Male infertility contributes substantially to the global infertility burden, and sperm analysis remains central to diagnosis, treatment planning, and assisted reproductive technology. Conventional semen evaluation, however, is labor-intensive, operator-dependent, and limited by inter- and intra-observer variability, motivating the development of objective and reproducible computational approaches.
arXiv:2310. 00505v3 Announce Type: replace-cross Abstract: Fetal health classification is a critical task in obstetrics, enabling early identification and management of potential health problems.
By Sujith K Mandala
arXiv:2606. 20438v1 Announce Type: new Abstract: Male infertility is a major cause of couple infertility, often linked to abnormal sperm morphology.
By Zahra Asghari Varzaneh, Reza Khoshkangini, Thomas Ebner, Lars Johansson
arXiv:2607. 16941v1 Announce Type: cross Abstract: Polycystic Ovarian Syndrome (PCOS) is a widespread hormone problem for women of childbearing age.
By Al Zadid Sultan Bin Habib, Md Asif Bin Syed, Md. Ekramul Islam, Tanpia Tasnim
The paper introduces a dual cross‑attention deep learning framework for automated grading of Cervical Intraepithelial Neoplasia (CIN) and prediction of Swede scores, using a newly released BUET Multi‑Center Colposcopy Dataset. The architecture fuses paired multimodal cervigrams and employs a custom composite loss to handle class imbalance, achieving 71.85% accuracy and 86.23% AUC‑ROC for three‑class CIN grading, and AUC‑ROC values between 75.7% and 88.4% for individual Swede score components. The total predicted Swede Score has a mean absolute error of 1.489, indicating potential for AI‑assisted colposcopy screening in resource‑limited settings.
By Dania Khan, Nuzhat Aisha Shaikh, Asfina Hassan Juicy, Raiyun Kabir, S M Shahida, Taufiq Hasan
Hepatitis C is a liver infection caused by a virus, which results in mild to severe inflammation of the liver. Over many years, hepatitis C gradually damages the liver, often leading to permanent scarring, known as cirrhosis.
arXiv:2606. 26561v1 Announce Type: new Abstract: Hepatitis C is a liver infection caused by a virus, which results in mild to severe inflammation of the liver.
By Abrar Alotaibi, Lujain Alnajrani, Nawal Alsheikh, Alhatoon Alanazy, Salam Alshammasi, Meshael Almusairii, Shoog Alrassan, Aisha Alansari
arXiv:2607. 16250v1 Announce Type: cross Abstract: Estrogen Receptor (ER) status is a critical biomarker in breast cancer diagnosis, prognosis, and treatment selection.
By Priyanka Paudel, Madan Baduwal
arXiv:2609.15225v1 Announce Type: new
Abstract: Objective: To develop an intelligent framework, termed CUA-Net, for the automated classification of congenital uterine anomalies (CUA) without requirin...
By Yueyue Xu, Yuhao Huang, Jiaxiao Deng, Yuanji Zhang, Haoming Zhang, Jiajia Qu, Shiying Zheng, Xiaomei Tang, Haining Chen, Chengcai Chen, Yiyi Wu, Xin Yang, Dong Ni
arXiv:2607. 04486v1 Announce Type: new Abstract: Diagnosing and monitoring diseases frequently involves the analysis of human biological samples, with blood analysis being pivotal.
By Ahmed M. Sayed (Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt), Sondos A. Refaat (Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt), Abdallah M. Mostafa (Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt), Mariam S. El-Rahmany (Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt), Ensaf Hussein Mohamed (Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt, School of Information Technology and Computer Science)
This study evaluates the classification accuracy of six modern deep‑learning architectures—VGG19, ResNet50, GoogleNet, ConvNeXt, EfficientNet, and Vision Transformers—on breast ultrasound images categorized by BI‑RADS. Using 2,945 training images and 936 validation images from 1,540 patients, the models were tested in full fine‑tuning, linear evaluation, and training‑from‑scratch settings. The best performance was achieved with full fine‑tuning, yielding 76.39 % accuracy and a 67.94 % F1 score.
By Malitha Gunawardhana, Norbert Zolek
arXiv:2508. 17728v2 Announce Type: replace-cross Abstract: Cervical cancer remains a significant global health concern and a leading cause of cancer-related deaths among women.
By Nisreen Albzour, Sarah S. Lam