Endocrinology

Menopause

Latest AI and machine learning research in menopause for healthcare professionals.

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Heart patient health monitoring system using invasive and non-invasive measurement.

The abnormal heart conduction, known as arrhythmia, can contribute to cardiac diseases that carry th...

Integrated machine learning-based virtual screening and biological evaluation for identification of potential inhibitors against cathepsin K.

Cathepsin K is a type of cysteine proteinase that is primarily expressed in osteoclasts and has a ke...

Predicting osteoporosis from kidney-ureter-bladder radiographs utilizing deep convolutional neural networks.

Osteoporosis is a common condition that can lead to fractures, mobility issues, and death. Although ...

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

BACKGROUND: Osteoporosis is becoming more common worldwide, imposing a substantial burden on individ...

DEMA: A Deep Learning-Enabled Model for Non-Invasive Human Vital Signs Monitoring Based on Optical Fiber Sensing.

Optical fiber sensors are extensively employed for their unique merits, such as small size, being li...

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. W...

Prediction models for postoperative recurrence of non-lactating mastitis based on machine learning.

OBJECTIVES: This study aims to build a machine learning (ML) model to predict the recurrence probabi...

Solving the non-submodular network collapse problems via Decision Transformer.

Given a graph G, the network collapse problem (NCP) selects a vertex subset S of minimum cardinality...

Deep learning for discrimination of active and inactive lesions in multiple sclerosis using non-contrast FLAIR MRI: A multicenter study.

BACKGROUND: Within the domain of multiple sclerosis (MS), the precise discrimination between active ...

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 ...

Completion of Pembrolizumab in Advanced Non-Small Cell Lung Cancer-Real World Outcomes After Two Years of Therapy (COPILOT).

BACKGROUND: Seminal trials with first-line pembrolizumab for metastatic non-small cell lung cancer (...

Ballistocardial Signal-Based Personal Identification Using Deep Learning for the Non-Invasive and Non-Restrictive Monitoring of Vital Signs.

Owing to accelerated societal aging, the prevalence of elderly individuals experiencing solitary or ...

Mixing neural networks, continuation and symbolic computation to solve parametric systems of non linear equations.

We consider a square non linear parametric equations system F(P,X) = 0 which is constituted of n non...

Hybrid non-animal modeling: A mechanistic approach to predict chemical hepatotoxicity.

Developing mechanistic non-animal testing methods based on the adverse outcome pathway (AOP) framewo...

Non-local degradation modeling for spatially adaptive single image super-resolution.

Existing methods for single image super-resolution (SISR) model the blur kernel as spatially invaria...

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 a...

Non-Invasive Biosensing for Healthcare Using Artificial Intelligence: A Semi-Systematic Review.

The rapid development of biosensing technologies together with the advent of deep learning has marke...

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