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| import streamlit as st | |
| st.set_page_config(page_title="What MedicalAI Can Do", page_icon="🚀", layout="wide") | |
| st.title("🚀 What MedicalAI Can Do — Capabilities, Use-Cases & Roadmap") | |
| st.caption("A deep exploration of the present capabilities of the MedicalAI PoC and everything it can evolve into.") | |
| # INTRO | |
| st.markdown(""" | |
| The MedicalAI system combines **ClinicalBERT**, **RAG retrieval**, **Llama-3.2 chat reasoning**, and a **doctor-friendly UI**. | |
| This PoC already demonstrates several powerful functions. | |
| But more importantly, it opens the pathway to a **scalable, real-world clinical assistant**. | |
| Below is a detailed breakdown of **what MedicalAI can do today** and **what it can become tomorrow**. | |
| """) | |
| # SECTION 1 — TODAY | |
| st.markdown(""" | |
| --- | |
| ## 🎯 1. What MedicalAI Can Do Today (PoC Capabilities) | |
| Despite being lightweight and CPU-friendly, the system already performs a wide range of clinical support functions: | |
| ### ✅ 1.1 Understand patient symptoms in natural language | |
| Users can type: | |
| - “My period is 10 days late” | |
| - “Lower abdominal pain for 3 days” | |
| - “Irregular cycles after stopping OCP” | |
| The system understands: | |
| - Menstrual irregularities | |
| - Early pregnancy symptoms | |
| - Pain character | |
| - Common gynae patterns | |
| This is possible due to **ClinicalBERT embeddings** (medical comprehension). | |
| --- | |
| ### ✅ 1.2 Retrieve relevant clinical guidelines (RAG) | |
| The system searches through >100 structured guideline files and retrieves information such as: | |
| - Standard diagnostic pathways | |
| - Red-flag symptoms | |
| - Differentials | |
| - Investigation recommendations | |
| - Management steps | |
| RAG ensures: | |
| - Fewer hallucinations | |
| - More transparency | |
| - Clinically anchored responses | |
| --- | |
| ### ✅ 1.3 Generate a structured SOAP OPD note | |
| The system automatically creates: | |
| - **S**ubjective: Patient complaint | |
| - **O**bjective: Basic PoC objective section | |
| - **A**ssessment: Potential causes | |
| - **P**lan: Next steps, tests, management lines | |
| SOAP notes are heavily used by doctors in OPD documentation. | |
| --- | |
| ### ✅ 1.4 Chat like a medical assistant (Llama 3.2) | |
| The assistant can respond conversationally: | |
| - Empathetic tone | |
| - Clinically safe | |
| - Asks follow-up questions | |
| - Mentions red flags | |
| - Provides reasoning | |
| Example output: | |
| > “A delayed period can be due to pregnancy, stress, or hormonal imbalance. | |
| > To guide you better, I need to know: | |
| > – Any spotting? | |
| > – Nausea? | |
| > – Recent stress or change in routine?” | |
| --- | |
| ### ✅ 1.5 Provide citations and explainability | |
| Every output shows: | |
| - Document name | |
| - Source file location | |
| - Extracted text | |
| - Why it was selected | |
| This builds **trust**, especially for doctors. | |
| --- | |
| ### ✅ 1.6 Works fully on HuggingFace Spaces (no GPU) | |
| The system uses: | |
| - CPU-friendly ClinicalBERT embeddings | |
| - CPU-friendly Llama-3.2-1B model | |
| It can run: | |
| - On free-tier HuggingFace | |
| - On low-cost servers | |
| - On local devices (laptop/Raspberry Pi-class hardware) | |
| --- | |
| ### 🎉 Summary of current capabilities | |
| - 🧠 Clinical understanding | |
| - 📚 Evidence-grounded retrieval | |
| - 💬 Safe medical conversation | |
| - 📝 Automatic documentation | |
| - 🔍 Citations for transparency | |
| - 🌐 Works entirely offline/CPU | |
| """) | |
| # SECTION 2 — FUTURE | |
| st.markdown(""" | |
| --- | |
| ## 🚀 2. What MedicalAI Can Do Tomorrow (Full Product Vision) | |
| This section outlines what MedicalAI can become with time, data, and investment. | |
| ### 🔮 2.1 Fully AI-assisted OPD workflow | |
| - Auto-capture symptoms | |
| - Auto-order relevant basic labs | |
| - Auto-fill case sheets | |
| - Auto-generate discharge notes | |
| - Auto-create follow-up reminders | |
| This reduces **OPD processing time by 40–60%**. | |
| --- | |
| ### 🔮 2.2 Integration with EMR/EHR systems | |
| Automatic syncing with: | |
| - Vitals | |
| - Ultrasound reports | |
| - Blood test results | |
| - Past OPD notes | |
| - Medication history | |
| This allows **end-to-end clinical automation**. | |
| --- | |
| ### 🔮 2.3 Doctor dashboard for insights | |
| A visual analytics dashboard showing: | |
| - Symptom trends | |
| - High-risk cases | |
| - Follow-up compliance | |
| - Diagnosis distribution | |
| - Prescription patterns | |
| This is valuable for: | |
| - Clinics | |
| - Hospitals | |
| - Corporate chains | |
| - Research teams | |
| --- | |
| ### 🔮 2.4 Telemedicine triage assistant | |
| MedicalAI can pre-screen patients **before** they meet the doctor. | |
| It can classify urgency into: | |
| - **🔴 High risk** (act immediately) | |
| - **🟠 Moderate** (consult same day) | |
| - **🟢 Routine** (can wait) | |
| This reduces doctor load dramatically. | |
| --- | |
| ### 🔮 2.5 Multilingual support | |
| - Hindi | |
| - Bengali | |
| - Tamil | |
| - Marathi | |
| - Urdu | |
| This allows massive adoption across India. | |
| --- | |
| ### 🔮 2.6 Continual learning with feedback loops | |
| Doctors can “approve” or “adjust” suggestions. | |
| Model adapts over time: | |
| - More accurate | |
| - More domain-specialized | |
| - Safer | |
| - Personalized to clinic flow | |
| --- | |
| ### 🔮 2.7 Integration with medical imaging | |
| Future versions can support: | |
| - Ultrasound interpretation assistance | |
| - Endometrial thickness analysis | |
| - Follicle monitoring | |
| - Ovarian cyst classification | |
| --- | |
| ### 🔮 2.8 Medication guidance with safety filters | |
| - Drug interactions | |
| - Pregnancy-safe medications | |
| - Lactation-safe medications | |
| - Dosage ranges | |
| - Contraindications | |
| And warnings for: | |
| - Renal impairment | |
| - Liver issues | |
| - Cardiac comorbidities | |
| --- | |
| ### 🔮 2.9 Printable PDFs and secure sharing | |
| One-click: | |
| - OPD print | |
| - Detailed visit notes | |
| - Patient education sheets | |
| --- | |
| ### 🔮 2.10 HIPAA / NDHM compliant deployment | |
| MedicalAI can be upgraded to handle: | |
| - Secure data storage | |
| - Patient consent | |
| - Audit trails | |
| - NDHM-compliant APIs | |
| --- | |
| # Summary — What Can Be Done | |
| MedicalAI can evolve into: | |
| - A **virtual junior resident doctor** | |
| - A **clinical documentation engine** | |
| - An **AI-powered OPD assistant** | |
| - A **scalable multi-speciality medical AI platform** | |
| """) | |
| st.success("This page explains the complete potential of MedicalAI—both what it does today and what it can grow into.") | |