: Not listed

Consensusfreemium

Answers research questions from peer-reviewed papers and shows study design.

Regulatory status: Not listed

scitepaid

Smart Citations show whether later papers support or contradict a finding. Offers a free trial.

Regulatory status: Not listed

EkaScribeNot listed

AI medical scribe from Eka Care built for Indian multilingual consultations, with ABDM-aligned design per press reports.

Regulatory status: Not listed

A listing here is not an endorsement. Ask any vendor for its CDSCO licence and class before clinical use.

Where to learn

Stanford Online (Coursera)coursefree auditbeginner

No coding needed. Covers clinical data, ML basics and how to judge an AI tool. Certificate is paid.

DeepLearning.AI (Coursera)coursefree auditintermediate

Hands-on diagnosis, prognosis and treatment models. Needs some Python.

Indian Council of Medical Researchguidelinefreebeginner

India's own rules for AI research, consent and ethics committee review (March 2023).

World Health Organizationguidelinefreeintermediate

Lists the risks of chatbots in care, education and research, with over 40 recommendations.

ICMJEguidelinefreebeginner

The disclosure rules most journals follow: AI cannot be an author, you disclose use, you own the content.

IIT Madras / SWAYAM Pluscoursefreebeginner

Indian, free to learn, no prior AI knowledge needed. Not medical; the certificate exam costs Rs 1000 per the press coverage.

Do it yourself

Check an AI answer against its sources

Pick a clinical question from your last duty. Ask Elicit or Consensus, then open every cited paper and mark each claim as supported, partly supported or not found. Keep the tally.

Open the dataset or tool →
Audit a reference list for fake citations

Ask a chat assistant for 10 references on a topic you know. Look up each on PubMed or Crossref and count how many exist and say what was claimed.

Open the dataset or tool →
Write your AI-use disclosure statement

Take a draft you are writing and note every step where AI helped. Write a short statement naming the tool, version and purpose, using the ICMJE page as the checklist.

Open the dataset or tool →

Use public or properly de-identified data only, and get ethics approval before any project on your own patients.

Papers worth reading

Societies and guidance

Ethical guidelines for AI in biomedical research and healthcare.

Guidance on large multi-modal models in health.

Rules for AI use and disclosure by authors.

Links checked 3 October 2026. “Not listed” means we could not confirm the detail, not that it is absent. Educational material, not clinical advice.