Endocrinology

Menopause

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

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Distilling knowledge from graph neural networks trained on cell graphs to non-neural student models.

The development and refinement of artificial intelligence (AI) and machine learning algorithms have ...

Pharmacovigilance in Cell and Gene Therapy: Evolving Challenges in Risk Management and Long-Term Follow-Up.

Cell and gene therapies, including CAR T-cells, CRISPR-based genome editing, and next-generation vir...

Non-coding genetic elements of lung cancer identified using whole genome sequencing in 13,722 Chinese.

A substantial portion of lung cancer-associated genetic elements in East Asian populations remains u...

Application of causal forest double machine learning (DML) approach to assess tuberculosis preventive therapy's impact on ART adherence.

Adherence to antiretroviral therapy (ART) is critical for HIV treatment success, yet the impact of t...

Non-invasive prediction of the secondary enucleation risk in uveal melanoma based on pretreatment CT and MRI prior to stereotactic radiotherapy.

PURPOSE: The aim of this study was to develop a radiomic model to non-invasively predict the risk of...

A Deep Learning Model to Detect Acute MCA Occlusion on High Resolution Non-Contrast Head CT.

BACKGROUND AND PURPOSE: To assess the feasibility and accuracy of a deep learning (DL) model to iden...

An Anisotropic Cross-View Texture Transfer with Multi-Reference Non-Local Attention for CT Slice Interpolation.

Computed tomography (CT) is one of the most widely used non-invasive imaging modalities for medical ...

Advanced non-destructive detection of peanut adulteration in ground roasted hazelnut using FT-NIR spectroscopy and machine learning.

Hazelnut adulteration with ground peanut is a severe health and economic problem. In this study, Fou...

A Machine Learning-Based Modeling Approach for Dye Removal Using Modified Natural Adsorbents.

This study used machine learning models to investigate the potential of biosorbents derived from nat...

NSPLformer: exploration of non-stationary progressively learning model for time series prediction.

Although Transformers perform well in time series prediction, they struggle when dealing with real-w...

Non-invasive acoustic classification of adult asthma using an XGBoost model with vocal biomarkers.

Traditional diagnostic methods for asthma, a widespread chronic respiratory illness, are often limit...

Adaptive resetting for informed search strategies and the design of non-equilibrium steady-states.

Stochastic resetting, the procedure of stopping and re-initializing random processes, has recently e...

Limits on the computational expressivity of non-equilibrium biophysical processes.

Many biological decision-making tasks require classifying high-dimensional chemical states. The biop...

Clinical correlates of errors in machine-learning diagnostic model of autism spectrum disorder: Impact of sample cohorts.

Machine-learning models can assist in diagnosing autism but have biases. We examines the correlates ...

Bioinformatics analysis of Rho-signal transduction genes in postmenopausal osteoporosis and periodontitis.

Postmenopausal osteoporosis (PMOP) increases the risk of periodontitis (PD), yet the shared mechanis...

Recent Advances in Non-Planar Collectors for Melt Electrowriting (MEW): Creating Physiologically Relevant Scaffold Structures for Tissue Engineering.

Melt electrowriting (MEW) is an advanced additive manufacturing technique that offers unprecedented ...

NUPES : Non-Uniform Post-Training Quantization via Power Exponent Search.

Deep neural network (DNN) deployment has been confined to larger hardware devices due to their expen...

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