Surveillance

When two heads are better than one: nutritional epidemiology meets machine learning.

Artificial intelligence and the future of global health.

Concurrent advances in information technology infrastructure and mobile computing power in many low ...

AI Surveillance during Pandemics: Ethical Implementation Imperatives.

Artificial intelligence surveillance can be used to diagnose individual cases, track the spread of C...

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

Big Data in Ophthalmology.

Big data is the fuel of mankind's fourth industrial revolution. Coupled with new technology such as ...

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...

Future Vision 2020 and Beyond-5 Critical Trends in Eye Research.

Ophthalmology has been at the forefront of many innovations in basic science and clinical research. ...

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 ...

Application of Augmented Intelligence for Pharmacovigilance Case Seriousness Determination.

INTRODUCTION: Identification of adverse events and determination of their seriousness ensures timely...

Natural Language Processing for the Identification of Surgical Site Infections in Orthopaedics.

BACKGROUND: The identification of surgical site infections for infection surveillance in hospitals d...

Comparison of prostate cancer detection rates between magnetic resonance imaging-targeted biopsy and transrectal ultrasound-guided biopsy according to Prostate Imaging Reporting and Data System in patients with PSA ≥4 ng/mL: a systematic review and meta-analysis.

BACKGROUND: Previous studies have investigated magnetic resonance imaging-targeted biopsy (MRI-TBx) ...

Reporting on deep learning algorithms in health care.

Transparent Reporting on Research Using Unstructured Electronic Health Record Data to Generate 'Real World' Evidence of Comparative Effectiveness and Safety.

Research that makes secondary use of administrative and clinical healthcare databases is increasingl...

Applying Natural Language Processing to Evaluate News Media Coverage of Bullying and Cyberbullying.

Bullying events have frequently been the focus of coverage by news media, including news stories abo...

[An overview of validation methods based on the medical claims database].

Medical claims database is an important source of data for studying the characteristics, and burden ...

Reporting guidelines for clinical trials evaluating artificial intelligence interventions are needed.

Enabling Data-Driven Clinical Quality Assurance: Predicting Adverse Event Reporting in Clinical Trials Using Machine Learning.

INTRODUCTION: Adverse event (AE) under-reporting has been a recurrent issue raised during health aut...

A New Approach to Compare the Performance of Two Classification Methods of Causes of Death for Timely Surveillance in France.

Timely mortality surveillance in France is based on the monitoring of electronic death certificates ...

IDOMEN: An Extension of Infectious Disease Ontology for MENingitis.

In sub-Saharan African countries the prevention and control of epidemic diseases requires the improv...

Combining Natural Language Processing of Electronic Medical Notes With Administrative Data to Determine Racial/Ethnic Differences in the Disclosure and Documentation of Military Sexual Trauma in Veterans.

BACKGROUND: Despite national screening efforts, military sexual trauma (MST) is underreported. Littl...

A Deep Learning-Based Decision Support Tool for Precision Risk Assessment of Breast Cancer.

PURPOSE: The Breast Imaging Reporting and Data System (BI-RADS) lexicon was developed to standardize...