MedicalToxic education
I am CEO of MedicalToxic, a platform for clinicians and public audiences. I contribute toxicology articles, case studies and reference resources.[1]
Role: CEO and bylined contributor.
Read my articlesProjects & teaching
Turning knowledge into useful work.
Toxicology education, clinical AI research, and tools for documentation and training.
ToxLumen
The MedicalToxic team’s platform is designed to turn clinical case information into structured facts, reference-guided analysis and editable notes. It brings documentation and toxicology tools into a single case workflow.[2]
Role: MedicalToxic leadership.
Clinical effectiveness and patient-outcome benefit have not been established in the evidence reviewed for this site.
Explore ToxLumenToxLumen Simulation
A training module for poison-information specialists, new hires and exam candidates, with simulated consultations, practice questions and feedback.[2]
Role: A MedicalToxic team product.
Educational effectiveness has not been independently established in the evidence reviewed for this site.
View training informationPoisoning classification research
Collaborative studies of machine-learning and neural-network models using National Poison Data System records. They examine whether recorded clinical features can distinguish a defined set of poisoning exposures.[3]
Role: First author on the two featured studies.
Retrospective research in selected exposure categories; prospective clinical performance remains to be tested.
Explore the studiesSpeaking, teaching & communicationDifferent audiences.
Different audiences.
A shared subject.
Artificial Intelligence in Clinical Toxicology
PHA 6242 is a 3-credit course covering machine learning, deep learning, natural language processing, and the evaluation and validation of large language models in clinical toxicology. The 14-module curriculum connects AI methods with applications in the specialty.[4]
View the official UF course pageToxicology case studies
Bylined educational case discussions on MedicalToxic, connecting clinical presentation with toxicologic reasoning.[5]
Browse case studiesA conversation with ricin
A fictional interview that uses a conversational format to explain a toxic agent. An example of public-facing science communication.[6]
Read the explainerChildren and lead exposure
I discussed childhood lead exposure and blood testing in a Persian-language report published in 2019.[7]
View the Persian reportThe role of AI in medical toxicology
A Medical Toxicology podcast episode shared through my professional profile, discussing potential applications of AI in the field.[8]
View the episode announcementConference contributions
AI in pharmacology
Coauthored conference paper with Jafar Abdollahi · 2024 International Symposium on Telecommunications · IEEE.[9]
Machine learning for coronary artery disease prediction
Coauthored conference paper with Jafar Abdollahi · QICAR 2024 · IEEE.[9]
For organizers & educators
Discuss a speaking or teaching opportunity
Possible subjects include poisoning patterns, interpretation of clinical AI research, poison-information practice and communication of toxicology evidence. Share your audience, format and learning objectives.
Start a conversationReferences
- MedicalToxic · About and teamSource notes
- MedicalToxic · ToxLumen product pageSource notes
- Deep learning neural networks · 2023Source notes
- University of Florida · PHA 6242 Artificial Intelligence in Clinical ToxicologySource notes
- MedicalToxic · Omid Mehrpour author pageSource notes
- A Conversation with Ricin · MedicalToxicSource notes
- Persian public education · Childhood lead exposureSource notes
- Role of AI in medical toxicology · Part 1Source notes
- Conference contributions · IEEE 2024Source notes