AIMC Topic: Humans

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Analysis of Drug Effects on iPSC Cardiomyocytes with Machine Learning.

Annals of biomedical engineering
Patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) offer an attractive experimental platform to investigate cardiac diseases and therapeutic outcome. In this study, iPSC-CMs were utilized to study their calcium transient...

Assessing the Scope and Predictors of Intentional Dose Non-adherence in Clinical Trials.

Therapeutic innovation & regulatory science
BACKGROUND: Although there is broad agreement that the accurate estimation of non-adherence rates in clinical trials is essential to determining the dose-response relationship, treatment safety and efficacy effects, no accurate estimates have ever be...

Variability in Plus Disease Identified Using a Deep Learning-Based Retinopathy of Prematurity Severity Scale.

Ophthalmology. Retina
PURPOSE: Retinopathy of prematurity is a leading cause of childhood blindness worldwide, but clinical diagnosis is subjective, which leads to treatment differences. Our goal was to determine objective differences in the diagnosis of plus disease betw...

Radiomics and deep learning in lung cancer.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Lung malignancies have been extensively characterized through radiomics and deep learning. By providing a three-dimensional characterization of the lesion, models based on radiomic features from computed tomography (CT) and positron-emission tomograp...

A novel vision-based real-time method for evaluating postural risk factors associated with musculoskeletal disorders.

Applied ergonomics
Real-time risk assessment for work-related musculoskeletal disorders (MSD) has been a challenging research problem. Previous methods such as using depth cameras suffered from limited visual range and wearable sensors could cause intrusiveness to the ...

BPBSAM: Body part-specific burn severity assessment model.

Burns : journal of the International Society for Burn Injuries
BACKGROUND AND OBJECTIVE: Burns are a serious health problem leading to several thousand deaths annually, and despite the growth of science and technology, automated burns diagnosis still remains a major challenge. Researchers have been exploring vis...

Grab-AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease.

Human brain mapping
Alzheimer's disease (AD) is associated with disruptions in brain activity and networks. However, there is substantial inconsistency among studies that have investigated functional brain alterations in AD; such contradictions have hindered efforts to ...

Deep Multi-Critic Network for accelerating Policy Learning in multi-agent environments.

Neural networks : the official journal of the International Neural Network Society
Humans live among other humans, not in isolation. Therefore, the ability to learn and behave in multi-agent environments is essential for any autonomous system that intends to interact with people. Due to the presence of multiple simultaneous learner...

What are the main patient safety concerns of healthcare stakeholders: a mixed-method study of Web-based text.

International journal of medical informatics
OBJECTIVES: Various healthcare stakeholders define quality of care in different ways. Public policy could advocate all these concerns. This study was conducted to identify the main themes on patient safety of stakeholders expressed before and after t...

Using artificial neural networks to predict impingement and dislocation in total hip arthroplasty.

Computer methods in biomechanics and biomedical engineering
Dislocation after total hip arthroplasty (THA) remains a major issue and an important post-surgical complication. Impingement and subsequent dislocation are influenced by the design (head size) and position (anteversion and abduction angles) of the a...