Who this is for
- Physicians, residents, clinical researchers, and medical students
- Pharma and medtech teams supporting medical education
- Hospitals, congresses, institutes, and biomedical research groups
Responsible AI Education · Clinical AI Literacy · Agentic AI in Medicine
Education & seminars for physicians and biomedical teams
Practical AI education for physicians, clinical researchers, and pharma partners: responsible AI, XAI, LLMs, agentic AI, low-data models, and clinical validation.
Positioning
Preparing clinicians for the agentic AI era
Clear, physician-centered AI education: what works, what fails, what evidence to trust, and how AI can support - not replace - clinical judgment.
Core promise
Machine learning translated into clinical language: validation, bias, leakage, explainability, LLM risks, workflow use, and responsible adoption.
Flagship workshop
AI in Biomedicine: From Data to Clinical Guidelines
A four-hour workshop on biomedical AI: FAIR data, XAI, multimodal models, LLMs, and translation from models to clinical guidelines.
- Session 1: From Excel to FAIR: Building the Foundations.
- Session 2: Our World Is Not Linear: Explainable AI in Clinical Practice.
- Session 3: Beyond Tables: Imaging, Language Models & Multimodal AI.
- Session 4: From AI Models to Guidelines and Education.
First scheduled version: Saturday, 27 June 2026, 10:00-14:00, as part of the IMBE conference “Molecular Medicine from the Laboratory to Practice: Challenges and Questions X” in Athens.
Seminar modules
Responsible AI in clinical practice
Validation, bias, leakage, calibration, uncertainty, and human-in-the-loop use.
From Excel to FAIR data
From spreadsheets to reproducible biomedical datasets.
XAI for diagnostics, prognosis & biomarkers
Nonlinearity, interpretation, feature selection, biomarker discovery, and potential drug-target identification.
LLMs and agentic AI
Prompting, RAG, hallucinations, governance, and realistic clinical workflows.
Multimodal AI
Clinical data, imaging, omics, biomarkers, text, and real-world evidence.
Regulatory-facing AI literacy
FDA AI/ML SaMD concepts, GMLP, transparency, lifecycle risk, and what physicians should ask.
Democratizing low-data AI
ZACH-ViT, hZACH-ViT, and s-DNNs as compact, train-from-scratch alternatives.
Biometrics as a case study
ECG authentication, robustness, privacy, adversarial risk, and validation in high-stakes AI.
Possible formats
60-90 minute keynote
High-level responsible AI orientation for congresses, hospital groups, and pharma-supported medical education.
Half-day workshop
Structured educational workshop with practical examples, discussion, and discipline-specific case studies.
Full-day training
Deeper clinical AI literacy programme including hands-on interpretation of AI papers, model outputs, and common pitfalls.
Custom pharma/clinical programme
Tailored seminar series for collaborating physicians, advisory boards, or medical affairs education initiatives.
Use this form for physician education, pharma-supported medical education, congress workshops, invited talks, or tailored responsible AI programmes.
Request an AI seminar or workshop
Use this form for physician education, pharma-supported medical education, congress workshops, invited talks, or tailored responsible AI programmes.
Available in English and Greek - online, onsite, or hybrid.
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Contact
Bring responsible AI education to your medical audience
For pharmaceutical, hospital, congress, or research-group seminars, contact me to adapt the format, duration, clinical domain, and learning objectives.