US Health Policy

Neural critic learning with accelerated value iteration for nonlinear model predictive control.

In practical industrial processes, the receding optimization solution of nonlinear model predictive ...

Development and comparison of machine learning models for in-vitro drug permeation prediction from microneedle patch.

The field of machine learning (ML) is advancing to a larger extent and finding its applications acro...

Predictive value of magnetic resonance imaging diffusion parameters using artificial intelligence in low-and intermediate-risk prostate cancer patients treated with stereotactic ablative radiotherapy: A pilot study.

INTRODUCTION: To investigate the predictive value of the pre-treatment diffusion parameters of diffu...

Identifying time-resolved features of nocturnal sleep characteristics of narcolepsy using machine learning.

The differential diagnosis of narcolepsy type 1, a rare, chronic, central disorder of hypersomnolenc...

Development and validation of AI/ML derived splice-switching oligonucleotides.

Splice-switching oligonucleotides (SSOs) are antisense compounds that act directly on pre-mRNA to mo...

Prevalence, mortality, cost, and disparities in transcatheter mitral valve repair and replacement in cancer patients: Artificial intelligence and propensity score national 5-year analysis of 7495 procedures.

INTRODUCTION: We conducted the first comprehensive evaluation of the therapeutic value and safety pr...

Social Workers' Perspectives on Socially Isolated Older Adults Living with a Robot Companion.

Addressing depression and social isolation among solo-living older adults in South Korea requires a ...

Early health technology assessment: the value of valuing AI applications.

Clinical value of deep learning image reconstruction on the diagnosis of pulmonary nodule for ultra-low-dose chest CT imaging.

PURPOSE: To compare the image quality and pulmonary nodule detectability between deep learning image...

Part I: prostate cancer detection, artificial intelligence for prostate cancer and how we measure diagnostic performance: a comprehensive review.

MRI has firmly established itself as a mainstay for the detection, staging and surveillance of prost...

The value of CT radiomics combined with deep transfer learning in predicting the nature of gallbladder polypoid lesions.

BACKGROUND: Computed tomography (CT) radiomics combined with deep transfer learning was used to iden...

Predictive modeling of deep vein thrombosis risk in hospitalized patients: A Q-learning enhanced feature selection model.

Deep vein thrombosis (DVT) represents a critical health concern due to its potential to lead to pulm...

Protocol to explain support vector machine predictions via exact Shapley value computation.

Shapley values from cooperative game theory are adapted for explaining machine learning predictions....

Extracting value from total-body PET/CT image data - the emerging role of artificial intelligence.

The evolution of Positron Emission Tomography (PET), culminating in the Total-Body PET (TB-PET) syst...

Redefining Healthcare With Artificial Intelligence (AI): The Contributions of ChatGPT, Gemini, and Co-pilot.

Artificial Intelligence (AI) in healthcare marks a new era of innovation and efficiency, characteriz...

The value of artificial intelligence for the treatment of mechanically ventilated intensive care unit patients: An early health technology assessment.

PURPOSE: The health and economic consequences of artificial intelligence (AI) systems for mechanical...

Capturing artificial intelligence applications' value proposition in healthcare - a qualitative research study.

Artificial intelligence (AI) applications pave the way for innovations in the healthcare (HC) indust...

Explainable artificial intelligence models for predicting risk of suicide using health administrative data in Quebec.

Suicide is a complex, multidimensional event, and a significant challenge for prevention globally. A...

Using Natural Language Processing to Identify Home Health Care Patients at Risk for Diagnosis of Alzheimer's Disease and Related Dementias.

This study aimed to: (1) validate a natural language processing (NLP) system developed for the home ...

Detection of biomagnetic signals from induced pluripotent stem cell-derived cardiomyocytes using deep learning with simulation data.

The detection of spontaneous magnetic signals can be used for the non-invasive electrophysiological ...

Semi-supervised learning towards automated segmentation of PET images with limited annotations: application to lymphoma patients.

Manual segmentation poses a time-consuming challenge for disease quantification, therapy evaluation,...