Student Work
Exploring Inclusive Reasoning in AI
PubblicoContenuto scaricabile
open in viewerRacism is embedded into the health industry in a subconscious level, influencing people in a subconscious level and backed by institutional policies. We set out to develop a machine learning algorithm to detect cancerous melanoma in a patient's skin, ensuring that the results of this system remain fair and consistent regardless of the patient's ethnicity or origin. While Convolutional Neural Networks (CNNs) yielded 79.8% accuracy, the highest of the algorithms we tested, there's still room for improvement, and we believe that further research in this subject should be done.
- This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
- Creator
- Subject
- Publisher
- Identifier
- E-project-050621-094300
- 22731
- Advisor
- Year
- 2021
- UN Sustainable Development Goals
- Date created
- 2021-05-06
- Resource type
- Rights statement
- Ultima modifica
- 2021-08-29
Relazioni
- In Collection:
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Elementi
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Final Report_0.pdf | Pubblico | Scaricare |
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