AIMC Topic: Postmenopause
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Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women.
BMC medical imaging
Jul 1, 2025
BACKGROUND: Current ultrasound-based screening for endometrial cancer (EC) primarily relies on endometrial thickness (ET) and morphological evaluation, which suffer from low specificity and high interobserver variability. This study aimed to develop ...
Evaluation of fragility fracture risk using deep learning based on ultrasound radio frequency signal.
Endocrine
Jul 9, 2024
BACKGROUND: It was essential to identify individuals at high risk of fragility fracture and prevented them due to the significant morbidity, mortality, and economic burden associated with fragility fracture. The quantitative ultrasound (QUS) showed p...
Prevalence of non-communicable chronic diseases in rural India amongst peri- and post-menopausal women: Can artificial intelligence help in early identification?
Maturitas
May 16, 2024
AIMS: To identify peri- and post-menopausal women at risk of non-communicable diseases in rural India and to assess their prevalence amongst these groups via the use of artificial intelligence.
Automatic segmentation of lower limb muscles from MR images of post-menopausal women based on deep learning and data augmentation.
PloS one
Apr 2, 2024
Individual muscle segmentation is the process of partitioning medical images into regions representing each muscle. It can be used to isolate spatially structured quantitative muscle characteristics, such as volume, geometry, and the level of fat inf...
Phenotyping Women Based on Dietary Macronutrients, Physical Activity, and Body Weight Using Machine Learning Tools.
Nutrients
Jul 22, 2019
Nutritional phenotyping can help achieve personalized nutrition, and machine learning tools may offer novel means to achieve phenotyping. The primary aim of this study was to use energy balance components, namely input (dietary energy intake and macr...
8-Hydroxy-2'-deoxyguanosine as a Discriminatory Biomarker for Early Detection of Breast Cancer.
Clinical breast cancer
Dec 21, 2018
BACKGROUND: Breast cancer (BC) is one of the most prevalent and reported cancers among Saudi women. Detection of BC in the early invasive stage (stages I, II) has an advantage in treating patients over detection in the late invasive stage (stages III...
The utility of artificial neural networks and classification and regression trees for the prediction of endometrial cancer in postmenopausal women.
Public health
Aug 24, 2018
OBJECTIVE: Artificial neural networks (ANNs) and classification and regression trees (CARTs) have been previously used for the prediction of cancer in several fields. In our study, we aim to investigate the diagnostic accuracy of three different meth...
Comparison of Changes in the Lipid Profiles of Eastern Chinese Postmenopausal Women With Early-Stage Breast Cancer Treated With Different Aromatase Inhibitors: A Retrospective Study.
Clinical pharmacology in drug development
Dec 29, 2017
Cardiovascular morbidity is closely associated with serum lipid level. We aimed to investigate the effects of different aromatase inhibitors, including letrozole, anastrozole, and exemestane, on the lipid profile of eastern Chinese breast cancer pati...
Artificial neural networks to predict future bone mineral density and bone loss rate in Japanese postmenopausal women.
BMC research notes
Nov 10, 2017
OBJECTIVE: Predictions of the future bone mineral density and bone loss rate are important to tailor medicine for women with osteoporosis, because of the possible presence of personal risk factors affecting the severity of osteoporosis in the future....
The effect of genistein on glucose control and insulin sensitivity in postmenopausal women: A meta-analysis.
Maturitas
Dec 28, 2016
Preclinical studies have revealed the beneficial effects of genistein in pancreatic β-cell functions. The results of randomized controlled trials (RCTs) in assessing the effects of genistein on glucose metabolism are inconsistent, however. The aim of...
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