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Improving the Lives of Women: Advancing Endometriosis Research with Machine Learning - News from Medicon Valley

Improving the Lives of Women: Advancing Endometriosis Research with Machine Learning News from Medicon Valley

Published: Nov. 2, 2024, 2:54 a.m.
Understanding AI's Role in Endometriosis Patient Education and Evaluating Its Information and Accuracy: Systematic Review.

Endometriosis is a chronic gynecological condition that affects a significant portion of women of reproductive age, leading to debilitating symptoms such as chronic pelvic pain and infertility. Despite advancements in …

Published: Oct. 30, 2024, midnight
Machine Learning-Based Detection of Endometriosis: A Retrospective Study in A Population of Iranian Female Patients.

Endometriosis, is a prevalent condition among women of childbearing age, characterized by the presence of ectopic endometrial glands. It is associated with pelvic pain and infertility. Unfortunately, the diagnosis of …

Published: Oct. 30, 2024, midnight
Identification of a disulfidptosis-related genes signature for diagnostic and immune infiltration characteristics in endometriosis.

Endometriosis (EMs) is the prevalent gynecological disease with the typical features of intricate pathogenesis and immune-related factors. Currently, there is no effective therapeutic intervention for EMs. Disulfidptosis, the cell death …

Published: Oct. 29, 2024, midnight
Research progress on correlative prediction factors and prediction models of endometriosis associated ovarian carcinoma.

Endometriosis is a common benign disease in women of childbearing age, with a malignant change rate of about 1%. Endometriosis associated ovarian cancer (EAOC), which usually occurs in the ovaries, …

Published: Oct. 22, 2024, midnight
Evaluation of the diagnostic utility of immune microenvironment-related biomarkers in endometriosis using multidimensional transcriptomic data.

Endometriosis (EMS) is a relatively common gynecological disorder and almost fifty percent of women with EMS suffer from infertility. There are few treatment options for endometriosis, and often recurrences occur …

Published: Sept. 24, 2024, midnight
A stacked machine learning-based classification model for endometriosis and adenomyosis: a retrospective cohort study utilizing peripheral blood and coagulation markers.

Endometriosis (EMs) and adenomyosis (AD) are common gynecological diseases that impact women's health, and they share symptoms such as dysmenorrhea, chronic pain, and infertility, which adversely affect women's quality of …

Published: Sept. 10, 2024, midnight
Looking into the future: a machine learning powered prediction model for oocyte return rates after cryopreservation.

Could a predictive model, using data from all US fertility clinics reporting to the Society for Assisted Reproductive Technology, estimate the likelihood of patients using their stored oocytes?

Published: Aug. 29, 2024, midnight
Construction and validation of a clinical risk model based on machine learning for screening characteristic factors of lymphovascular space invasion in endometrial cancer - Nature.com

Construction and validation of a clinical risk model based on machine learning for screening characteristic factors of lymphovascular space invasion in endometrial cancer Nature.com

Published: June 1, 2024, 7 a.m.
Early Warnings: Harnessing machine learning insights to improve endometrial cancer diagnosis - Carle Health

Early Warnings: Harnessing machine learning insights to improve endometrial cancer diagnosis Carle Health

Published: Feb. 13, 2024, 8 a.m.
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