AI for Medicine

Learn to evaluate and apply AI in healthcare settings with privacy, evidence and human oversight. Fictional hospital cases and practical tools for doctors and healthcare professionals. The model suggests. The clinician decides.

Developed under the new AI Act model · Continuous updates

IntellCore campus app, available on iOS and Android

Edition 2026

200 hours of applied learning

8 academic credits

25 lessons + 6 workshops

Digital campus

Verifiable certificate

550 USD one payment · or 2 × 275 USD (today and after 30 days)

Enroll here

What you'll learn

Distinguish prediction, classification and generative AI from a clinical decision, and define acceptable uses.
Design a health-data flow with minimisation, a legal basis, access control and an impact assessment.
Interpret sensitivity, specificity, predictive values, bias and external validation without confusing performance with clinical utility.
Review AI-generated documentation and communication, detect hallucinations and verify every claim against its source.
Relate intended purpose, the AI Act and the MDR to consent, liability and effective human oversight.
Defend a fictional clinical pilot with evidence, indicators, stopping criteria and a final dossier.
Apply the IntellCore AI Act Method™: classify the risk of an AI use case in your field and document it under the AI Act 2026.

Program curriculum

01 — What AI in medicine is and is not

AI, machine learning and generative models
From expert systems to today's AI
Intended purpose and limits of the clinical case
Automation bias and human oversight
Benefit, risk and criteria for not using AI
Workshop · Purpose and limits sheet for two fictional uses: documentation drafting and image-review support; responsibility matrix and criteria for not using AI.

02 — Clinical data, health records and privacy

Health records: provenance and quality
GDPR and special categories of data
Minimisation, pseudonymisation and anonymisation
Access, vendors and impact assessment
Workshop · Synthetic data map, access matrix and draft impact assessment with purposes, retention, vendors and risks.

03 — Assisted diagnosis and medical imaging

Sensitivity, specificity and the confusion matrix
Prevalence, thresholds and predictive values
Bias, reference standard and external validation
Medical imaging and distribution shift
Workshop · Validation report with a synthetic confusion matrix, metrics, subgroups, limits and a reasoned decision to continue or stop the evaluation.

04 — Generative AI in practice

Clinical documentation: a draft, never an automatic record
Reports and source traceability
Patient communication and accessibility
Hallucinations, verification and malicious instructions
Workshop · Synthetic documentation draft with a source-claim table, log of omissions and hallucinations, corrected version and review protocol.

05 — Regulation and liability

AI Act: classification and high-risk systems
MDR and software as a medical device
Consent, information and liability
The professional decides and signs: control and incidents
Workshop · Preliminary regulatory matrix, information and oversight flow, and list of evidence pending legal and regulatory validation.

06 — Implementing AI in a clinical service

Evaluation before the pilot
Scoped pilot, training and stopping criteria
Monitoring, costs and change management
Final dossier and defence before the committee
Workshop · Final Valdemora dossier and ten-minute defence: evidence, limits, owners, residual risks and a reasoned decision to pilot or not implement.

07 — IntellCore AI Act Method™ applied to your field

The EU AI Act 2026: risk levels, prohibited practices and obligations
Transparency, human oversight and documentation in your professional field
Classifying and auditing a real AI use case step by step
Your compliance file: certified with the IntellCore AI Act Method™

Practical application

· Purpose and limits sheet for two fictional uses: documentation drafting and image-review support; responsibility matrix and criteria for not using AI.
· Synthetic data map, access matrix and draft impact assessment with purposes, retention, vendors and risks.
· Validation report with a synthetic confusion matrix, metrics, subgroups, limits and a reasoned decision to continue or stop the evaluation.
· Synthetic documentation draft with a source-claim table, log of omissions and hallucinations, corrected version and review protocol.
· Preliminary regulatory matrix, information and oversight flow, and list of evidence pending legal and regulatory validation.
· Final Valdemora dossier and ten-minute defence: evidence, limits, owners, residual risks and a reasoned decision to pilot or not implement.

Practical project: Implementation dossier for Valdemora District Hospital: intended purpose, data map, validation evidence, regulatory review, human oversight and a pilot with stopping criteria.

Who is this for?

· Physicians
· Medical residents
· Nursing
· Dentistry
· Physiotherapy
· Pharmacy
· Clinical psychology
· Healthcare managers

Requirements

· No technical knowledge or programming required.
· Basic use of documents and spreadsheets.
· Work exclusively with the fictional case and synthetic data; never enter real patient data.

Edition 2026

What each week includes

Every week of the program follows the same structure.

01
Explainer video per lesson
02
Guided reading (6 h)
03
IntellCore Labs · ~90 min workshop with data
04
Verified real case
05
IntellCore Podcast
06
IntellCore Radar
07
Self-assessment
08
Practice and exam (70%, 3 attempts)
09
Extended practice (5 h)
10
IntellCore AI Act Method™ module applied to your field (30 h)
11
Applied final project (30 h)
12
6 modules × 23 h + IntellCore AI Act Method™ module 30 h + final assessment 2 h + final project 30 h = 200 h
13
Downloadable PDF summary