School of Computer Science and Engineering Researchers Update Current Study Findings on Artificial Intelligence (Innovative approach towards early prediction of ovarian cancer: Machine learning- enabled XAI techniques).

Researchers from the School of Computer Science and Engineering have conducted a study on the early prediction of ovarian cancer using machine learning techniques and explainable artificial intelligence (XAI) methodologies. The study aimed to evaluate the effectiveness of various prediction methodologies, including support vector machines and ensemble learning techniques. The researchers collected a dataset of 349 patients with known ovarian cancer status and applied preprocessing techniques to enhance the input data. The results showed promising accuracy rates, and the study contributes to the field of oncology and women's health by offering a new approach to the early diagnosis of ovarian cancer. [Extracted from the article]