Machine learning has revolutionized problem-solving across fields, including healthcare. With advances in deep learning, skin disease diagnosis can now match or exceed human accuracy, enabling early detection of conditions that could lead to severe outcomes like skin cancer. Skin health is vital, yet diseases arise from genetics, environment, infection, and more. In remote areas of Balochistan, access to expert diagnosis is limited, increasing the need for automated solutions. This project develops a real-time, deep learning-based skin disease detection system to classify multiple conditions, assist dermatologists, improve accuracy, reduce workload, enable timely treatment, and promote skin health awareness.

The project aims to strengthen the bridge between academia and industry by creating a platform for meaningful interaction between students and professionals. Through this initiative, final-year students will have the opportunity to present their senior-year project ideas directly to industry experts, allowing them to gain valuable feedback, improve the practical relevance of their work, and explore potential real-world applications.

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