Preventive Care

Deep learning for screening of interstitial lung disease patterns in high-resolution CT images.

AIM: To develop a screening tool for the detection of interstitial lung disease (ILD) patterns using...

Hard exudate detection based on deep model learned information and multi-feature joint representation for diabetic retinopathy screening.

BACKGROUND AND OBJECTIVE: Diabetic retinopathy (DR), which is generally diagnosed by the presence of...

Inconsistent Performance of Deep Learning Models on Mammogram Classification.

OBJECTIVES: Performance of recently developed deep learning models for image classification surpasse...

A machine learning approach for handling big data produced by high resolution mass spectrometry after data independent acquisition of small molecules - Proof of concept study using an artificial neural network for sample classification.

Liquid chromatography coupled to high-resolution mass spectrometry (HRMS) enables data independent a...

DeepCPI: A Deep Learning-based Framework for Large-scale in silico Drug Screening.

Accurate identification of compound-protein interactions (CPIs) in silico may deepen our understandi...

The application of artificial intelligence (AI) techniques to identify frailty within a residential aged care administrative data set.

INTRODUCTION: Research has shown that frailty, a geriatric syndrome associated with an increased ris...

Untargeted Metabolomics for Metabolic Diagnostic Screening with Automated Data Interpretation Using a Knowledge-Based Algorithm.

Untargeted metabolomics may become a standard approach to address diagnostic requests, but, at prese...

Factors Influencing Delivery of Cancer Survivorship Care Plans: A National Patterns of Care Study.

Nearly half of all Americans will develop cancer at least once in their lifetime. Through improved s...

Development and Evaluation of a Deep Learning System for Screening Retinal Hemorrhage Based on Ultra-Widefield Fundus Images.

PURPOSE: To develop and evaluate a deep learning (DL) system for retinal hemorrhage (RH) screening u...

High-Throughput Screening Technology in Industrial Biotechnology.

Based on the development of automatic devices and rapid assay methods, various high-throughput scree...

Automatic detection of rare pathologies in fundus photographs using few-shot learning.

In the last decades, large datasets of fundus photographs have been collected in diabetic retinopath...

Classification of glomerular hypercellularity using convolutional features and support vector machine.

Glomeruli are histological structures of the kidney cortex formed by interwoven blood capillaries, a...

A boosting inspired personalized threshold method for sepsis screening.

Sepsis is one of the biggest risks to patient safety, with a natural mortality rate between 25% and ...

Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

BACKGROUND: Colonoscopy with computer-aided detection (CADe) has been shown in non-blinded trials to...

DeepMalaria: Artificial Intelligence Driven Discovery of Potent Antiplasmodials.

Antimalarial drugs are becoming less effective due to the emergence of drug resistance. Resistance h...

Use of Artificial Intelligence-Based Analytics From Live Colonoscopies to Optimize the Quality of the Colonoscopy Examination in Real Time: Proof of Concept.

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment.

Mild cognitive impairment (MCI) is the first sign of dementia among elderly populations and its earl...

Machine intelligence in peptide therapeutics: A next-generation tool for rapid disease screening.

Discovery and development of biopeptides are time-consuming, laborious, and dependent on various fac...

Cost-effectiveness of targeted screening for the identification of patients with atrial fibrillation: evaluation of a machine learning risk prediction algorithm.

As many cases of atrial fibrillation (AF) are asymptomatic, patients often remain undiagnosed until...

Automated screening of natural language in electronic health records for the diagnosis septic shock is feasible and outperforms an approach based on explicit administrative codes.

PURPOSE: Identification of patients for epidemiologic research through administrative coding has imp...

pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens.

Identification of neoantigens is a critical step in predicting response to checkpoint blockade thera...