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...
Gorde:
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| Formatua: | Tesis |
| Hizkuntza: | ingelesa |
| Argitaratua: |
Department of Computer Science and Engineering, MIST
2024
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| Gaiak: | |
| Sarrera elektronikoa: | http://dspace.mist.ac.bd:8080/xmlui/handle/123456789/776 |
| Etiketak: |
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Antzeko izenburuak: PREDICTING POLYCYSTIC OVARY SYNDROME THROUGH MACHINE LEARNING TECHNIQUE USING PATIENTS’ SYMPTOM DATA AND OVARY ULTRASOUND IMAGES
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