Primary Care

Preventive Care

Latest AI and machine learning research in preventive care for healthcare professionals.

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Bioinformatics and machine learning approach identifies potential drug targets and pathways in COVID-19.

Current coronavirus disease-2019 (COVID-19) pandemic has caused massive loss of lives. Clinical tria...

Accuracy or novelty: what can we gain from target-specific machine-learning-based scoring functions in virtual screening?

Machine-learning (ML)-based scoring functions (MLSFs) have gradually emerged as a promising alternat...

Do you have COVID-19? An artificial intelligence-based screening tool for COVID-19 using acoustic parameters.

This study aimed to develop an artificial intelligence (AI)-based tool for screening COVID-19 patien...

Establishment and validation of a computer-assisted colonic polyp localization system based on deep learning.

BACKGROUND: Artificial intelligence in colonoscopy is an emerging field, and its application may hel...

Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data.

Most lung cancers are diagnosed at an advanced stage. Presymptomatic identification of high-risk in...

Electrocardiogram screening for aortic valve stenosis using artificial intelligence.

AIMS: Early detection of aortic stenosis (AS) is becoming increasingly important with a better outco...

Deep Learning for Automated Diabetic Retinopathy Screening Fused With Heterogeneous Data From EHRs Can Lead to Earlier Referral Decisions.

PURPOSE: Fundus images are typically used as the sole training input for automated diabetic retinopa...

Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study.

BACKGROUND: Medical artificial intelligence (AI) has entered the clinical implementation phase, alth...

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...

Vaxign2: the second generation of the first Web-based vaccine design program using reverse vaccinology and machine learning.

Vaccination is one of the most significant inventions in medicine. Reverse vaccinology (RV) is a sta...

Non-destructive acoustic screening of pineapple ripeness by unsupervised machine learning and Wavelet Kernel methods.

In a pineapple exporting factory, manual lines are usually built to screen fruits of non-ripen hitti...

Creative Approaches for Assessing Long-term Outcomes in Children.

Advances in new technologies, when incorporated into routine health screening, have tremendous promi...

Artificial Intelligence-Based Screening for Mycobacteria in Whole-Slide Images of Tissue Samples.

OBJECTIVES: This study aimed to develop and validate a deep learning algorithm to screen digitized a...

Application of artificial intelligence-driven endoscopic screening and diagnosis of gastric cancer.

The landscape of gastrointestinal endoscopy continues to evolve as new technologies and techniques b...

Artificial intelligence in breast cancer screening: primary care provider preferences.

BACKGROUND: Artificial intelligence (AI) is increasingly being proposed for use in medicine, includi...

Use of ColonFlag score for prioritisation of endoscopy in colorectal cancer.

OBJECTIVE: Colorectal cancer (CRC) is the fourth most common cancer in UK. Symptomatic patients are ...

Consolidated EHR Workflow for Endoscopy Quality Reporting.

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

LightBBB: computational prediction model of blood-brain-barrier penetration based on LightGBM.

MOTIVATION: Identification of blood-brain barrier (BBB) permeability of a compound is a major challe...

The impact of compound library size on the performance of scoring functions for structure-based virtual screening.

Larger training datasets have been shown to improve the accuracy of machine learning (ML)-based scor...

Improving structure-based virtual screening performance via learning from scoring function components.

Scoring functions (SFs) based on complex machine learning (ML) algorithms have gradually emerged as ...

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