Surveillance

Artificial Intelligence-Electrocardiography to Predict Incident Atrial Fibrillation: A Population-Based Study.

BACKGROUND: An artificial intelligence (AI) algorithm applied to electrocardiography during sinus rh...

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...

Comparing machine learning with case-control models to identify confirmed dengue cases.

In recent decades, the global incidence of dengue has increased. Affected countries have responded w...

Guidelines for clinical trials using artificial intelligence - SPIRIT-AI and CONSORT-AI.

The rapidly growing use of artificial intelligence in pathology presents a challenge in terms of stu...

Country-level pandemic risk and preparedness classification based on COVID-19 data: A machine learning approach.

In this work we present a three-stage Machine Learning strategy to country-level risk classification...

Predicting population health with machine learning: a scoping review.

OBJECTIVE: To determine how machine learning has been applied to prediction applications in populati...

Magnetic resonance imaging-ultrasound fusion-targeted biopsy combined with systematic 12-core ultrasound-guided biopsy improves the detection of clinically significant prostate cancer: Are we ready to abandon the systematic approach?

BACKGROUND: Multiparametric (mp) magnetic resonance imaging (MRI)-ultrasound fusion-targeted biopsy ...

Recommendations for Reporting Machine Learning Analyses in Clinical Research.

Use of machine learning (ML) in clinical research is growing steadily given the increasing availabil...

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...

Prospective Validation of Vesical Imaging-Reporting and Data System Using a Next-Generation Magnetic Resonance Imaging Scanner-Is Denoising Deep Learning Reconstruction Useful?

PURPOSE: The Vesical Imaging Reporting and Data System (VI-RADS) was launched in 2018 to standardize...

How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts.

In recent years, there has been a dramatic increase in research papers about machine learning (ML) a...

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 ...

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...

REDBot: Natural language process methods for clinical copy number variation reporting in prenatal and products of conception diagnosis.

BACKGROUND: Current copy number variation (CNV) identification methods have rapidly become mature. H...

Digital Biopsy with Fluorescence Confocal Microscope for Effective Real-time Diagnosis of Prostate Cancer: A Prospective, Comparative Study.

BACKGROUND: A microscopic analysis of tissue is the gold standard for cancer detection. Hematoxylin-...

Artificial intelligence in cardiac radiology.

Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its implementat...

Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning.

It is important that antibiotics prescriptions are based on antimicrobial susceptibility data to ens...

Inconsistency in the use of the term "validation" in studies reporting the performance of deep learning algorithms in providing diagnosis from medical imaging.

BACKGROUND: The development of deep learning (DL) algorithms is a three-step process-training, tunin...

Reporting Guidelines for Artificial Intelligence in Medical Research.

A Comparative Analysis of Two Machine Learning-Based Diagnostic Patterns with Thyroid Imaging Reporting and Data System for Thyroid Nodules: Diagnostic Performance and Unnecessary Biopsy Rate.

The risk stratification system of the American College of Radiology Thyroid Imaging Reporting and D...

Incorporating standardised reporting guidelines in clinical trials of artificial intelligence in gastrointestinal endoscopy.