AIMC Topic: Male

Clear Filters Showing 25341 to 25350 of 27433 articles

Predicting Sex-Specific Nonfatal Suicide Attempt Risk Using Machine Learning and Data From Danish National Registries.

American journal of epidemiology
Suicide attempts are a leading cause of injury globally. Accurate prediction of suicide attempts might offer opportunities for prevention. This case-cohort study used machine learning to examine sex-specific risk profiles for suicide attempts in Dani...

Machine learning-driven identification of early-life air toxic combinations associated with childhood asthma outcomes.

The Journal of clinical investigation
Air pollution is a well-known contributor to asthma. Air toxics are hazardous air pollutants that cause or may cause serious health effects. Although individual air toxics have been associated with asthma, only a limited number of studies have specif...

Artificial Neural Networks Predict 30-Day Mortality After Hip Fracture: Insights From Machine Learning.

The Journal of the American Academy of Orthopaedic Surgeons
OBJECTIVES: Accurately stratifying patients in the preoperative period according to mortality risk informs treatment considerations and guides adjustments to bundled reimbursements. We developed and compared three machine learning models to determine...

Automatic segmentation of paravertebral muscles in abdominal CT scan by U-Net: The application of data augmentation technique to increase the Jaccard ratio of deep learning.

Medicine
Sarcopenia, characterized by a decline of skeletal muscle mass, has emerged as an important prognostic factor for cancer patients. Trunk computed tomography (CT) is a commonly used modality for assessment of cancer disease extent and treatment outcom...

XOmiVAE: an interpretable deep learning model for cancer classification using high-dimensional omics data.

Briefings in bioinformatics
The lack of explainability is one of the most prominent disadvantages of deep learning applications in omics. This 'black box' problem can undermine the credibility and limit the practical implementation of biomedical deep learning models. Here we pr...

Yulong Li.

Neuron
In an interview with Neuron, Yulong Li discusses optical tool development and next steps to interrogate the whole brain. He further shares the importance of interdisciplinarity; how new tools for neural imaging, perturbation, and artificial intellige...