Inspiration
At "Skin Skan," our inspiration comes from a deep commitment to making a life-changing impact. Witnessing the devastating effects of untreated skin conditions, we harness the potential of AI and Machine Learning to create a user-friendly platform that detects skin diseases early. We envision a world where no one suffers needlessly, where skin health is prioritized, and timely intervention saves lives. Through "Skin Skan," we strive to empower individuals, raise awareness, and foster a community dedicated to proactive skin care, transforming the future of skin health for generations to come.
What it does
"Skin Skan" is an AI and Machine Learning-powered platform that allows users to upload pictures of their skin lesions or affected areas. The system analyzes the images using computer vision and machine learning techniques to detect potential skin diseases. By offering instant feedback and early detection, "Skin Skan" aims to empower individuals to seek timely medical attention, reducing the rates of severe illness and death caused by skin problems, while promoting proactive skin health and overall well-being.
How we built it
First, we acquired skin cancer and burn datasets from Kaggle. Then, in PyTorch, we used transfer learning with the ResNet-18 Convolutional Neural Network. We finetuned our model based on the datasets. Then, we created a Flask framework, combining Python and HTML. On the backend, we called our model to develop predictions based on inputted images. On the frontend, we employed Bootstrap and JavaScript to create a simple yet elegant interface for users.
Challenges we ran into
Challenges we ran into were inputting images based on forms with flask and properly handling them to be processed by our machine learning model. We were also challenged by the high amount of JavaScript required throughout the app.
Accomplishments that we're proud of
We are very proud of the frontend of our website, as it is the most complex we have created so far. We are also proud of the high accuracy rate of the diagnoses by the machine learning model.
What we learned
From the "Skin Skan" project, we learned the power of AI in healthcare, the impact of early detection, the importance of user-centric design and data privacy, and the potential for technology to empower individuals in proactive healthcare. The project highlighted the social impact of technology, fostering a community focused on wellness and inspiring continuous innovation in healthcare.
What's next for Skin Skan
We plan to add more types of skin problems, such as classifying the different types of acne (yay teenage life).
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