Health Policy

Development and Validation of a Gene Signature Classifier for Consensus Molecular Subtyping of Colorectal Carcinoma in a CLIA-Certified Setting.

PURPOSE: Consensus molecular subtyping (CMS) of colorectal cancer has potential to reshape the color...

Infusion of short chain fatty acids in the ileum improves the carcass traits, meat quality and lipid metabolism of growing pigs.

Short chain fatty acids (SCFA) are the main products of indigestible carbohydrates undergoing bacter...

Detecting Technical Anomalies in High-Frequency Water-Quality Data Using Artificial Neural Networks.

Anomaly detection (AD) in high-volume environmental data requires one to tackle a series of challeng...

Generating High-Quality Lymph Node Clinical Target Volumes for Head and Neck Cancer Radiation Therapy Using a Fully Automated Deep Learning-Based Approach.

PURPOSE: To develop a deep learning model that generates consistent, high-quality lymph node clinica...

Combination of Deep Learning-Based Denoising and Iterative Reconstruction for Ultra-Low-Dose CT of the Chest: Image Quality and Lung-RADS Evaluation.

The objective of our study was to assess the effect of the combination of deep learning-based denoi...

The Role of Mobility Digital Ecosystems for Age-Friendly Urban Public Transport: A Narrative Literature Review.

Within the context of the intersection of the global megatrends of urbanisation, ageing societies an...

Machine learning identifies abnormal Ca transients in human induced pluripotent stem cell-derived cardiomyocytes.

Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) provide an excellent platform...

COVID-SAFE: An IoT-Based System for Automated Health Monitoring and Surveillance in Post-Pandemic Life.

In the early months of the COVID-19 pandemic with no designated cure or vaccine, the only way to bre...

Deep learning-based image reconstruction for brain CT: improved image quality compared with adaptive statistical iterative reconstruction-Veo (ASIR-V).

PURPOSE: To compare the image quality of brain computed tomography (CT) images reconstructed with de...

Real-time monitoring and prediction of water quality parameters and algae concentrations using microbial potentiometric sensor signals and machine learning tools.

The overarching hypothesis of this study was that temporal microbial potentiometric sensor (MPS) sig...

Deep learning-based and hybrid-type iterative reconstructions for CT: comparison of capability for quantitative and qualitative image quality improvements and small vessel evaluation at dynamic CE-abdominal CT with ultra-high and standard resolutions.

PURPOSE: To determine the image quality improvement including vascular structures using deep learnin...

A Machine Learning-Assisted Nanoparticle-Printed Biochip for Real-Time Single Cancer Cell Analysis.

Cancers are a complex conglomerate of heterogeneous cell populations with varying genotypes and phen...

Key insights in the AIDA community policy on sharing of clinical imaging data for research in Sweden.

Development of world-class artificial intelligence (AI) for medical imaging requires access to massi...

Ada-WHIPS: explaining AdaBoost classification with applications in the health sciences.

BACKGROUND: Computer Aided Diagnostics (CAD) can support medical practitioners to make critical deci...

Robotic Hepatectomy Is a Safe and Cost-Effective Alternative to Conventional Open Hepatectomy: a Single-Center Preliminary Experience.

A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability.

Health data that are publicly available are valuable resources for digital health research. Several ...

Part 1: Artificial intelligence technology in surgery.

Artificial intelligence (AI) is one of the disruptive technologies of the fourth Industrial Revoluti...

Application of an artificial neural network for the improvement of agricultural drainage water quality using a submerged biofilter.

Artificial neural network (ANN) mathematical models, such as the radial basis function neural networ...

Learning hidden patterns from patient multivariate time series data using convolutional neural networks: A case study of healthcare cost prediction.

OBJECTIVE: To develop an effective and scalable individual-level patient cost prediction method by a...

Population demographics in geographic proximity to hospitals with robotic platforms do not correlate with disparities in access to robotic surgery.

BACKGROUND: Disparities in access to robotic surgery have been shown on the local, regional, and nat...

Reverse-Engineering Neural Networks to Characterize Their Cost Functions.

This letter considers a class of biologically plausible cost functions for neural networks, where th...