Menopause

Application of machine learning algorithms to identify people with low bone density.

BACKGROUND: Osteoporosis is becoming more common worldwide, imposing a substantial burden on individuals and society. The onset of osteoporosis is subtle, early detection is challenging, and population-wide screening is infeasible. Thus, there is a need to develop a method to identify those at high risk for osteoporosis.

Metabolic phenotyping with computed tomography deep learning for metabolic syndrome, osteoporosis and sarcopenia predicts mortality in adults.

BACKGROUND: Computed tomography (CT) body compositions reflect age-related metabolic derangements. We aimed to develop a multi-outcome deep learning model using CT multi-level body composition parameters to detect metabolic syndrome (MS), osteoporosis and sarcopenia by identifying metabolic clusters simultaneously. We also investigated the prognostic value of metabolic phenotyping by CT model for ...

Exploring Human-Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion-Extension Performance across Varied Robot Assistance-Resistance Configurations.

Knee rehabilitation therapy after trauma or neuromotor diseases is fundamental to restore the joint functions as best as possible, exoskeleton robots ...

A novel activation function based on DNA enzyme-free hybridization reaction and its implementation on nonlinear molecular learning systems.

With the advent of the post-Moore's Law era, the development of traditional silicon-based computers has reached its limit, and there is an urgent need...

Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assay.

PURPOSE: To evaluate the Stratipath Breast tool for image-based risk profiling and compare it with an established prognostic multigene assay for risk ...

Vaginal microbiota molecular profiling and diagnostic performance of artificial intelligence-assisted multiplex PCR testing in women with bacterial vaginosis: a single-center experience.

BACKGROUND: Bacterial vaginosis (BV) is a most common microbiological syndrome. The use of molecular methods, such as multiplex real-time PCR (mPCR) a...

Physiological data for affective computing in HRI with anthropomorphic service robots: the AFFECT-HRI data set.

In human-human and human-robot interaction, the counterpart influences the human's affective state. Contrary to humans, robots inherently cannot respo...

Exploring the impact of pathogenic microbiome in orthopedic diseases: machine learning and deep learning approaches.

Osteoporosis, arthritis, and fractures are examples of orthopedic illnesses that not only significantly impair patients' quality of life but also comp...

Identification of potential cell death-related biomarkers for diagnosis and treatment of osteoporosis.

BACKGROUND: This study aimed to identify potential biomarkers for the diagnosis and treatment of osteoporosis (OP).

BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification.

The accurate classification of non-coding RNA (ncRNA) sequences is pivotal for advanced non-coding genome annotation and analysis, a fundamental aspec...

Artificial intelligence insights into osteoporosis: assessing ChatGPT's information quality and readability.

UNLABELLED: Accessible, accurate information, and readability play crucial role in empowering individuals managing osteoporosis. This study showed tha...

Effect of different targets of goal-directed fluid therapy on intraoperative hypotension and fluid infusion in robot-assisted laparoscopic gynecological surgery: a randomized non-inferiority trial.

Carotid corrected flow time (FTc) and tidal volume challenge pulse pressure variation (VtPPV) are useful clinical parameters for assessing volume stat...

Improved Arterial Stiffness Indices 3 and 6 Months after Living-donor Renal Transplantation.

Arterial stiffness is a non-traditional risk factor of cardiovascular disease and may explain part of the excess cardiovascular risk in chronic kidney...

Deep learning model for personalized prediction of positive MRSA culture using time-series electronic health records.

Methicillin-resistant Staphylococcus aureus (MRSA) poses significant morbidity and mortality in hospitals. Rapid, accurate risk stratification of MRSA...

Deep learning-based harmonization of trabecular bone microstructures between high- and low-resolution CT imaging.

BACKGROUND: Osteoporosis is a bone disease related to increased bone loss and fracture-risk. The variability in bone strength is partially explained b...

A deep learning based holistic diagnosis system for immunohistochemistry interpretation and molecular subtyping.

BACKGROUND: Breast cancer in different molecular subtypes, which is determined by the overexpression rates of human epidermal growth factor receptor 2...

TCDformer: A transformer framework for non-stationary time series forecasting based on trend and change-point detection.

Although time series prediction models based on Transformer architecture have achieved significant advances, concerns have arisen regarding their perf...

Effect of robotic gait training on muscle and bone characteristics in spinal cord transected rats.

Osteoporosis and loss of muscle mass are secondary issues with spinal cord injury. Robotic gait training has provided evidence of increasing bone dens...

A multi-branch convolutional neural network for snoring detection based on audio.

Obstructive sleep apnea (OSA) is associated with various health complications, and snoring is a prominent characteristic of this disorder. Therefore, ...

Performance of Progressive Generations of GPT on an Exam Designed for Certifying Physicians as Certified Clinical Densitometrists.

BACKGROUND: Artificial intelligence (AI) large language models (LLMs) such as ChatGPT have demonstrated the ability to pass standardized exams. These ...