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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Egile nagusia:	ALAM SUHA, SAYMA
Formatua:	Tesis
Hizkuntza:	ingelesa
Argitaratua:	Department of Computer Science and Engineering, MIST 2024
Gaiak:	PREDICTING POLYCYSTIC OVARY SYNDROME THROUGH MACHINE LEARNING TECHNIQUE USING PATIENTS’ SYMPTOM DATA AND OVARY ULTRASOUND IMAGES
Sarrera elektronikoa:	http://dspace.mist.ac.bd:8080/xmlui/handle/123456789/776
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!