Medicaid

Candidate Passive Sensor Suite Technologies for Tactical Combat Casualty Care Environments: Comparative Assessment Study.

BACKGROUND: The United States Army Institute for Surgical Research conducted an analysis of 3 prototype sensor suites; all candidates were designed to passively document care delivery in tactical combat casualty care environments. OBJECTIVE: This study aims to ensure sensor suites remain resilient and adaptive in complex battlefield environments. This research effort conducts a systematic comparat...

Denoising of ultra-low-dose 15O positron emission tomography images using deep image prior with anatomical information extracted through magnetic resonance segmentation.

PURPOSE: Recent deep-learning methods can recover standard-dose PET images from low-dose images. However, these methods require a large amount of data. We proposed a novel unsupervised learning approach using conditional deep image prior (DIP) with tissue probability maps extracted by magnetic resonance (MR) segmentation (DIPseg), to improve denoising performance by more explicit anatomical guidan...

Multitask Artificial Intelligence-Based Electrocardiogram Tool for Preoperative Cardiac Testing in Noncardiac Surgery: Retrospective Cohort Study of Health Care Utilization and Costs.

BACKGROUND: Preoperative cardiovascular risk stratification is essential in noncardiac surgery, but conventional testing is frequently overused, incre...

AI-Powered Resting 12-Lead Electrocardiogram Algorithm for Predicting Low Peak Oxygen Consumption: Development and Validation Study.

BACKGROUND: Low peak oxygen consumption (V̇O2) is associated with higher cardiovascular and all-cause mortality, while improvements in peak V̇O2 reduc...

Disparities in Engagement with an Artificial Intelligence-Based Chat Intervention Post-appendectomy.

PURPOSE: Artificial intelligence (AI)-based text messaging, or "chat," in post-appendectomy care has been shown to decrease preventable emergency depa...

[Prioritizing the development of clinical low vision rehabilitation institutions].

Low vision rehabilitation is an indispensable and integral part of the national eye health initiative, and it is directly related to the quality of li...

An empirical study of machine learning robustness and scalability for imbalanced tabular clinical data in emergency and critical care.

Every year, millions of patients pass through emergency departments and intensive care units where clinicians must make life-altering decisions under ...

Predictors of Detectable Viral Load among Adolescents with HIV in Low Resource Settings who are Receiving Care in Youth-Friendly Clinics.

OBJECTIVE: Adolescents with HIV (AWH) have higher rates of detectable viral loads (DVL) than adults. We sought to identify clinical and psychosocial p...

Prediction of hospitalisation in young children with pneumonia in Malawi: A machine learning-based approach.

BACKGROUND: Globally, pneumonia remains the single biggest cause of mortality in children under 5 years of age. This study sought to train and test a ...

The impact of a novel deep learning reconstruction algorithm on image quality in ultralow-dose CT: a quantitative phantom study.

OBJECTIVE: The aim of this study is to evaluate the performance of a novel deep learning image reconstruction (DLIR) algorithm in noise reduction, con...

Large language models for generating longitudinal synthetic data in low-risk pregnancy care.

This article describes an obstetric dataset covering the full continuum of care of 5000 synthetic low-risk pregnant women, from preconception to post-...

Digital and Blended Lifestyle Interventions for Preschool-Aged Children and Families With a Low Socioeconomic Position and the General Population: Scoping Review.

BACKGROUND: Many unhealthy habits develop in early childhood and can lead to long-term health risks, which disproportionately affect children with low...

Hybrid learning: a combination of self-supervised and supervised learning for joint MRI reconstruction and denoising in low-field MRI.

Deep learning has demonstrated strong potential for MRI reconstruction. However, conventional supervised learning requires high-quality, high-SNR refe...

Radiation dose-aware sinogram knowledge library transformer with feature modulation for low-dose medical image segmentation.

Low-dose computed tomography (LDCT) and low-dose positron emission tomography (LDPET) enable shorter acquisition times and lower radiation exposure. H...

Breaking the Limits of Low-Field MRI: Deep Learning Approaches to Image Enhancement.

Low-field magnetic resonance imaging (LF-MRI) has emerged as a transformative technology, offering portable and cost-effective solutions for medical i...

Automated abdominal aortic calcification, muscle health and incident falls: the UK Biobank Imaging Study.

Emerging evidence suggests that vascular disease is linked with poorer muscle strength and higher falls risk. We evaluated the association between abd...

Large Language Models in Colorectal Cancer Care and Clinical Decision Support: Systematic Review.

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer morbidity and mortality worldwide. The complexity of guideline-concordant care and un...

Determinants of Medical Help-Seeking Behavior Following Case Finding of Early Cognitive Impairment: Semistructured Interview Study of Patients and Caregivers.

BACKGROUND: Timely medical follow-up after a diagnosis of cognitive impairment, such as mild cognitive impairment (MCI) or dementia, is imperative for...

A preliminary study of a lifetime long-term care costs estimation model based on changes in care level: implications for sustainable long-term care in Japan.

BACKGROUND: Japan faces an unprecedented demographic shift, characterized by the world's most rapidly aging population and a projected surge in annual...

Assessing AI-generated smoking cessation advice for patient education in primary care.

BACKGROUND: Artificial intelligence (AI) has emerged as a promising tool to support smoking cessation in primary care, particularly for populations un...