AIMC Topic: Humans

Clear Filters Showing 11501 to 11510 of 95995 articles

Comparison of predictive models for knee pain and analysis of individual and physical activity variables using interpretable machine learning.

The Knee
BACKGROUND: Knee pain is associated with not only individual factors such as age and obesity but also physical activity factors such as occupational activities and exercise, which has a significant impact on the lives of adults and the elderly.

Overview of artificial intelligence in hand surgery.

The Journal of hand surgery, European volume
Artificial intelligence has evolved significantly since its inception, becoming a powerful tool in medicine. This paper provides an overview of the core principles, applications and future directions of artificial intelligence in hand surgery. Artifi...

Enhancing diagnosis prediction with adaptive disease representation learning.

Artificial intelligence in medicine
Diagnosis prediction predicts which diseases a patient is most likely to suffer from in the future based on their historical electronic health records. The time series model can better capture the temporal progression relationship of patient diseases...

DRExplainer: Quantifiable interpretability in drug response prediction with directed graph convolutional network.

Artificial intelligence in medicine
Predicting the response of a cancer cell line to a therapeutic drug is pivotal for personalized medicine. Despite numerous deep learning methods that have been developed for drug response prediction, integrating diverse information about biological e...

Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine.

Epilepsy & behavior : E&B
Artificial intelligence (AI) is revolutionizing epilepsy care by advancing seizure detection, enhancing diagnostic precision, and enabling personalized treatment. Machine learning and deep learning technologies improve seizure monitoring, automate EE...

Modeling crash avoidance behaviors in vehicle-pedestrian near-miss scenarios: Curvilinear time-to-collision and Mamba-driven deep reinforcement learning.

Accident; analysis and prevention
Interactions between vehicle-pedestrian at intersections often lead to safety-critical situations. This study aims to model the crash avoidance behaviors of vehicles during interactions with pedestrians in near-miss scenarios, contributing to the dev...

Circadian rhythm modulation in heart rate variability as potential biomarkers for major depressive disorder: A machine learning approach.

Journal of psychiatric research
Major depressive disorder (MDD) is associated with reduced heart rate variability (HRV), but its link to circadian rhythm modulation (CRM) of HRV is unclear. Given that depression disrupts circadian rhythms, assessing HRV fluctuations may better capt...

Initial study of verbal and nonverbal communication training through the collaborative operation of a humanoid robot for individuals with autism spectrum disorder.

Asian journal of psychiatry
Individuals with autism spectrum disorder (ASD) experience difficulties in both verbal and nonverbal communication. Collaborative work allows them to use and develop their nonverbal communication abilities. Therefore, we developed a collaborative wor...

Prediction of clinical risk factors in pregnancy using optimized neural network scheme.

Placenta
Women should be aware of prenancy related health issues. A user-friendly model is developed in which the patients can use as well as clinicians to determine the risks associated with foetal development inside the womb, birth weight, whose effects are...