Endocrinology

Menopause

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

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Integrative network and computational toxicology reveal the molecular mechanisms in PFOA-induced spermatogenic disorder.

Perfluorooctanoic acid (PFOA), a widely used industrial chemical, poses significant environmental an...

MRI-based multimodal AI model enables prediction of recurrence risk and adjuvant therapy in breast cancer.

Timely intervention and improved prognosis for breast cancer patients rely on early metastasis risk ...

Enhancing osteoporosis risk prediction using machine learning: A holistic approach integrating biomarkers and clinical data.

Osteoporosis (OP) affects approximately 18 % of the global population, with osteoporosis-associated ...

NFR-EDL: Non-linear fuzzy rank-based ensemble deep learning for accurate diagnosis of oral and dental diseases using RGB color photography.

BACKGROUND: Oral health plays a vital role in our daily lives, affecting essential activities like e...

A novel artificial intelligence-based methodology to predict non-specific response to treatment.

Non-specific response to treatment (NSRT) is the primary contributor to the failure of randomized cl...

Enhanced non-invasive machine learning approach for early colorectal cancer detection: Predictive modeling and validation in a Jordanian cohort.

BACKGROUND: Colorectal cancer (CRC) ranks as the third most prevalent cancer worldwide, posing signi...

Atten-Nonlocal Unet: Attention and Non-local Unet for medical image segmentation.

The convolutional neural network(CNN)-based models have emerged as the predominant approach for medi...

Non-invasive diagnosis of lung diseases via multimodal feature extraction from breathing audio and chest dynamics.

Early and accurate diagnosis of lung diseases is crucial for effective treatment. While traditional ...

Accuracy of robot and template systems in implant cases: A retrospective non-randomized controlled study.

OBJECTIVES: This clinical study aimed to compare the accuracy of implant placement obtained using a ...

A Physics-Integrated Deep Learning Approach for Patient-Specific Non-Newtonian Blood Viscosity Assessment using PPG.

BACKGROUND AND OBJECTIVE: The aim of this study is to extract a patient-specific viscosity equation ...

GVM-Net: A GNN-Based Vessel Matching Network for 2D/3D Non-Rigid Coronary Artery Registration.

The registration of coronary artery structures from preoperative coronary computed tomography angiog...

A deep learning model for prediction of lysine crotonylation sites by fusing multi-features based on multi-head self-attention mechanism.

Lysine crotonylation (Kcr) is an important post-translational modification, which is present in both...

Comparative Analysis of Feature Extraction Methods and Machine Learning Models for Predicting Osteoporosis Prevalence.

This study systematically examined the impact of three feature selection techniques (Boruta, Extreme...

Classifying athletes and non-athletes by differences in spontaneous brain activity: a machine learning and fMRI study.

Different types of sports training can induce distinct changes in brain activity and function; howev...

Large-Scale Non-Adiabatic Dynamics Simulation Based on Machine Learning Hamiltonian and Force Field: The Case of Charge Transport in Monolayer MoS.

We present an efficient and reliable large-scale non-adiabatic dynamics simulation method based on m...

Molecular Insights into the Binding of Organophosphate Flame Retardant Key Metabolites with Mineralocorticoid and Estrogen Receptors.

Flame retardants (FR) encompass a wide range of chemicals designed to inhibit and reduce the spread ...

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