AIMC Topic: Humans

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Assessing Data Quality in Heterogeneous Health Care Integration: Simulation Study of the AIDAVA Framework.

JMIR medical informatics
BACKGROUND: Integrated health data are foundational for secondary use, research, and policymaking. However, data quality issues-such as missing values and inconsistencies-are common due to the heterogeneity of health data sources. Existing frameworks...

Detection of Polyphonic Alarm Sounds From Medical Devices Using Frequency-Enhanced Deep Learning: Simulation Study.

JMIR medical informatics
BACKGROUND: Although an increasing number of bedside medical devices are equipped with wireless connections for reliable notifications, many nonnetworked devices remain effective at detecting abnormal patient conditions and alerting medical staff thr...

Novel heterozygous mutation in KMT2B causing an unusual phenotypic presentation: a comprehensive clinical and bioinformatic analysis.

Molecular biology reports
BACKGROUND: KMT2B-related dystonia is a childhood-onset movement disorder. This study investigated a novel KMT2B gene variant using whole exome sequencing (WES) and bioinformatics analysis, and expanded the known clinical spectrum of KMT2B-related dy...

AI-Assisted 3D diagnosis of impacted maxillary canines: A validation study.

Clinical oral investigations
INTRODUCTION: This study aimed to validate an artificial intelligence (AI)-based automated image analysis for three-dimensional (3D) characterization of impacted canine position. In addition, it compared clinical treatment plans developed using conve...

A matrix stiffness gene signature identifies SLC20A1 as a novel mechano-immunological checkpoint enabling synergistic immunotherapy in pancreatic ductal adenocarcinoma.

Cancer immunology, immunotherapy : CII
Matrix stiffness is a defining feature of pancreatic ductal adenocarcinoma (PDAC) and drives malignant progression through mechanisms that remain poorly understood. Using an ensemble machine learning approach, we integrated multiomics data from 886 p...

Multi-stage variational autoencoders for hierarchical molecular generation and activity optimization.

Journal of computer-aided molecular design
Deep generative models may detect novel compounds with favourable features, exhibiting chemical design potential. Traditional single-stage variational autoencoders (VAEs) lack validity, uniqueness, and biologically meaningful distribution alignment. ...

SpaMWGDA: Identifying spatial domains of spatial transcriptomes using multi-view weighted fusion graph convolutional network and data augmentation.

PLoS computational biology
The rapid development of spatial transcriptomics (ST) has made it possible to effectively integrate gene expression and spatial information of cells and accurately identify spatial domains. A large number of deep learning (DL)-based methods have been...

A study protocol for assessing the effects of intangible cultural heritage experiences on human well-being.

PloS one
BACKGROUND: While interventions have been designed which use extended reality (XR) technology in promoting physical, mental and social well-being through cultural heritage experiences, well-defined methodologies for the assessment of such interventio...

Predicting the risk of asthma development in youth using machine learning models.

PloS one
Asthma is a chronic respiratory disease characterized by wheezing and difficulty breathing, which disproportionally affects 4.7 million children in the U.S. Currently, there is a lack of asthma predictive models for youth with good performance. This ...

Machine learning-based prediction of metabolic dysfunction-associated steatotic liver disease using National Health and Nutrition Examination Survey (NHANES) data.

PloS one
OBJECTIVE: With the global increase in obesity rates and lifestyle changes, metabolic dysfunction-associated steatotic liver disease (MASLD) has become a prevalent chronic liver disorder, affecting approximately 25% of the global population. This dis...