Domestic Violence

A deep learning and docking simulation-based virtual screening strategy enables the rapid identification of HIF-1α pathway activators from a marine natural product database.

Artificial Intelligence is hailed as a cutting-edge technology for accelerating drug discovery effor...

Artificial intelligence assisted identification of potential tau aggregation inhibitors: ligand- and structure-based virtual screening, in silico ADME, and molecular dynamics study.

Alzheimer's disease (AD) is a severe, growing, multifactorial disorder affecting millions of people ...

Systematic review finds "spin" practices and poor reporting standards in studies on machine learning-based prediction models.

OBJECTIVES: We evaluated the presence and frequency of spin practices and poor reporting standards i...

A "Do No Harm" Novel Safety Checklist and Research Approach to Determine Whether to Launch an Artificial Intelligence-Based Medical Technology: Introducing the Biological-Psychological, Economic, and Social (BPES) Framework.

Given the impact artificial intelligence (AI)-based medical technologies (hardware devices, software...

Assessing the utility of a sliding-windows deep neural network approach for risk prediction of trauma patients.

The risks of post trauma complications are regulated by the injury, comorbidities, and the clinical ...

Deep Learning-Enabled Morphometric Analysis for Toxicity Screening Using Zebrafish Larvae.

Toxicology studies heavily rely on morphometric analysis to detect abnormalities and diagnose diseas...

Machine-learning screening of luminogens with aggregation-induced emission characteristics for fluorescence imaging.

Due to the excellent biocompatible physicochemical performance, luminogens with aggregation-induced ...

Super High-Throughput Screening of Enzyme Variants by Spectral Graph Convolutional Neural Networks.

Finding new enzyme variants with the desired substrate scope requires screening through a large numb...

Tile-based microscopic image processing for malaria screening using a deep learning approach.

BACKGROUND: Manual microscopic examination remains the golden standard for malaria diagnosis. But it...

Artificial intelligence based virtual screening study for competitive and allosteric inhibitors of the SARS-CoV-2 main protease.

SARS-CoV-2 is a highly contagious and dangerous coronavirus that first appeared in late 2019 causing...

Correlation analysis of deep learning methods in S-ICD screening.

BACKGROUND: Machine learning methods are used in the classification of various cardiovascular diseas...

The Synergy between Deep Learning and Organs-on-Chips for High-Throughput Drug Screening: A Review.

Organs-on-chips (OoCs) are miniature microfluidic systems that have arguably become a class of advan...

Artificial intelligence CAD tools in trauma imaging: a scoping review from the American Society of Emergency Radiology (ASER) AI/ML Expert Panel.

BACKGROUND: AI/ML CAD tools can potentially improve outcomes in the high-stakes, high-volume model o...

In Silico Screening and Optimization of Cell-Penetrating Peptides Using Deep Learning Methods.

Cell-penetrating peptides (CPPs) have great potential to deliver bioactive agents into cells. Althou...

A Patch-Based Deep Learning Approach for Detecting Rib Fractures on Frontal Radiographs in Young Children.

Chest radiography is the modality of choice for the identification of rib fractures in young childre...

High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography.

X-ray crystallography is the most commonly employed technique to discern macromolecular structures, ...

Are Deep Learning Structural Models Sufficiently Accurate for Virtual Screening? Application of Docking Algorithms to AlphaFold2 Predicted Structures.

Machine learning-based protein structure prediction algorithms, such as RosettaFold and AlphaFold2, ...

MRI Screening in Vestibular Schwannoma: A Deep Learning-based Analysis of Clinical and Audiometric Data.

OBJECTIVE: To find a more objective method of assessing which patients should be screened for a vest...

AI: Workload Reduction by Autonomous Reporting of Normal Chest Radiographs.

Autonomous Chest Radiograph Reporting Using AI: Estimation of Clinical Impact.

Background Automated interpretation of normal chest radiographs could alleviate the workload of radi...

Artificial Intelligence Screening of Medical School Applications: Development and Validation of a Machine-Learning Algorithm.

PURPOSE: To explore whether a machine-learning algorithm could accurately perform the initial screen...