A machine learning-based immune response signature to facilitate prognosis prediction in patients with endometrial cancer | Scientific Reports Nature.com
A machine learning-based immune response signature to facilitate prognosis prediction in patients with endometrial cancer Nature.com
How can we best achieve tissue segmentation and cell counting of multichannel-stained endometriosis sections to understand tissue composition?
This study addresses the challenges in the early diagnosis of deep infiltrating endometriosis (DIE) by exploring the potential role of the deubiquitinating enzyme USP14. By analyzing the GSE141549 dataset from …
Digital twin technology, originally developed for intricate physical systems, holds great potential in women's healthcare, particularly in the management of pelvic floor disorders. This paper delves into the development of …
Improving the Lives of Women: Advancing Endometriosis Research with Machine Learning News from Medicon Valley
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 …
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 …
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 …
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, …