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English
$
USD
I will build deep learning models for medical image analysis
About this Gig
Are you a medical researcher, healthcare startup, or a data scientist looking to extract life-saving insights from complex medical imagery?
I am an AI & Data Science Engineer specialized in developing highly accurate, production-ready Deep Learning models specifically designed for the healthcare and medical imaging domain.
What I Offer in This Gig:
- DICOM Processing: Robust preprocessing pipelines for handling raw medical formats (DICOM, NIfTI, etc.) including windowing, normalization, and artifact removal.
- Advanced Architectures: Custom model building using advanced CNNs and Multiple Instance Learning (MIL) algorithms, perfect for identifying localized pathologies in high-resolution scans.
- Large-Scale Training: Capability to handle and scale massive datasets (e.g., 18,000+ image cohorts) utilizing high-performance A100 GPU accelerated training environments.
- Precision Tuning: Medical AI is not just about accuracy. I provide rigorous statistical evaluation and exact optimum decision threshold tuning (e.g., pinpointing the exact cut-off like 0.409) to maximize Sensitivity and Specificity.
- Explainable AI (XAI): Integrating Grad-CAM and heatmap overlays so medical professionals can vis
Programming language:
Python
•
SQL
•
Java
Tools:
Jupyter Notebook
•
OpenCV
•
TensorFlow
•
Excel
•
Colab
•
PyTorch
Frameworks:
Scikit-learn
•
Keras
•
PyTorch
My Portfolio
FAQ
Do you handle raw DICOM files?
Yes, I can build preprocessing pipelines to correctly extract, window, and normalize pixel arrays from raw DICOM headers before feeding them into the deep learning models.
Can you handle extremely large datasets?
Absolutely. I utilize optimized data generators and A100 GPU environments to efficiently train models on large cohorts (e.g., 18,000+ scans) without memory bottlenecks.
