Health Policy

Dual-use ionization source for direct and sensitive detection of trace carbamates residue.

Directly determining trace compounds in actual sample by ambient ionization mass spectrometry (AIMS)...

Deep Learning Image Reconstruction Algorithm for CCTA: Image Quality Assessment and Clinical Application.

OBJECTIVE: The increasing number of coronary computed tomography angiography (CCTA) requests raised ...

Deep Learning-Based T2-Weighted MR Image Quality Assessment and Its Impact on Prostate Cancer Detection Rates.

BACKGROUND: Image quality evaluation of prostate MRI is important for successful implementation of M...

An AI-based algorithm for the automatic evaluation of image quality in canine thoracic radiographs.

The aim of this study was to develop and test an artificial intelligence (AI)-based algorithm for de...

Classification and rapid non-destructive quality evaluation of different processed products of Cyperus rotundus based on near-infrared spectroscopy combined with deep learning.

The quality of traditional Chinese medicine is very important for human health, but the traditional ...

Artificial Intelligence-Driven Image Quality Selection During Myocardial Contrast Echocardiography: A New Path to Precision.

Artificial Intelligence for Quantitative Modeling in Drug Discovery and Development: An Innovation and Quality Consortium Perspective on Use Cases and Best Practices.

Recent breakthroughs in artificial intelligence (AI) and machine learning (ML) have ushered in a new...

Natural language processing for mental health interventions: a systematic review and research framework.

Neuropsychiatric disorders pose a high societal cost, but their treatment is hindered by lack of obj...

Reducing the risk of hallucinations with interpretable deep learning models for low-dose CT denoising: comparative performance analysis.

Reducing CT radiation dose is an often proposed measure to enhance patient safety, which, however re...

Federated Semi-Supervised Learning for Medical Image Segmentation via Pseudo-Label Denoising.

Distributed big data and digital healthcare technologies have great potential to promote medical ser...

Stochastic scheduling of autonomous mobile robots at hospitals.

This paper studies the scheduling of autonomous mobile robots (AMRs) at hospitals where the stochast...

A Novel Extensible Continuum Robot with Growing Motion Capability Inspired by Plant Growth for Path-Following in Transoral Laryngeal Surgery.

This article presents a novel extensible continuum robot (ECR) with growing motion capability for im...

Challenges and opportunities of big data analytics in healthcare.

Data science is an interdisciplinary discipline that employs big data, machine learning algorithms, ...

Rapid runtime learning by curating small datasets of high-quality items obtained from memory.

We propose the "runtime learning" hypothesis which states that people quickly learn to perform unfam...

Editorial for "Deep Learning-Based T2-Weighted MR Image Quality Assessment and Its Impact on Prostate Cancer Detection Rates".

Interpretable algorithmic forensics.

One of the most troubling trends in criminal investigations is the growing use of "black box" techno...

The role of corporate social responsibility and government incentives in installing industrial wastewater treatment plants: SEM-ANN deep learning approach.

Contaminated industrial wastewater is one of the severe causes of health diseases. The wastewater tr...

The Role of Artificial Intelligence and Machine Learning in Assisted Reproductive Technologies.

Artificial intelligence (AI) and machine learning, the form most commonly used in medicine, offer po...

Addressing the challenges of AI-based telemedicine: Best practices and lessons learned.

Telemedicine is the use of technology to provide healthcare services and information remotely, witho...

Procedure code overutilization detection from healthcare claims using unsupervised deep learning methods.

BACKGROUND: Fraud, Waste, and Abuse (FWA) in medical claims have a negative impact on the quality an...

A quality detection method of corn based on spectral technology and deep learning model.

Corn is an important food crop in the world. With economic development and population growth, the nu...