AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Motion

Showing 281 to 290 of 845 articles

Clear Filters

On-demand anchoring of wireless soft miniature robots on soft surfaces.

Proceedings of the National Academy of Sciences of the United States of America
Untethered soft miniature robots capable of accessing hard-to-reach regions can enable new, disruptive, and minimally invasive medical procedures. However, once the control input is removed, these robots easily move from their target location because...

SANE (Easy Gait Analysis System): Towards an AI-Assisted Automatic Gait-Analysis.

International journal of environmental research and public health
The gait cycle of humans may be influenced by a range of variables, including neurological, orthopedic, and pathological conditions. Thus, gait analysis has a broad variety of applications, including the diagnosis of neurological disorders, the study...

An End-to-End Human Abnormal Behavior Recognition Framework for Crowds With Mentally Disordered Individuals.

IEEE journal of biomedical and health informatics
Abnormal or violent behavior by people with mental disorders is common. When individuals with mental disorders exhibit abnormal behavior in public places, they may cause physical and mental harm to others as well as to themselves. Thus, it is necessa...

Real-Time People Re-Identification and Tracking for Autonomous Platforms Using a Trajectory Prediction-Based Approach.

Sensors (Basel, Switzerland)
Currently, the importance of autonomous operating devices is rising with the increasing number of applications that run on robotic platforms or self-driving cars. The context of social robotics assumes that robotic platforms operate autonomously in e...

TRACK: A New Method From a Re-Examination of Deep Architectures for Head Motion Prediction in 360 Videos.

IEEE transactions on pattern analysis and machine intelligence
We consider predicting the user's head motion in 360 videos, with 2 modalities only: the past user's positions and the video content (not knowing other users' traces). We make two main contributions. First, we re-examine existing deep-learning appro...

Deep learning-guided weighted averaging for signal dropout compensation in DWI of the liver.

Magnetic resonance in medicine
PURPOSE: To develop an algorithm for the retrospective correction of signal dropout artifacts in abdominal DWI resulting from cardiac motion.

Motion Estimation by Deep Learning in 2D Echocardiography: Synthetic Dataset and Validation.

IEEE transactions on medical imaging
Motion estimation in echocardiography plays an important role in the characterization of cardiac function, allowing the computation of myocardial deformation indices. However, there exist limitations in clinical practice, particularly with regard to ...

Artificial Neural Network Approach to Guarantee the Positioning Accuracy of Moving Robots by Using the Integration of IMU/UWB with Motion Capture System Data Fusion.

Sensors (Basel, Switzerland)
This study presents an effective artificial neural network (ANN) approach to combine measurements from inertial measurement units (IMUs) and time-of-flight (TOF) measurements from an ultra-wideband (UWB) system with OptiTrack Motion Capture System (O...

Discrete Missing Data Imputation Using Multilayer Perceptron and Momentum Gradient Descent.

Sensors (Basel, Switzerland)
Data are a strategic resource for industrial production, and an efficient data-mining process will increase productivity. However, there exist many missing values in data collected in real life due to various problems. Because the missing data may re...

A time motion study of manual versus artificial intelligence methods for wound assessment.

PloS one
OBJECTIVES: This time-motion study explored the amount of time clinicians spent on wound assessments in a real-world environment using wound assessment digital application utilizing Artificial Intelligence (AI) vs. manual methods. The study also aime...