AIMC Topic: Male

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Upper gastrointestinal haemorrhage patients' survival: A causal inference and prediction study.

European journal of clinical investigation
BACKGROUND: Upper gastrointestinal (GI) bleeding is a common medical emergency. This study aimed to develop models to predict critically ill patients with upper GI bleeding in-hospital and 30-day survival, identify the correlation factor and infer th...

Prediction of suicidal ideation among preadolescent children with machine learning models: A longitudinal study.

Journal of affective disorders
BACKGROUND: Machine learning (ML) has been widely used to predict suicidal ideation (SI) in adolescents and adults. Nevertheless, studies of accurate and efficient models of SI prediction with preadolescent children are still needed because SI is sur...

Initial Experience in Urological Surgery with a Novel Robotic Technology: Magnetic-Assisted Robotic Surgery in Urology.

Journal of endourology
Magnetic-assisted robotic surgery (MARS) has been developed to maximize patient benefits of minimally invasive surgery while enhancing surgeon control and visualization. MARS platform (Levita Magnetics) comprises two robotic arms that provide contro...

Deep learning models reveal replicable, generalizable, and behaviorally relevant sex differences in human functional brain organization.

Proceedings of the National Academy of Sciences of the United States of America
Sex plays a crucial role in human brain development, aging, and the manifestation of psychiatric and neurological disorders. However, our understanding of sex differences in human functional brain organization and their behavioral consequences has be...

Ranking and filtering of neuropathology features in the machine learning evaluation of dementia studies.

Brain pathology (Zurich, Switzerland)
Early diagnosis of dementia diseases, such as Alzheimer's disease, is difficult because of the time and resources needed to perform neuropsychological and pathological assessments. Given the increasing use of machine learning methods to evaluate neur...

A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development.

Environmental research
BACKGROUND: Most previous research on the environmental epidemiology of childhood atopic eczema, rhinitis and wheeze is limited in the scope of risk factors studied. Our study adopted a machine learning approach to explore the role of the exposome st...

Usefulness of pituitary high-resolution 3D MRI with deep-learning-based reconstruction for perioperative evaluation of pituitary adenomas.

Neuroradiology
PURPOSE: To evaluate the diagnostic value of T1-weighted 3D fast spin-echo sequence (CUBE) with deep learning-based reconstruction (DLR) for depiction of pituitary adenoma and parasellar regions on contrast-enhanced MRI.

Real-Time Tissue Classification Using a Novel Optical Needle Probe for Biopsy.

Applied spectroscopy
Core needle biopsy is a part of the histopathological process, which is required for cancerous tissue examination. The most common method to guide the needle inside of the body is ultrasound screening, which in greater part is also the only guidance ...

Artificial Intelligence Versus Human Focus Group Rating of Facial Attractiveness.

Facial plastic surgery & aesthetic medicine
Many open-access artificial intelligence (AI)-based websites that rate facial attractiveness are available, but none have been compared with human focus group outcomes. To compare human and AI-based websites scoring of facial attractiveness of adul...

Timing matters for accurate identification of the epileptogenic zone.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Interictal biomarkers of the epileptogenic zone (EZ) and their use in machine learning models open promising avenues for improvement of epilepsy surgery evaluation. Currently, most studies restrict their analysis to short segments of intra...