AIMC Topic: Humans

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Spatiotemporal Deep Learning-Based Cine Loop Quality Filter for Handheld Point-of-Care Echocardiography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
The reliability of automated image interpretation of point-of-care (POC) echocardiography scans depends on the quality of the acquired ultrasound data. This work reports on the development and validation of spatiotemporal deep learning models to asse...

Automatic Segmentation of Abdominal Aortic Aneurysms From Time-Resolved 3-D Ultrasound Images Using Deep Learning.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Abdominal aortic aneurysms (AAAs) are rupture-prone dilatations of the aorta. In current clinical practice, the maximal diameter of AAAs is monitored with 2-D ultrasound to estimate their rupture risk. Recent studies have shown that 3-D and mechanica...

Deep-Learning Model for Quality Assessment of Urinary Bladder Ultrasound Images Using Multiscale and Higher-Order Processing.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Autonomous ultrasound image quality assessment (US-IQA) is a promising tool to aid the interpretation by practicing sonographers and to enable the future robotization of ultrasound procedures. However, autonomous US-IQA has several challenges. Ultras...

Automatic 3-D Lamina Curve Extraction From Freehand 3-D Ultrasound Data Using Sequential Localization Recurrent Convolutional Networks.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Freehand 3-D ultrasound imaging is emerging as a promising modality for regular spine exams due to its noninvasiveness and affordability. The laminae landmarks play a critical role in depicting the 3-D shape of the spine. However, the extraction of t...

Predicting place of delivery choice among childbearing women in East Africa: a comparative analysis of advanced machine learning techniques.

Frontiers in public health
BACKGROUND: Sub-Saharan Africa faces high neonatal and maternal mortality rates due to limited access to skilled healthcare during delivery. This study aims to improve the classification of health facilities and home deliveries using advanced machine...

Physicians' ethical concerns about artificial intelligence in medicine: a qualitative study: .

Frontiers in public health
BACKGROUND/AIM: Artificial Intelligence (AI) is the capability of computational systems to perform tasks that require human-like cognitive functions, such as reasoning, learning, and decision-making. Unlike human intelligence, AI does not involve sen...

Screening for frequent hospitalization risk among community-dwelling older adult between 2016 and 2023: machine learning-driven item selection, scoring system development, and prospective validation.

Frontiers in public health
BACKGROUND: Screening for frequent hospitalizations in the community can help prevent super-utilizers from growing in the inpatient population. However, the determinants of frequent hospitalizations have not been systematically examined, their operat...

Analysis of the Predictors of Mortality from Ischemic Heart Diseases in the Southern Region of Brazil: A Geographic Machine-Learning-Based Study.

Global heart
BACKGROUND: Mortality due to ischemic heart disease (IHD) is heterogeneously distributed globally, and identifying the sites most affected by it is essential in developing strategies to mitigate the impact of the disease, despite the complexity resul...

Deciphering the impact of senescence in kidney transplant rejection: An integrative machine learning and multi-omics analysis via bulk and single-cell RNA sequencing.

PloS one
BACKGROUND: The demographic shift towards an older population presents significant challenges for kidney transplantation (KTx), particularly due to the vulnerability of aged donor kidneys to ischemic damage, delayed graft function, and reduced graft ...

GFPrint™: A machine learning tool for transforming genetic data into clinical insights.

PloS one
The increasing availability of massive genetic sequencing data in the clinical setting has triggered the need for appropriate tools to help fully exploit the wealth of information these data possess. GFPrint™ is a proprietary streaming algorithm desi...