Oncowise AI is a multi-task healthcare assistant designed to provide intelligent decision support for cancer treatment. By fine-tuning large language models on medical literature (PubMed), the system translates complex clinical data into accessible insights for both medical professionals and patients.
Receive personalized medication suggestions tailored to your unique lab results. With automated result uploading, you no longer have to manually enter complex data; the AI interprets your reports and provides clarity on treatment steps and durations immediately.
Focus on high-level clinical decisions. The Doctor's Dashboard allows you to view all patient-AI interactions. This eliminates repetitive questions during visits, as you can see exactly what the patient has asked and what the AI has already clarified.
Medical knowledge is vast, technical, and often locked behind complex research papers. Building a reliable chatbot requires more than simple text generation; it necessitates accuracy in classification, precision in knowledge extraction, and coherence in natural language response to ensure user safety and trust.
The core value of Oncowise lies in its ability to analyze raw laboratory data (e.g., blood markers, tumor profiles) and map them to standard treatment protocols. By providing data-grounded suggestions on medication type and duration, the system ensures higher adherence and better clinical results.
The system employs a sophisticated cascaded pipeline combining three distinct fine-tuned models:
The backend is powered by a Flask API that handles the model inference logic via AWS Cloud Processing/Google Colab, while the frontend is a modern SwiftUI mobile application integrated with Firebase for secure authentication.
Classification Accuracy
QA Exact Match (EM)
BLEU Score (Linguistics)
Built with AdamW optimization, L2 regularization, and Dropout (0.3). The project manages API security via environment variables to protect OpenAI and backend endpoints.