Latest AI and machine learning research in menopause for healthcare professionals.
The objective of this observational study was to evaluate the efficacy of a neck-mounted automated activity monitor (AAM) at detecting early postpartum resumed ovarian cyclicity. A total of 192 lactating cows (primiparous = 73 and multiparous = 119) were enrolled in this study. Cows were continuously monitored by a neck-mounted AAM early postpartum (7 to 30 d in milk; DIM). Calving was classified ...
Atypical femur fractures (AFF) represent a very rare type of fracture that can be difficult to discriminate radiologically from normal femur fractures (NFF). AFFs are associated with drugs that are administered to prevent osteoporosis-related fragility fractures, which are highly prevalent in the elderly population. Given that these fractures are rare and the radiologic changes are subtle currentl...
RATIONALE AND OBJECTIVES: This study aims to investigate the use of radiomics analysis of hip CT imaging to unveil osteoporosis.
Artificial intelligence (AI) radar technology offers several advantages over other technologies, including low cost, privacy assurance, high accuracy,...
OBJECTIVE: To develop and evaluate a fully automated method based on deep learning and phantomless internal calibration for bone mineral density (BMD)...
Previous studies revealed that hormone replacement therapy (HRT) probably has a protective effect for preventing dementia in post-menopausal women. Ho...
Spinal fixation with rigid pedicle screws have shown to be an effective treatment for many patients. However, this surgical option has been proved to ...
BACKGROUND/OBJECTIVE: Patients with systemic mastocytosis are at high risk of developing osteoporosis and fractures. Herein, we report a case of hip f...
Osteoporosis is characterized by low bone mass, bone microarchitecture disruption, and collagen loss, leading to increased fracture risk. In the curre...
Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have been widely used in the human-machine interaction (...
We determined if a convolutional neural network (CNN) deep learning model can accurately segment acute ischemic changes on non-contrast CT compared to...
The application of deep learning (DL) models for screening environmental estrogens (EEs) for the sound management of chemicals has garnered significan...
Adrenal insufficiency (AI) is a serious disorder characterized by the adrenal glucocorticoid deficiency. Regardless of the etiology, AI patients need ...
UNLABELLED: While FRAX with BMD could be more precise in estimating the fracture risk, DL-based models were validated to slightly reduce the number of...
RATIONALE AND OBJECTIVES: To develop an intelligent diagnostic model for osteoporosis screening based on low-dose chest computed tomography (LDCT). Th...
BACKGROUND: Population aging is emerging as an increasingly acute challenge for countries around the world. One particular manifestation of this pheno...
Pathogenic organisms utilize iron to survive and replicate and have evolved many processes to extract iron from human hosts. The goal of this study w...
UNLABELLED: This study utilized deep learning to classify osteoporosis and predict bone density using opportunistic CT scans and independently tested ...
In the present study, a bioelectrochemical reactor (BEC) was utilized to treat two types of real saline produced water (PW). BEC was designed based on...
This paper makes a case for digital mental health and provides insights into how digital technologies can enhance (but not replace) existing mental he...