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...
Kaydedildi:
| Yazar: | |
|---|---|
| Materyal Türü: | Tez |
| Dil: | İngilizce |
| Baskı/Yayın Bilgisi: |
Department of Computer Science and Engineering, MIST
2024
|
| Konular: | |
| Online Erişim: | http://dspace.mist.ac.bd:8080/xmlui/handle/123456789/776 |
| Etiketler: |
Etiket eklenmemiş, İlk siz ekleyin!
|
Benzer Materyaller: PREDICTING POLYCYSTIC OVARY SYNDROME THROUGH MACHINE LEARNING TECHNIQUE USING PATIENTS’ SYMPTOM DATA AND OVARY ULTRASOUND IMAGES
- PREDICTING POLYCYSTIC OVARY SYNDROME THROUGH MACHINE LEARNING TECHNIQUE USING PATIENTS' SYMPTOM DATA AND OVARY ULTRASOUND IMAGES /
- Machine learning for audio,image and video analysis : theory and applications /
- Deep learning /
- Introduction to Machine Learning /
- Machine learning /
- PREDICTION OF FLUID FLOW AROUND 2D SQUARE OBJECTS INSIDE A DOUBLE LID DRIVEN CAVITY USING CFD AND ARTIFICIAL NEURAL NETWORK