Skin cancer detection : spreading awareness through mobile application
Skin cancer is a growing danger, especially the elderly population. Early detection and treatment is critical in reducing the fatality of melanoma. Screening done by a specialist or individual can lead to improved survival rate of melanoma as melanoma is detected at reduced thickness and is easie...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/148182 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Skin cancer is a growing danger, especially the elderly population. Early detection and
treatment is critical in reducing the fatality of melanoma. Screening done by a specialist or
individual can lead to improved survival rate of melanoma as melanoma is detected at
reduced thickness and is easier to treat. However, only a small fraction of individuals have
performed a full body skin examination at least once in their lives as they lack education
on their risks of developing skin cancer.
This project aims to spread awareness on individual’s risk of developing skin cancer
through four assessments: Skin Cancer Detection Algorithm, Skin Risk Assessment,
Profile Risk Assessment, and Lesion Risk Assessments. With increased awareness, the
general public is expected to be more cautious of suspicious skin lesions. This increase in
caution is expected to encourage the general public to go for a check-up with a specialist
earlier, thus facilitating early detection and treatment of skin cancer and reducing the
mortality of skin cancer.
An ensemble machine learning model is created by combining InceptionResNetV2 and
DenseNet201 trained on the HAM10000 dataset. This ensemble model achieved an average
macro-average accuracy of 86% and is used as the Skin Cancer Detection Algorithm.
The main findings of the study are as follows: (1) The users find the application useful and
easy to use, (2) The users display positive attitude and behavioural intention towards using
the application, and (3) The usefulness and usability of the application both significantly
positively influenced the Attitude and Behavioural Intention towards using the application. |
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