AIMC Topic: Wounds and Injuries

Clear Filters Showing 91 to 100 of 160 articles

Person transfer assist systems: a literature review.

Disability and rehabilitation. Assistive technology
OBJECTIVE: Novel developments in the robotics field have produced systems that can support person wheelchair transfers, maximize safety and reduce caregiver burden. The purpose of this study was to identify and describe these systems, their usability...

Modelling disease risk for amyloid A (AA) amyloidosis in non-human primates using machine learning.

Amyloid : the international journal of experimental and clinical investigation : the official journal of the International Society of Amyloidosis
Amyloid A (AA) amyloidosis is found in humans and non-human primates, but quantifying disease risk prior to clinical symptoms is challenging. We applied machine learning to identify the best predictors of amyloidosis in rhesus macaques from availabl...

Dynamic multi-outcome prediction after injury: Applying adaptive machine learning for precision medicine in trauma.

PloS one
OBJECTIVE: Machine learning techniques have demonstrated superior discrimination compared to conventional statistical approaches in predicting trauma death. The objective of this study is to evaluate whether machine learning algorithms can be used to...

The trauma severity model: An ensemble machine learning approach to risk prediction.

Computers in biology and medicine
Statistical theory indicates that a flexible model can attain a lower generalization error than an inflexible model, provided that the setting is appropriate. This is highly relevant for mortality risk prediction with trauma patients, as researchers ...

Identification of a closed cutaneous injury after mechanical trauma caused by collision.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
PURPOSE: Robotics has evolved rapidly in terms of mechanical design and control in the past few years. Collaborative robots that have direct contact with humans are being introduced in various fields, including industrial and medical services. Becaus...

Comparison of artificial neural network and logistic regression models for prediction of outcomes in trauma patients: A systematic review and meta-analysis.

Injury
BACKGROUND: Currently, two models of artificial neural network (ANN) and logistic regression (LR) are known as models that extensively used in medical sciences. The aim of this study was to compare the ANN and LR models in prediction of Health-relate...

A Random Forest-Assisted Evolutionary Algorithm for Data-Driven Constrained Multiobjective Combinatorial Optimization of Trauma Systems.

IEEE transactions on cybernetics
Many real-world optimization problems can be solved by using the data-driven approach only, simply because no analytic objective functions are available for evaluating candidate solutions. In this paper, we address a class of expensive data-driven co...

Demographic and Symptomatic Features of Voice Disorders and Their Potential Application in Classification Using Machine Learning Algorithms.

Folia phoniatrica et logopaedica : official organ of the International Association of Logopedics and Phoniatrics (IALP)
BACKGROUND: Studies have used questionnaires of dysphonic symptoms to screen voice disorders. This study investigated whether the differential presentation of demographic and symptomatic features can be applied to computerized classification.

A Composite Model of Wound Segmentation Based on Traditional Methods and Deep Neural Networks.

Computational intelligence and neuroscience
Wound segmentation plays an important supporting role in the wound observation and wound healing. Current methods of image segmentation include those based on traditional process of image and those based on deep neural networks. The traditional metho...