Core Research Specialization

AI for Healthcare

Comprehensive AI solutions for healthcare including diagnostic support, drug discovery, and patient monitoring.

1 Projects 2 Publications

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In-Depth Overview

Research Focus & Scope

AI for Healthcare represents ICVRL's interdisciplinary initiative merging visual intelligence, physiological sensor analysis, and clinical informatics to enhance patient outcomes, empower clinicians, and modernize healthcare delivery systems.

Methodological Approach

How We Conduct Research in AI for Healthcare

We develop multi-modal clinical decision support systems (CDSS) that fuse medical imaging with electronic health records (EHR) and time-series physiological data while maintaining HIPAA-aligned privacy, federated learning, and adversarial robustness.

Impact & Deployments

Real-World Applications

Comprehensive AI diagnostic assistant for hospitals

Remote patient monitoring and vitals detection

ICU telemetry anomaly prediction

Clinical decision support systems

Post-operative recovery monitoring

Lab Projects

Projects in this Domain

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MedSeg-AI: Intelligent Medical Image Segmentation Platform

An AI-powered platform for automated segmentation of medical images including CT, MRI, and X-ray scans with cl...

active Code

Scholarly Output

Recent Publications

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journal

A Comprehensive Survey of Vision Transformers in Medical Imaging

Shams ur Rehman, Muhammad Hamza, Ayesha Malik, Ahmad Khan

ACM Computing Surveys, 2025

journal

GAN-Based Synthetic Data Augmentation for Rare Disease Classification

Muhammad Hamza, Shams ur Rehman, Ayesha Malik

Medical Image Analysis, 2024

Tech Stack & Tools

Federated Learning PyTorch MONAI Scikit-Learn FastAI OpenCV Flask Docker

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