Machine learning techniques for medical images in PCOS-Reference-Cited by-同舟云学术

Machine learning techniques for medical images in PCOS

Published:2022-12-09 Issue: Volume: Page:
ISSN:
Container-title:2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)
language:
Short-container-title:

Author:

Makhdoomi Anaa¹,Jan Naila¹,Palak Palak²,Goel Nidhi¹

Affiliation:

1. IGDTUW,Dept. of ECE,Delhi

2. DTU,Dept. of ECE,Delhi

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10064684/10064724/10064817.pdf?arnumber=10064817

Reference24 articles.

1. Classification of polycystic ovary based on ultrasound images using competitive neural network

2. Epileptic Seizure Detection Using Rhythmicity Spectrogram and Cross-Patient Test Set

3. Follicles classification to detect polycystic ovary syndrome using glcm and novel hybrid machine learning;nilofer;Turkish Journal of Computer and Mathematics Education (TURCOMAT),2021

4. Ultimate guide to object detection using deep learning [2022] — upgrad blog,0

5. Modified backpropagation algorithm for polycystic ovary syndrome detection based on ultrasound images;wisesty;International Conference on Soft Computing and Data Mining,2016

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Nutritional management recommendation systems in polycystic ovary syndrome: a systematic review;BMC Women's Health;2024-04-12

2. Explainable Artificial Intelligence based Detection and Early Diagnosis of Polycystic Ovaries Syndrome using Optimized Hybrid Deep Learning Technique;International Journal of Advanced Research in Science, Communication and Technology;2024-04-10

3. Comparative Analysis of Feature Selection Methods for Automatic Classification of PCOD;2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON);2023-12-01

4. Pcos Prediction: Advancements in Medical Informatics Using Artificial Intelligence;2023 2nd International Conference on Futuristic Technologies (INCOFT);2023-11-24

5. Comparing Different Models for Polycystic Ovary Syndrome Diagnosis: An Empirical Investigation on a Large Clinical Dataset;2023 IEEE Women in Technology Conference (WINTECHCON);2023-09-21