3 papers
eess.IV2026
Blasto-Net: An Explainable Multi-Task Learning for Blastocyst Segmentation, Grading, and Implantation Prediction
Zahra Asghari Varzaneh, Reza Khoshkangini, Magnus Johnsson +2
This study introduces Blasto-Net, a multi-task deep learning model for comprehensive blastocyst analysis. The proposed model performs three tasks simultaneously in a single forward…
cs.AI2026
Context-Aware Hierarchical Bayesian Modeling of IVF Laboratory Environmental Conditions
Zahra Asghari Varzaneh, Reza Khoshkangini, Pia Saldeen +2
IVF pregnancy rates are routinely modeled using patient-level variables, while high-resolution laboratory environmental data remain underutilized. We show that this is a missed opp…
cs.AI2026
Interpretable Sperm Morphology Classification via Attention-Guided Deep Learning
Zahra Asghari Varzaneh, Reza Khoshkangini, Thomas Ebner +1
Male infertility is a major cause of couple infertility, often linked to abnormal sperm morphology. While deep learning models offer automated analysis, most lack interpretability,…