AIMC Topic: Humans

Clear Filters Showing 24961 to 24970 of 95995 articles

Human Joint Angle Estimation Using Deep Learning-Based Three-Dimensional Human Pose Estimation for Application in a Real Environment.

Sensors (Basel, Switzerland)
Human pose estimation (HPE) is a technique used in computer vision and artificial intelligence to detect and track human body parts and poses using images or videos. Widely used in augmented reality, animation, fitness applications, and surveillance,...

Real-Time Tracking Data and Machine Learning Approaches for Mapping Pedestrian Walking Behavior: A Case Study at the University of Moratuwa.

Sensors (Basel, Switzerland)
The growing urban population and traffic congestion underline the importance of building pedestrian-friendly environments to encourage walking as a preferred mode of transportation. However, a major challenge remains, which is the absence of such ped...

Exploring Tau Fibril-Disaggregating and Antioxidating Molecules Binding to Membrane-Bound Amyloid Oligomers Using Machine Learning-Enhanced Docking and Molecular Dynamics.

Molecules (Basel, Switzerland)
Intracellular tau fibrils are sources of neurotoxicity and oxidative stress in Alzheimer's. Current drug discovery efforts have focused on molecules with tau fibril disaggregation and antioxidation functions. However, recent studies suggest that memb...

A Machine Learning Approach to Identify Key Residues Involved in Protein-Protein Interactions Exemplified with SARS-CoV-2 Variants.

International journal of molecular sciences
Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the human angiotensin-converting enzyme 2 (ACE2). The frequent mutatio...

Evolution of Chatbots in Nursing Education: Narrative Review.

JMIR medical education
BACKGROUND: The integration of chatbots in nursing education is a rapidly evolving area with potential transformative impacts. This narrative review aims to synthesize and analyze the existing literature on chatbots in nursing education.

Quantitative prediction of postpartum hemorrhage in cesarean section on machine learning.

BMC medical informatics and decision making
BACKGROUND: Cesarean section-induced postpartum hemorrhage (PPH) potentially causes anemia and hypovolemic shock in pregnant women. Hence, it is helpful for obstetricians and anesthesiologists to prepare pre-emptive prevention when predicting PPH occ...