PREDICTING POLYCYSTIC OVARY SYNDROME THROUGH MACHINE LEARNING TECHNIQUE USING PATIENTS’ SYMPTOM DATA AND OVARY ULTRASOUND IMAGES
Polycystic ovary syndrome (PCOS) is the most prevalent endocrinological abnormality & one of the primary causes of anovulatory infertility in women globally. The real-world clinical PCOS detection technique is critical since the accuracy of interpretations being substantially dependent on vast num...
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| Главный автор: | |
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| Формат: | Диссертация |
| Язык: | английский |
| Опубликовано: |
Department of Computer Science and Engineering, MIST
2024
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| Предметы: | |
| Online-ссылка: | http://dspace.mist.ac.bd:8080/xmlui/handle/123456789/776 |
| Метки: |
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