Identifying and Reporting Dependent Adult abuse

Extracting postmarketing adverse events from safety reports in the vaccine adverse event reporting system (VAERS) using deep learning.

OBJECTIVE: Automated analysis of vaccine postmarketing surveillance narrative reports is important t...

An integrated nomogram combining deep learning, Prostate Imaging-Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of clinically significant prostate cancer on biparametric MRI: a retrospective multicentre study.

BACKGROUND: Biparametric MRI (comprising T2-weighted MRI and apparent diffusion coefficient maps) is...

Consolidated EHR Workflow for Endoscopy Quality Reporting.

Although colonoscopy is the most frequently performed endoscopic procedure, the lack of standardized...

Enriching contextualized language model from knowledge graph for biomedical information extraction.

Biomedical information extraction (BioIE) is an important task. The aim is to analyze biomedical tex...

The effects of robot-assisted left-hand training on hemispatial neglect in older patients with chronic stroke: A pilot and randomized controlled trial.

BACKGROUND: Even though a variety of rehabilitative technique have been implemented to ameliorate ne...

New international reporting guidelines for clinical trials evaluating effectiveness of artificial intelligence interventions in dermatology: strengthening the SPIRIT of robust trial reporting.

The human visual system and CNNs can both support robust online translation tolerance following extreme displacements.

Visual translation tolerance refers to our capacity to recognize objects over a wide range of differ...

DECIDE-AI: new reporting guidelines to bridge the development-to-implementation gap in clinical artificial intelligence.

On the critical review of five machine learning-based algorithms for predicting protein stability changes upon mutation.

A review, recently published in this journal by Fang (2019), showed that methods trained for the pre...

Social Robot Interventions for People with Dementia: A Systematic Review on Effects and Quality of Reporting.

BACKGROUND: Using non-pharmacological interventions is a current approach in dementia care to manage...

Reporting of demographic data and representativeness in machine learning models using electronic health records.

OBJECTIVE: The development of machine learning (ML) algorithms to address a variety of issues faced ...

MINIMAR (MINimum Information for Medical AI Reporting): Developing reporting standards for artificial intelligence in health care.

The rise of digital data and computing power have contributed to significant advancements in artific...

Current Clinical Applications of Artificial Intelligence in Radiology and Their Best Supporting Evidence.

PURPOSE: Despite tremendous gains from deep learning and the promise of artificial intelligence (AI)...

A Systematic Search over Deep Convolutional Neural Network Architectures for Screening Chest Radiographs.

Chest radiographs are primarily employed for the screening of pulmonary and cardio-/thoracic conditi...

Reporting and Implementing Interventions Involving Machine Learning and Artificial Intelligence.

Increasingly, interventions aimed at improving care are likely to use such technologies as machine l...

[Cranial Facial 3D Biometry: Statistical analysis of Class II disharmonies].

We could study Cone Beam documents of patients consulting in ORL with standard Angle Class I occlusi...

Developing specific reporting guidelines for diagnostic accuracy studies assessing AI interventions: The STARD-AI Steering Group.

Follow-Up on the Use of Machine Learning in Clinical Quality Assurance: Can We Detect Adverse Event Under-Reporting in Oncology Trials?

Integrating distal and proximal information to predict gene expression via a densely connected convolutional neural network.

MOTIVATION: Interactions among cis-regulatory elements such as enhancers and promoters are main driv...

FOBI: an ontology to represent food intake data and associate it with metabolomic data.

Nutrition research can be conducted by using two complementary approaches: (i) traditional self-repo...

Deep convolutional neural network applied to the liver imaging reporting and data system (LI-RADS) version 2014 category classification: a pilot study.

PURPOSE: To develop a deep convolutional neural network (CNN) model to categorize multiphase CT and ...