The journal of obstetrics and gynaecology research · 2025
Evaluating apoptotic biomarkers with endometrial histopathological changes in women with abnormal uterine bleeding.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Madhavi Bellala Venkata, Kamal Thallury Shirin, Shankar Bellala Ravi, Bindu Prathipaty Josephine
Аннотация
AIM: Abnormal uterine bleeding (AUB) is a common clinical challenge faced by women, often indicating underlying gynecological disorders, including endometrial pathologies. The evaluation of apoptotic biomarkers has gained attention as a potential method to elucidate the mechanisms driving these pathologies. AUB lacks precise diagnostic tools, with an insufficient understanding of apoptotic biomarkers' roles in endometrial changes, hindering effective management and targeted therapies for affected women.
METHODS: The objectives are to identify apoptotic biomarkers associated with endometrial histopathological changes, evaluate their diagnostic potential for abnormal uterine bleeding, and enhance understanding of underlying biological mechanisms in affected women. Analyzing healthcare data reveals patterns that inform clinical decisions and improve patient outcomes.
RESULTS: Content-based filtering technique combined with deep feedforward neural networks can uncover patterns in biomarkers, forecast histopathological outcomes, improve diagnostic accuracy, and tailor treatment strategies for women experiencing abnormal uterine bleeding. Findings show that in cycles under 21 days, 5% of patients experienced bleeding for 4 days, while 74% had 4-6 days of bleeding, and 21% bled for more than 6 days. This result was implemented using Python software.
CONCLUSIONS: Future research could explore targeted therapies based on apoptotic biomarkers, enhancing diagnostic accuracy and personalized treatment strategies for women with abnormal uterine bleeding and associated endometrial histopathological changes.
METHODS: The objectives are to identify apoptotic biomarkers associated with endometrial histopathological changes, evaluate their diagnostic potential for abnormal uterine bleeding, and enhance understanding of underlying biological mechanisms in affected women. Analyzing healthcare data reveals patterns that inform clinical decisions and improve patient outcomes.
RESULTS: Content-based filtering technique combined with deep feedforward neural networks can uncover patterns in biomarkers, forecast histopathological outcomes, improve diagnostic accuracy, and tailor treatment strategies for women experiencing abnormal uterine bleeding. Findings show that in cycles under 21 days, 5% of patients experienced bleeding for 4 days, while 74% had 4-6 days of bleeding, and 21% bled for more than 6 days. This result was implemented using Python software.
CONCLUSIONS: Future research could explore targeted therapies based on apoptotic biomarkers, enhancing diagnostic accuracy and personalized treatment strategies for women with abnormal uterine bleeding and associated endometrial histopathological changes.