Dermopsy
Project Overview
Challenges
Category
Year
About
Traditional methods for diagnosing skin disorders, including cancer and fungal infections, are often slow, costly, and invasive. This solution utilises a reflectance confocal microscope combined with advanced generative AI and deep learning techniques to provide rapid, non-invasive diagnosis. This system performs virtual staining and segments infection samples without the need for traditional histological stains, reducing diagnostic time from days to minutes and lowering costs. Integrated on a cloud platform, it enables dermatopathologists to make swift, accurate decisions, significantly improving patient outcomes
Team
Mashaal Ibne Masha Allah
National University of Sciences & Technology (NUST)
I am a passionate entrepreneur with a background in Computer Engineering, dedicated to solving global challenges through innovative solutions. My work at Dermopsy leverages AI and deep learning to revolutionize the diagnosis of skin diseases, reducing costs and improving outcomes through early detection. I am also the co-founder of ClassNotes, an edtech startup where I’ve helped over 30 million students get access to quality education. With a focus on impactful problem-solving, I continue to push the boundaries of technology for social good.
Abdullah Arshad
National University of Sciences & Technology (NUST)
Abdullah Arshad, a Computer Engineering graduate from NUST, Pakistan, is a Software Engineer at Osol. Specializing in AI and backend development, he contributed to project Dermopsy, advancing skin disease diagnosis in collaboration with NIDI Skin and BIOMISA.
Faizan Sohail
National University of Sciences & Technology (NUST)
Faizan Sohail, a Computer Engineering graduate and Automation Engineer at Walimax Limited UK. Passionate about business automation, I specialize in optimizing workflows for e-commerce platforms like Amazon and eBay. Collaborating with NIDI Skin, I contributed to Dermopsy, skin cancer diagnostics with advanced machine learning. I strive to deliver impactful, innovative solutions.
Ammad Ali
National University of Sciences & Technology (NUST)
Ammad is an AI Engineer at CureMD and a graduate of NUST Pakistan with a degree in Computer Engineering. He has a solid background in AI-driven solutions and a wealth of expertise working on medical AI projects, helping to develop cutting-edge healthcare technologies. Ammad is committed to using cutting-edge technology to address difficult problems and promote significant advancements in the field of artificial intelligence.
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