AIMC Topic: Humans

Clear Filters Showing 32961 to 32970 of 95995 articles

Deep learning assisted measurement of echocardiographic left heart parameters: improvement in interobserver variability and workflow efficiency.

The international journal of cardiovascular imaging
Machine learning techniques designed to recognize views and perform measurements are increasingly used to address the need for automation of the interpretation of echocardiographic images. The current study was designed to determine whether a recentl...

Impact of preferred surgical modality on surgeon wellness: a survey of workload, physical pain/discomfort, and neuromusculoskeletal disorders.

Surgical endoscopy
BACKGROUND: We compared surgeons' workload, physical discomfort, and neuromusculoskeletal disorders (NMSDs) across four surgical modalities: endoscopic, laparoscopic, open, and robot-assisted (da Vinci Surgical Systems).

Feasibility, safety, and efficacy of task-oriented mirrored robotic training on upper-limb functions and activities of daily living in subacute poststroke patients: a pilot study.

European journal of physical and rehabilitation medicine
BACKGROUND: Robotic training with high repetitions facilitates upper-limb movements but provides fewer benefits for activities of daily living. Integrating activities of daily living training tasks and mirror therapy into a robot may enhance the func...

Magnetic Soft Robot for Minimally Invasive Urethral Catheter Biofilm Eradication.

ACS nano
Catheter-related biofilm infection remains the main problem for millions of people annually, affecting morbidity, mortality, and quality of life. Despite the recent advances in the prevention of biofilm formation, alternative methods for biofilm prev...

Assessment of landmark detection in cephalometric radiographs with different conditions of brightness and contrast using the an artificial intelligence software.

Dento maxillo facial radiology
OBJECTIVES: To evaluate the reliability and reproducibility of an artificial intelligence (AI) software in identifying cephalometric points on lateral cephalometric radiographs considering four settings of brightness and contrast.

Depressive Disorder Recognition Based on Frontal EEG Signals and Deep Learning.

Sensors (Basel, Switzerland)
Depressive disorder (DD) has become one of the most common mental diseases, seriously endangering both the affected person's psychological and physical health. Nowadays, a DD diagnosis mainly relies on the experience of clinical psychiatrists and sub...

Cholesterol Levels, Hormone Replacement Therapy, and Incident Dementia among Older Adult Women.

Nutrients
Previous studies revealed that hormone replacement therapy (HRT) probably has a protective effect for preventing dementia in post-menopausal women. However, the results were still controversial. The association between cholesterol levels and incident...

Real-time dual prediction of intradialytic hypotension and hypertension using an explainable deep learning model.

Scientific reports
Both intradialytic hypotension (IDH) and hypertension (IDHTN) are associated with poor outcomes in hemodialysis patients, but a model predicting dual outcomes in real-time has never been developed. Herein, we developed an explainable deep learning mo...

Rapid automated 3-D pose estimation of larval zebrafish using a physical model-trained neural network.

PLoS computational biology
Quantitative ethology requires an accurate estimation of an organism's postural dynamics in three dimensions plus time. Technological progress over the last decade has made animal pose estimation in challenging scenarios possible with unprecedented d...

Machine learning: a powerful tool for identifying key microbial agents associated with specific cancer types.

PeerJ
Machine learning (ML) includes a broad class of computer programs that improve with experience and shows unique strengths in performing tasks such as clustering, classification and regression. Over the past decade, microbial communities have been imp...