Preventive Care

Indian citizen's perspective about side effects of COVID-19 vaccine - A machine learning study.

BACKGROUND AND AIMS: Ever since the vaccination drive for COVID-19 has started in India, the citizen...

Current status and limitations of artificial intelligence in colonoscopy.

BACKGROUND: Artificial intelligence (AI) using deep learning methods for polyp detection (CADe) and ...

Computational representations of protein-ligand interfaces for structure-based virtual screening.

: Structure-based virtual screening (SBVS) is an essential strategy for hit identification. SBVS pri...

Ensemble machine learning of factors influencing COVID-19 across US counties.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the causal agent for COVID-19, is a com...

Detecting Medical Misinformation on Social Media Using Multimodal Deep Learning.

In 2019, outbreaks of vaccine-preventable diseases reached the highest number in the US since 1992. ...

Tracking COVID-19 vaccine hesitancy and logistical challenges: A machine learning approach.

Can we screen for pancreatic cancer? Identifying a sub-population of patients at high risk of subsequent diagnosis using machine learning techniques applied to primary care data.

BACKGROUND: Pancreatic cancer (PC) represents a substantial public health burden. Pancreatic cancer ...

FTIR spectroscopy with machine learning: A new approach to animal DNA polymorphism screening.

Technological advances in recent decades, especially in molecular genetics, have enabled the detecti...

Machine Learning Boosted Docking (HASTEN): An Open-source Tool To Accelerate Structure-based Virtual Screening Campaigns.

The software macHine leArning booSTEd dockiNg (HASTEN) was developed to accelerate structure-based v...

A robust real-time deep learning based automatic polyp detection system.

Colorectal cancer (CRC) is globally the third most common type of cancer. Colonoscopy is considered ...

Power of big data to improve patient care in gastroenterology.

Big data is defined as being large, varied or frequently updated, and usually generated from real-wo...

Multiple machine learning models combined with virtual screening and molecular docking to identify selective human ALDH1A1 inhibitors.

Aldehyde dehydrogenases (ALDHs) are the enzymes of oxidoreductase family that are responsible for th...

Prediction of the Blood-Brain Barrier (BBB) Permeability of Chemicals Based on Machine-Learning and Ensemble Methods.

The ability of chemicals to enter the blood-brain barrier (BBB) is a key factor for central nervous ...

Recent progress on the prospective application of machine learning to structure-based virtual screening.

As more bioactivity and protein structure data become available, scoring functions (SFs) using machi...

Predicting youth diabetes risk using NHANES data and machine learning.

Prediabetes and diabetes mellitus (preDM/DM) have become alarmingly prevalent among youth in recent ...

Artificial Intelligence for Screening Chinese Electronic Medical Record and Biobank Information.

To establish a structured and integrated platform of clinical data and biobank data, and a client t...

Data-driven approaches to advance research and clinical care for pediatric cancer.

Pediatric cancer is a rare disease with a distinct etiology and mutational landscape compared with a...

Text mining to support abstract screening for knowledge syntheses: a semi-automated workflow.

BACKGROUND: Current text mining tools supporting abstract screening in systematic reviews are not wi...

Automated laryngeal mass detection algorithm for home-based self-screening test based on convolutional neural network.

BACKGROUND: Early detection of laryngeal masses without periodic visits to hospitals is essential fo...

Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2.

A global pandemic has emerged following the appearance of the new severe acute respiratory virus who...

Automated Generation of Novel Fragments Using Screening Data, a Dual SMILES Autoencoder, Transfer Learning and Syntax Correction.

Fragment-based hit identification (FBHI) allows proportionately greater coverage of chemical space u...