Risk Management

Test-time adaptable neural networks for robust medical image segmentation.

Convolutional Neural Networks (CNNs) work very well for supervised learning problems when the traini...

Intelligent checklists improve checklist compliance in the intensive care unit: a prospective before-and-after mixed-method study.

BACKGROUND: We examined whether a context and process-sensitive 'intelligent' checklist increases co...

Assessing hERG1 Blockade from Bayesian Machine-Learning-Optimized Site Identification by Ligand Competitive Saturation Simulations.

Drug-induced cardiotoxicity is a potentially lethal and yet one of the most common side effects with...

Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study.

Machine learning (ML)-based algorithms for cardiovascular disease (CVD) risk assessment have shown p...

Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques.

INTRODUCTION: Studies addressing the development and/or validation of diagnostic and prognostic pred...

Suicide Risk Assessment Using Machine Learning and Social Networks: a Scoping Review.

According to the World Health Organization (WHO) report in 2016, around 800,000 of individuals have ...

How Much Can Potential Jurors Tell Us About Liability for Medical Artificial Intelligence?

Text Classification for Clinical Trial Operations: Evaluation and Comparison of Natural Language Processing Techniques.

The ability to detect patterns and trends across protocol deviations (PDs) is key to ensure high dat...

A Machine Learning Protocol for Predicting Protein Infrared Spectra.

Infrared (IR) absorption provides important chemical fingerprints of biomolecules. Protein secondary...

Artificial intelligence in medicine: A matter of joy or concern?

Artificial Intelligence (AI), a concept which dates back to the 1950s, is increasingly being develop...

Testing a convolutional neural network-based hippocampal segmentation method in a stroke population.

As stroke mortality rates decrease, there has been a surge of effort to study poststroke dementia (P...

Approval policies for modifications to machine learning-based software as a medical device: A study of bio-creep.

Successful deployment of machine learning algorithms in healthcare requires careful assessments of t...

Development and Validation of a Natural Language Processing Tool to Generate the CONSORT Reporting Checklist for Randomized Clinical Trials.

IMPORTANCE: Adherence to the Consolidated Standards of Reporting Trials (CONSORT) for randomized cli...

When Does Physician Use of AI Increase Liability?

An increasing number of automated and artificial intelligence (AI) systems make medical treatment re...

Machine Learning in Nuclear Medicine: Part 2-Neural Networks and Clinical Aspects.

This article is the second part in our machine learning series. Part 1 provided a general overview o...

Transfer learning in deep neural network based under-sampled MR image reconstruction.

In Magnetic Resonance Imaging (MRI), the success of deep learning-based under-sampled MR image recon...

FPGAN: Face de-identification method with generative adversarial networks for social robots.

In this paper, we propose a new face de-identification method based on generative adversarial networ...

Artificial intelligence in medicine creates real risk management and litigation issues.

The next step in the evolution of electronic medical record (EMR) use is the integration of artifici...

Noise reduction with cross-tracer and cross-protocol deep transfer learning for low-dose PET.

Previous studies have demonstrated the feasibility of reducing noise with deep learning-based method...

Improved Activity Recognition Combining Inertial Motion Sensors and Electroencephalogram Signals.

Human activity recognition and neural activity analysis are the basis for human computational neureo...

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.

The CONSORT 2010 statement provides minimum guidelines for reporting randomised trials. Its widespre...