Oncology Data Integration
We integrate clinical data, fine-tune models, and validate with experts for optimal oncology solutions.
Clinical Data Curation
Curating de-identified data from over 500 interventional oncology cases for comprehensive analysis and insights.
Model Fine-Tuning
Fine-tuning GPT-4 on oncology-specific guidelines and literature to enhance decision-making and reporting.
Oncology Integration
Hybrid design for clinical data integration and expert validation.
Model Training
Fine-tuning GPT-4 on oncology-specific guidelines and academic literature.
Web Assistant
Developing an API-driven assistant for clinician decision support and reporting.
The research is expected to produce:
A domain-adapted GPT-4 model for interpreting complex oncological data and supporting interventional treatment planning.
A prototype assistant capable of translating imaging and genomic information into actionable interventional procedures.
Reduced time and cognitive load for clinicians by automating documentation and cross-modality data synthesis.
Contributions to human-AI collaboration paradigms in precision oncology, demonstrating how LLMs can augment rather than replace expert decision-making.
This will also offer broader implications for regulatory-compliant AI in medicine and increase confidence in AI-driven decision support systems.