AI Dermatologist Diagnostic Platform

Q: Who conducted this research project?

Supervised by Dr. Junaid Akram at COMSATS University Islamabad, Lahore Campus with student researchers AI Dermatologist Team.

Q: What technologies and frameworks were utilized?

Python, PyTorch, EfficientNet, Flask

Dr. Junaid Akram; AI Dermatologist Team

Back to Supervision Directory

Fall 2025·Dr. Junaid Akram

Supervised Student Project

CompletedFall 2025BS Computer Science

AI Dermatologist Diagnostic Platform

Completed computer vision healthcare system utilizing deep convolutional networks for automated skin lesion segmentation and dermatological risk classification.

Computer VisionLesion SegmentationDermatology AI

Students

AI Dermatologist Team

Supervision

Dr. Junaid AkramLead Supervisor

Institution

Computer Vision ResearchCOMSATS University Islamabad, Lahore Campus

Supervised Projects Portfolio

Related Research & Supervised Projects

View all projects

AI & Machine Learning

HemaAI — Diagnostic Intelligence System

Completed biomedical machine learning project deploying deep convolutional neural networks to classify blood cell microscopic images and detect diagnostic anomalies automatically.

HemaAI Student TeamView Case Study

AI & Machine Learning

Cric-Craft — AI Cricket Performance Analysis System

Completed sports analytics platform combining computer vision for ball-tracking, player biomechanics assessment, and statistical match prediction.

SP25SE22 Student GroupView Case Study

AI & Machine Learning

ApneaGuard AI — Sleep Apnea Detection System

Completed biomedical signal processing system utilizing audio sensor processing and machine learning to detect nocturnal sleep apnea events in real time.

SP25CS03 Student GroupView Case Study