Menopause

Hybrid-YOLOv5 for object detection of non-ferrous metals in end-of-life vehicles.

In recent years, the detection of non-ferrous metals in end-of-life vehicles (ELVs) has become essen...

Data-driven approach to the deep learning of the dynamics of a non-integrable Hamiltonian system.

The dynamics of non-integrable Hamiltonian systems, described by area-preserving mappings, are regul...

Discovery of novel cathepsin K inhibitors for osteoporosis treatment using a deep learning-based strategy.

BACKGROUND: Cathepsin K (CTSK), a cysteine protease of the papain family, exhibits high expression i...

LncRNAs regulates cell death in osteosarcoma.

Despite improvements, prognosis in osteosarcoma patients remains poor, making it essential to identi...

Predicting boiling heat flux, heat transfer coefficient, and regimes Non-intrusively using external acoustics and deep learning.

Accurate monitoring of boiling heat transfer is critical for the safety and efficiency of high energ...

A Machine Learning Approach to Molecular Initiating Event Prediction Using High-Throughput Transcriptomic Chemical Screening Data.

Improved scalability of high-throughput RNA-sequencing technologies has contributed to their propose...

Protocol for a randomized and a non-randomized controlled trial testing Daily Growth: a personalised 'ecological momentary intervention' parenting app for parents and carers of children aged 2-5 years.

BACKGROUND: Children's ability to regulate their emotions is a critical protective factor for early ...

AmpHGT: expanding prediction of antimicrobial activity in peptides containing non-canonical amino acids using multi-view constrained heterogeneous graph transformer.

BACKGROUND: Antimicrobial peptide (AMP) prediction has been extensively studied in recent years. How...

Deep learning radiomics and mediastinal adipose tissue-based nomogram for preoperative prediction of postoperative‌ brain metastasis risk in non-small cell lung cancer.

MRI radiomics model for predicting tumor immune microenvironment types and efficacy of anti-PD-1/PD-L1 therapy in hepatocellular carcinoma.

BACKGROUND: To improve the prediction of immune checkpoint inhibitors (ICIs) efficacy in hepatocellu...

Chimeric mis-annotations of genes remain pervasive in eukaryotic non-model organisms.

BACKGROUND: Accurate annotation of protein-coding genes is critical for genome analysis in non-model...

Computed tomography-based radiomics predicts prognostic and treatment-related levels of immune infiltration in the immune microenvironment of clear cell renal cell carcinoma.

OBJECTIVES: The composition of the tumour microenvironment is very complex, and measuring the extent...

Radiomics and machine learning for osteoporosis detection using abdominal computed tomography: a retrospective multicenter study.

OBJECTIVE: This study aimed to develop and validate a predictive model to detect osteoporosis using ...

Formulation of low temperature mixed mode crack propagation behavior of crumb rubber modified HMA using artificial intelligence.

Determining mixed mode fracture parameters asphalt concrete mixtures remains an engineering challeng...

Evaluation of MRI-based synthetic CT for lumbar degenerative disease: a comparison with CT.

Patients with lumbar degenerative disease typically undergo preoperative MRI combined with CT scans,...

Deep learning-driven drug response prediction and mechanistic insights in cancer genomics.

In the field of cancer therapy, the diversity and heterogeneity of cancer genomes in clinical patien...

Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides.

Accurate risk stratification is critical for guiding treatment decisions in early breast cancer. We ...

Decades of Scientific Data and Global Media Reporting on Complications in Non-surgical Aesthetic Treatments for a Transparent Safety Profile: Kissing Snow White Awake.

INTRODUCTION: Non-surgical aesthetic treatments (NSATs) have gained significant traction over the pa...

Screening and validation of long non-coding RNAs associated with colorectal cancer based on random forest and LASSO regression algorithm.

OBJECTIVE: Colorectal cancer (CRC) ranks as the third most prevalent contributor to global disease b...

Driving Multifunctional Nanomedicine Design for Non-Inflammatory Tumor Therapy with Integrated Machine Learning and Density Functional Theory.

Due to the promotive role of inflammation in tumor progression, designing multifunctional nanomedici...

ERRα-Predictor: A Framework of Ensemble Models for Prediction of ERRα Binders, Antagonists, and Agonists Using Artificial Intelligence.

Estrogen-related receptor α (ERRα) is considered a promising target for the treatment of cancer and ...