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...

Volledige beschrijving

Bibliografische gegevens

Hoofdauteur:	ALAM SUHA, SAYMA
Formaat:	Thesis
Taal:	Engels
Gepubliceerd in:	Department of Computer Science and Engineering, MIST 2024
Onderwerpen:	PREDICTING POLYCYSTIC OVARY SYNDROME THROUGH MACHINE LEARNING TECHNIQUE USING PATIENTS’ SYMPTOM DATA AND OVARY ULTRASOUND IMAGES
Online toegang:	http://dspace.mist.ac.bd:8080/xmlui/handle/123456789/776
Tags:	Voeg label toe Geen labels, Wees de eerste die dit record labelt!