| | Category | CS | P07 | Catch it Early: Web-Based Screening for Melanoma |
| | Abstract | Artificial intelligence has the potential to improve early detection rates for |
| | melanoma. If caught early melanoma, the most dangerous form of |
| | malignant skin cancer, can be surgically removed with a near 100 percent |
| | survival rate. Despite this, melanoma kills more than 60,000 people every |
| | year. Identifying early-stage melanoma with the naked eye is exceptionally |
| | hard, meaning that the average person is unaware of their melanoma until |
| | later stages. An automated diagnosis system was created using artificial |
| | neural networks and principal components analysis. The system screens |
| | images for signs of melanoma and produces a positive or negative result. |
| | The computer-aided melanoma diagnosis system achieved an overall |
| | accuracy of 75%. A freely available website was created using the |
| | system. The website will allow more accurate self-examinations, second- |
| | opinions for dermatologists, or clinical use in rural areas or third-world |
| | countries. Hopefully, this will increase early detection of melanoma and |
| | reduce mortality rates. |
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