Endocrinology

Menopause

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

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Automated Fast Prediction of Bone Mineral Density From Low-dose Computed Tomography.

BACKGROUND: Low-dose chest CT (LDCT) is commonly employed for the early screening of lung cancer. Ho...

Robust vs. Non-robust radiomic features: the quest for optimal machine learning models using phantom and clinical studies.

PURPOSE: This study aimed to select robust features against lung motion in a phantom study and use t...

Deep learning-based evaluation of panoramic radiographs for osteoporosis screening: a systematic review and meta-analysis.

BACKGROUND: Osteoporosis is a complex condition that drives research into its causes, diagnosis, tre...

PrOsteoporosis: predicting osteoporosis risk using NHANES data and machine learning approach.

OBJECTIVES: Osteoporosis, prevalent among the elderly population, is primarily diagnosed through bon...

Can some algorithms of machine learning identify osteoporosis patients after training and testing some clinical information about patients?

OBJECTIVE: This study was designed to establish a diagnostic model for osteoporosis by collecting cl...

Using statistical modelling and machine learning in detecting bone properties: A systematic review protocol.

INTRODUCTION: Osteoporosis, a common condition characterised by decreased bone mass and microarchite...

Global Cross-Entropy Loss for Deep Face Recognition.

Contemporary deep face recognition techniques predominantly utilize the Softmax loss function, desig...

Non-Face-to-Face Services in Neurologic Care.

Neurologists in ambulatory settings struggle with low appointment availability and increased work re...

An explainable non-invasive hybrid machine learning framework for accurate prediction of thyroid-stimulating hormone levels.

Machine learning models, including thyroid biomarkers, are increasingly utilized in healthcare for b...

Harnessing Artificial Intelligence for Precision Diagnosis and Treatment of Triple Negative Breast Cancer.

Triple-Negative Breast Cancer (TNBC) is a highly aggressive subtype of breast cancer (BC) characteri...

Transcriptome analysis reveals the potential role of neural factor EN1 for long-terms survival in estrogen receptor-independent breast cancer.

Breast cancer patients with estrogen receptor-negative (ERneg) status, encompassing triple negative ...

Ensemble-learning approach improves fracture prediction using genomic and phenotypic data.

UNLABELLED: This study presents an innovative ensemble machine learning model integrating genomic an...

Machine Learning Predicts Non-Preferred and Preferred Vertebrate Hosts of Tsetse Flies (Glossina spp.) Based on Skin Volatile Emission Profiles.

Tsetse fly vectors of African trypanosomosis preferentially feed on certain vertebrates largely dete...

Accurate phenotyping of luminal A breast cancer in magnetic resonance imaging: A new 3D CNN approach.

Breast cancer (BC) remains a predominant and deadly cancer in women worldwide. By 2040, projections ...

EVlncRNA-net: A dual-channel deep learning approach for accurate prediction of experimentally validated lncRNAs.

Long non-coding RNAs (lncRNAs) play key roles in numerous biological processes and are associated wi...

HybrIK-X: Hybrid Analytical-Neural Inverse Kinematics for Whole-Body Mesh Recovery.

Recovering whole-body mesh by inferring the abstract pose and shape parameters from visual content c...

Effectiveness of Generative Artificial Intelligence-Driven Responses to Patient Concerns in Long-Term Opioid Therapy: Cross-Model Assessment.

While long-term opioid therapy is a widely utilized strategy for managing chronic pain, many patien...

Temporal Contrastive Learning through implicit non-equilibrium memory.

The backpropagation method has enabled transformative uses of neural networks. Alternatively, for en...

Deep learning based image enhancement for dynamic non-Cartesian MRI: Application to "silent" fMRI.

Radial based non-Cartesian sequences may be used for silent functional MRI examinations particularly...

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