about🌵 is a space for my (@samrawal) clinical AI work --
My overall goals are to:
- Build Clinical AI software which
- Makes information deep within medical records more accessible: semantically filter, search, and extract clinical information from medical data like Electronic Medical Records
- Is generalizable: can be applied across a range of clinical tasks without significant task-specific training
- Develop packages, models, and tools that can be used as building blocks for further downstream clinical research and development
- MedQA: a a GPT-powered clinical reference tool that can answer clinical questions and follow-up questions in natural language, along with references to sources. [More information]
- clinisift: multitool for processing clinical medical records.
- clinitokenizer: Sentence tokenizer for clinical/medical text.
- bert-Clinical-NER: A Named Entity Recognition model for clinical entities (problem, treatment, test).
- bert-Med-NER: A Named Entity Recognition model for medication entities (medication name, dosage, duration, frequency, reason).