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Nanotechnology in reproductive medicine: from gamete engineering to precision therapeutics.

Infertility represents a significant global health burden, necessitating advanced therapeutic interventions. While Assisted Reproductive Technologies have revolutionized fertility treatment, they remain constrained by limited efficacy, off-target toxicity, and procedural complexity. …

Published: July 8, 2026, midnight
Path beyond the blind end-unravel the imaging spectrum of appendiceal pathologies.

The appendix is involved in a diverse spectrum of inflammatory, infectious, benign, and malignant conditions that extend far beyond acute appendicitis. Although acute appendicitis remains the most common appendiceal emergency, …

Published: June 20, 2026, midnight
IITM Pravartak Announces Batch 03 of Applied Artificial Intelligence and Deep Learning Programme to Build Enterprise-Ready AI Talent - NewsX

IITM Pravartak Announces Batch 03 of Applied Artificial Intelligence and Deep Learning Programme to Build Enterprise-Ready AI Talent NewsX

Published: June 17, 2026, 1:18 p.m.
Emerging Pathways to Non-Invasive Diagnosis in Endometriosis: Integrating Machine Learning, Deep Learning and Multi-Omics Biomarkers.

Endometriosis is a chronic, debilitating condition affecting approximately 10-15% of reproductive-aged women and it is often associated with significant diagnostic delays due to its heterogeneity and unreliable non-invasive tests. Artificial …

Published: June 12, 2026, midnight
Deciphering immune-inflammatory dysregulation in the endometriotic microenvironment: insights from single-cell omics and artificial intelligence.

Endometriosis is a prevalent chronic inflammatory gynecological disorder affecting approximately 10% of reproductive-age women worldwide, characterized by endometrial-like tissue outside the uterine cavity. Ectopic lesion growth tracks closely with immune-inflammatory …

Published: June 11, 2026, midnight
Machine learning models for non-invasive endometriosis triage using a laparoscopically and histologically verified cohort.

To develop and internally validate machine-learning models for non-invasive triage of women at risk for endometriosis using structured clinical variables in a laparoscopically and histologically verified cohort.

Published: June 7, 2026, midnight
Quality of AI-generated post-operative patient education after minimally invasive gynecologic surgery: A comparative analysis.

To compare the quality of AI-generated responses to gynecologic post-operative questions with educational materials published by professional societies.

Published: May 30, 2026, midnight
Endometriosis and Chronic Endometritis: Shared Mechanisms, Diagnostic Challenges, and Clinical Implications in Infertility.

Endometriosis (EM) and chronic endometritis (CE) are both implicated in female infertility, yet the relationship between them remains incompletely understood. In this narrative review, we synthesize non-systematically selected clinical and …

Published: May 27, 2026, midnight
Artificial intelligence potential in ovarian endometriosis imaging: a comparative meta-analysis of transvaginal ultrasound-based AI models and human readers.

Transvaginal ultrasound (TVUS) is widely used for diagnosing ovarian endometriosis but remains limited by significant operator dependency. This systematic review and meta-analysis evaluated the diagnostic accuracy of ultrasound-based artificial intelligence …

Published: May 26, 2026, midnight
Endo-MedSAM: a promptable vision foundation model adaptation for uterus segmentation on pelvic MRI in endometriosis.

Endometriosis is a common gynecologic condition in which pelvic MRI plays an important role in diagnosis and preoperative assessment. AI-enabled automated uterus segmentation on pelvic MRI could support endometriosis care …

Published: May 25, 2026, midnight
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