You will get AI-Powered Healthcare Intelligence System (Chatbot, RAG, XAI, LLM)
Rising Talent
Rising Talent
Project details
🧠 Role
Lead AI/ML Engineer & Healthcare AI Consultant
Responsible for designing and delivering a secure, scalable, and intelligent GenAI system tailored for clinical and medical document processing. Oversaw architecture, model fine-tuning, pipeline development, and full-stack deployment with compliance awareness.
________________________________________
📋 Project Overview
In this project, I developed an AI-based Healthcare Document Intelligence Platform capable of understanding, retrieving, and summarizing large volumes of unstructured medical documents (e.g., discharge summaries, EHR notes, lab reports, prescriptions).
The system leverages Retrieval-Augmented Generation (RAG) combined with Large Language Models (LLMs) to answer queries like:
• "What medications was the patient prescribed post-surgery?"
• "Summarize key diagnosis insights from the last 6 months."
In addition, Explainable AI (XAI) techniques were applied to ensure transparency, traceability, and compliance with HIPAA/GDPR standards—crucial for adoption in the healthcare sector.
________________________________________
🎯 Goals
• Extract meaningful insights from complex unstructured medical text.
Lead AI/ML Engineer & Healthcare AI Consultant
Responsible for designing and delivering a secure, scalable, and intelligent GenAI system tailored for clinical and medical document processing. Oversaw architecture, model fine-tuning, pipeline development, and full-stack deployment with compliance awareness.
________________________________________
📋 Project Overview
In this project, I developed an AI-based Healthcare Document Intelligence Platform capable of understanding, retrieving, and summarizing large volumes of unstructured medical documents (e.g., discharge summaries, EHR notes, lab reports, prescriptions).
The system leverages Retrieval-Augmented Generation (RAG) combined with Large Language Models (LLMs) to answer queries like:
• "What medications was the patient prescribed post-surgery?"
• "Summarize key diagnosis insights from the last 6 months."
In addition, Explainable AI (XAI) techniques were applied to ensure transparency, traceability, and compliance with HIPAA/GDPR standards—crucial for adoption in the healthcare sector.
________________________________________
🎯 Goals
• Extract meaningful insights from complex unstructured medical text.
Machine Learning Tools
Apache Spark MLlib, Azure Machine Learning, BERT, BigDL, Caffe, ChatGPT, GitHub Copilot, Google AutoML, Google Sheets, Keras, Kubeflow, Microsoft CNTK, MLflow, NLTK, NumPy, OpenCV, pandas, Python, PyTorch, scikit-learn, SQL, TensorFlow, Vertex AI, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$100
|
Standard
$500
|
Advanced
$1,500
|
|---|---|---|---|
| Delivery Time | 2 days | 7 days | 14 days |
Number of Revisions | 5 | 5 | 5 |
Number of Model Variations | 2 | 4 | 6 |
Number of Scenarios | 3 | 5 | 5 |
Number of Graphs/Charts | 3 | 5 | 3 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | |||
Source Code | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$200 - $1,000
Additional Revision
+$50
Additional Model Variation
(+ 1 Day)
+$100
Additional Scenario
(+ 1 Day)
+$100
Additional Graph/Chart
(+ 1 Day)
+$50
Model Documentation
(+ 1 Day)
+$50
Source Code
(+ 1 Day)
+$50
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Donabel M.
Oct 20, 2025
MSFT Email Study - FY26
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Paul M.
Aug 19, 2025
GAN-Based Brain MRI Generation
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About Muhammad
AI Manager | GenAI | LLM | RAG | AI Agents | MLOps | Data Science
100%
Job Success
Rawalpindi, Pakistan - 12:03 pm local time
I specialize in:
Generative AI (LLMs, RAG, AI Agents, Multi-modal AI)
AI Product & Program Management
LLM Training, Evaluation & Benchmarking
Enterprise AI Platforms & MLOps
Secure AI & AI Governance (XAI, Adversarial ML)
I have led large-scale AI programs including:
LLM training pipelines (200+ contributors)
Enterprise RAG platforms
AI-powered document intelligence systems
Geospatial AI and satellite analytics platforms
Secure AI systems for healthcare, finance, and government
I combine deep technical expertise + program leadership + product thinking, ensuring AI systems are not just built — but delivered, scaled, and aligned with business outcomes.
Core Skills
AI & Data Systems
Generative AI (LLM, RAG, Agents, GANs)
LLM Training, Evaluation & RLHF workflows
AI/ML Engineering (PyTorch, TensorFlow, Transformers)
MLOps & AI Infrastructure (Docker, Kubernetes, CI/CD)
Vector Databases (Pinecone, FAISS, ChromaDB)
Document Intelligence & OCR Systems
AI Agents & Workflow Automation
Explainable AI (XAI), Secure ML, Adversarial ML
Program & Product Leadership
AI Technical Program Management
Product Strategy & Roadmap Execution
Agile / Scrum / Hybrid Delivery
Stakeholder & Executive Management
Risk, Dependency & Release Management
Cross-functional Team Leadership
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1
Get Requirements from Stakeholders
Step 2
Prepare what is asked for