HRT

A Graph Neural Network Model with a Transparent Decision-Making Process Defines the Applicability Domain for Environmental Estrogen Screening.

The application of deep learning (DL) models for screening environmental estrogens (EEs) for the sound management of chemicals has garnered significant attention. However, the currently available DL model for screening EEs lacks both a transparent decision-making process and effective applicability domain (AD) characterization, making the reliability of its prediction results uncertain and limitin...

Osteoporosis in Adrenal Insufficiency: Could Metformin be Protective?

Adrenal insufficiency (AI) is a serious disorder characterized by the adrenal glucocorticoid deficiency. Regardless of the etiology, AI patients need long-term replacement therapy for glucocorticoids and, in some cases, for mineralocorticoids. The replacement therapy cannot completely mirror the physiological secretion patterns, and therefore, glucocorticoid excess is a common sequela in AI patien...

Establish and validate the reliability of predictive models in bone mineral density by deep learning as examination tool for women.

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...

Combining Deep Learning and Radiomics for Automated, Objective, Comprehensive Bone Mineral Density Assessment From Low-Dose Chest Computed Tomography.

RATIONALE AND OBJECTIVES: To develop an intelligent diagnostic model for osteoporosis screening based on low-dose chest computed tomography (LDCT). Th...

Comparison between linear regression and four different machine learning methods in selecting risk factors for osteoporosis in a Chinese female aged cohort.

BACKGROUND: Population aging is emerging as an increasingly acute challenge for countries around the world. One particular manifestation of this pheno...

A study on whether deep learning models based on CT images for bone density classification and prediction can be used for opportunistic osteoporosis screening.

UNLABELLED: This study utilized deep learning to classify osteoporosis and predict bone density using opportunistic CT scans and independently tested ...

Saline wastewater treatment by bioelectrochemical process (BEC) based on Al-electrocoagulation and halophilic bacteria: optimization using ANN with new approach.

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...

MATH: A Deep Learning Approach in QSAR for Estrogen Receptor Alpha Inhibitors.

Breast cancer ranks as the second leading cause of death among women, but early screening and self-awareness can help prevent it. Hormone therapy drug...

Validation of bone mineral density measurement using quantitative CBCT image based on deep learning.

The bone mineral density (BMD) measurement is a direct method of estimating human bone mass for diagnosing osteoporosis, and performed to objectively ...

Modeling and insights into the structural characteristics of endocrine-disrupting chemicals.

Endocrine-disrupting chemicals (EDCs) can cause serious harm to human health and the environment; therefore, it is important to rapidly and correctly ...

Generalizability of Deep Learning Classification of Spinal Osteoporotic Compression Fractures on Radiographs Using an Adaptation of the Modified-2 Algorithm-Based Qualitative Criteria.

RATIONALE AND OBJECTIVES: Spinal osteoporotic compression fractures (OCFs) can be an early biomarker for osteoporosis but are often subtle, incidental...

Detrimental Effects of Saccharum officinarum Juice on Reproductive Functions of Female Wistar Rats.

Changing dietary compositions have contributed to the growing epidemic of metabolic diseases with serious impacts on several aspects of health, includ...

Prediction of osteoporosis using MRI and CT scans with unimodal and multimodal deep-learning models.

PURPOSE: Osteoporosis is the systematic degeneration of the human skeleton, with consequences ranging from a reduced quality of life to mortality. The...

Differential diagnosis of benign and malignant vertebral compression fractures: Comparison and correlation of radiomics and deep learning frameworks based on spinal CT and clinical characteristics.

PURPOSE: Differentiating benign from malignant vertebral compression fractures (VCFs) is a diagnostic dilemma in clinical practice. To improve the acc...

Deep-Learning-Based Detection of Vertebral Fracture and Osteoporosis Using Lateral Spine X-Ray Radiography.

Osteoporosis and vertebral fractures (VFs) remain underdiagnosed. The addition of deep learning methods to lateral spine radiography (a simple, widely...

A Deep Learning Approach for Histology-Based Nucleus Segmentation and Tumor Microenvironment Characterization.

Microscopic examination of pathology slides is essential to disease diagnosis and biomedical research. However, traditional manual examination of tiss...

Robot-Assisted Kyphoplasty versus Fluoroscopy-Assisted Kyphoplasty: A Meta-Analysis of Postoperative Outcomes.

Osteoporotic vertebral compression fractures are the most common manifestation of osteoporosis. Percutaneous kyphoplasty (PKP) can lead to both pain i...

Automated, calibration-free quantification of cortical bone porosity and geometry in postmenopausal osteoporosis from ultrashort echo time MRI and deep learning.

BACKGROUND: Assessment of cortical bone porosity and geometry by imaging in vivo can provide useful information about bone quality that is independent...

Deep learning for automatic mandible segmentation on dental panoramic x-ray images.

Many studies in the last decades have correlated mandible bone structure with systemic diseases like osteoporosis. Mandible segmentation, as well as s...

Advances in materials-based therapeutic strategies against osteoporosis.

Osteoporosis is caused by the disruption in homeostasis between bone formation and bone resorption. Conventional management of osteoporosis involves s...