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Fiverr Pro
English
$
USD
I will build an ai power virtual healthcare system
Aman Bhatnagar
About this gig
Transform Healthcare with ProDoc: The Future of AI Diagnostics
Stop guessing and start predicting. I will build ProDoc, a cutting-edge, AI-driven virtual healthcare system that turns patient vitals into actionable medical intelligence.
Why Choose ProDoc?
ProDoc doesn't just analyze data; it simulates a clinical consultation. By leveraging advanced Machine Learning, this system provides:
Precision Diagnostics: Instant disease prediction based on real-time vitals and symptoms.
Smart Recovery Tracking: An industry-first feature that calculates the exact estimated days to full recovery.
Automated Care Plans: Generates immediate precautions and smart prescriptions tailored to the diagnosis.
What You Get:
High-Accuracy ML Models: Trained on diverse medical datasets for reliable output.
Modern Interactive UI: A sleek, user-friendly dashboard for both patients and providers.
Scalable Architecture: Built with high-performance frameworks like FastAPI or Django.
Data Security: Prioritizing patient privacy and secure data handling.
Bring your healthcare vision to life with a system that thinks, predicts, and prescribes.
Get to know Aman Bhatnagar
Aman Bhatnagar
Achuta : Gen AI Solutions
- FromIndia
- Member sinceOct 2025
Languages
Hindi, English
Driven tech innovator skilled in Python, SQL & ML. Built smart AI tools, chatbots & data apps as freelance projects — turning ideas into impact with crafting smart, automated, data-powered solutions that merge intelligence with creativity.
My Portfolio
FAQ
Is patient data secure?
Yes. I implement industry-standard encryption and secure database protocols. For Premium orders, I can structure the backend to align with HIPAA/GDPR data privacy requirements.
Can I customize the diseases and vitals?
Absolutely. I can retrain the AI model using your specific medical datasets or focus on specialized areas like Cardiology or Pediatrics based on your project needs.
Can this system integrate with medical IoT devices?
Yes. I build the backend with RESTful APIs, allowing it to consume real-time data from wearable sensors or IoT devices (like heart rate or blood oxygen monitors) via JSON payloads or WebSockets.
What do I get in the "Recovery Prediction"?
Using regression analysis, the AI estimates recovery time based on symptom severity, age, and vital trends, providing patients with a realistic healing timeline.
Which Machine Learning models are used for diagnosis?
I implement ensemble models like XGBoost, Random Forest, or LightGBM. These are chosen for their high interpretability in medical contexts, ensuring the "Why" behind a prediction is as clear as the result itself.
