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Physical Examination

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Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study.

The Lancet. Digital health
BACKGROUND: Most patients who have heart failure with a reduced ejection fraction, when left ventricular ejection fraction (LVEF) is 40% or lower, are diagnosed in hospital. This is despite previous presentations to primary care with symptoms. We aim...

Machine learning-aided risk prediction for metabolic syndrome based on 3 years study.

Scientific reports
Metabolic syndrome (MetS) is a group of physiological states of metabolic disorders, which may increase the risk of diabetes, cardiovascular and other diseases. Therefore, it is of great significance to predict the onset of MetS and the corresponding...

Eliminating CT radiation for clinical PET examination using deep learning.

European journal of radiology
Clinical PET/CT examinations rely on CT modality for anatomical localization and attenuation correction of the PET data. However, the use of CT significantly increases the risk of ionizing radiation exposure for patients. We propose a deep learning f...

Sensing, Actuating, and Interacting Through Passive Body Dynamics: A Framework for Soft Robotic Hand Design.

Soft robotics
Robotic hands have long strived to reach the performance of human hands. The physical complexity and extraordinary capabilities of the human hand, in terms of sensing, actuation, and cognitive abilities, make achieving this goal challenging. At the h...

A Geometric Kinematic Model for Flexible Voxel-Based Robots.

Soft robotics
Voxel-based structures provide a modular, mechanically flexible periodic lattice, which can be used as a soft robot through internal deformations. To engage these structures for robotic tasks, we use a finite element method to characterize the motion...

A correlation-based feature analysis of physical examination indicators can help predict the overall underlying health status using machine learning.

Scientific reports
As a systematic investigation of the correlations between physical examination indicators (PEIs) is lacking, most PEIs are currently independently used for disease warning. This results in the general physical examination having limited diagnostic va...

Predicting stress, strain and deformation fields in materials and structures with graph neural networks.

Scientific reports
Developing accurate yet fast computational tools to simulate complex physical phenomena is a long-standing problem. Recent advances in machine learning have revolutionized the way simulations are approached, shifting from a purely physics- to AI-base...

Modeling Based on a Two-Step Parameter Identification Strategy for Liquid Crystal Elastomer Actuator Considering Dynamic Phase Transition Process.

IEEE transactions on cybernetics
Liquid crystal elastomer (LCE) is a promising candidate for actuation in light-driven soft robot applications. Due to the fact that LCE has complex hysteretic nonlinearities, which are highly dependent on the environment, modeling of actuators made o...

Artificial Intelligence and Anorectal Manometry: Automatic Detection and Differentiation of Anorectal Motility Patterns-A Proof-of-Concept Study.

Clinical and translational gastroenterology
INTRODUCTION: Anorectal manometry (ARM) is the gold standard for the evaluation of anorectal functional disorders, prevalent in the population. Nevertheless, the accessibility to this examination is limited, and the complexity of data analysis and re...