SmartScanPCOS: A feature-driven approach to cutting-edge prediction of Polycystic Ovary Syndrome using Machine Learning and Explainable Artificial Intelligence
PolyCystic Ovarian Syndrome (PCOS) poses significant challenges to women's reproductive health due to its diagnostic complexity arising from a variety of symptoms, including hirsutism, anovulation, pain, obesity, hyperandrogenism, and oligomenorrhea, necessitating multiple clinical tests. Lever...
Saved in:
| Main Authors: | Umaa Mahesswari G, Uma Maheswari P |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-10-01
|
| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S240584402415236X |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Review of eXplainable artificial intelligence for cybersecurity systems
by: Stéphane Reynaud, et al.
Published: (2025-05-01) -
Legal Perspectives for Explainable Artificial Intelligence in Medicine - Quo Vadis?
by: Cătălin-Mihai PESECAN, et al.
Published: (2025-05-01) -
XAIEnsembleTL-IoV: A new eXplainable Artificial Intelligence ensemble transfer learning for zero-day botnet attack detection in the Internet of Vehicles
by: Yakub Kayode Saheed, et al.
Published: (2024-12-01) -
Can eXplainable AI Offer a New Perspective for Groundwater Recharge Estimation?—Global‐Scale Modeling Using Neural Network
by: Hyekyeng Jung, et al.
Published: (2024-04-01) -
Explainable machine learning framework for biomarker discovery by combining biological age and frailty prediction
by: Xiheng Wang, et al.
Published: (2025-04-01)