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Domestic Violence

Latest AI and machine learning research in domestic violence for healthcare professionals.

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E-pharmacophore and deep learning based high throughput virtual screening for identification of CDPK1 inhibitors of Cryptosporidium parvum.

Cryptosporidiosis, a prevalent gastrointestinal illness worldwide, is caused by the protozoan parasi...

End-to-end reproducible AI pipelines in radiology using the cloud.

Artificial intelligence (AI) algorithms hold the potential to revolutionize radiology. However, a si...

Wavelet-based selection-and-recalibration network for Parkinson's disease screening in OCT images.

BACKGROUND AND OBJECTIVE: Parkinson's disease (PD) is one of the most prevalent neurodegenerative br...

No longer stuck in the past: new advances in artificial intelligence and molecular assays for parasitology screening and diagnosis.

PURPOSE OF REVIEW: Emerging technologies are revolutionizing parasitology diagnostics and challengin...

Perspectives on current approaches to virtual screening in drug discovery.

INTRODUCTION: For the past two decades, virtual screening (VS) has been an efficient hit finding app...

Simulated arbitration of discordance between radiologists and artificial intelligence interpretation of breast cancer screening mammograms.

Artificial intelligence (AI) algorithms have been retrospectively evaluated as replacement for one r...

High-Throughput Screening and Prediction of Nucleophilicity of Amines Using Machine Learning and DFT Calculations.

Nucleophilic index () as a significant parameter plays a crucial role in screening of amine catalyst...

Diabetic retinopathy screening with confocal fundus camera and artificial intelligence - assisted grading.

PURPOSE: Screening for diabetic retinopathy (DR) by ophthalmologists is costly and labour-intensive....

Inhalation Toxicity Screening of Consumer Products Chemicals using OECD Test Guideline Data-based Machine Learning Models.

This study aimed to screen the inhalation toxicity of chemicals found in consumer products such as a...

DSIL-DDI: A Domain-Invariant Substructure Interaction Learning for Generalizable Drug-Drug Interaction Prediction.

Drug-drug interactions (DDIs) trigger unexpected pharmacological effects in vivo, often with unknown...

Virtual-screening of xanthine oxidase inhibitory peptides: Inhibition mechanisms and prediction of activity using machine-learning.

Xanthine oxidase (XO) inhibitory peptides can prevent XO-mediated hyperuricemia. Currently, QSAR abo...

Machine learning approach for high-throughput phenolic antioxidant screening in black Rice germplasm collection based on surface FTIR.

Pigmented rice contains beneficial phenolic antioxidants but analysing them across germplasm collect...

Predicting the Hallucinogenic Potential of Molecules Using Artificial Intelligence.

The development of new drugs addressing serious mental health and other disorders should avoid the p...

Machine learning-based biomarker screening for acute myeloid leukemia prognosis and therapy from diverse cell-death patterns.

Acute myeloid leukemia (AML) exhibits pronounced heterogeneity and chemotherapy resistance. Aberrant...

A Cloud-Based System for Automated AI Image Analysis and Reporting.

Although numerous AI algorithms have been published, the relatively small number of algorithms used ...

Evaluating the accuracy of lung-RADS score extraction from radiology reports: Manual entry versus natural language processing.

INTRODUCTION: Radiology scoring systems are critical to the success of lung cancer screening (LCS) p...

Women's views on using artificial intelligence in breast cancer screening: A review and qualitative study to guide breast screening services.

As breast screening services move towards use of healthcare AI (HCAI) for screen reading, research o...

Combined structure-based virtual screening and machine learning approach for the identification of potential dual inhibitors of ACC and DGAT2.

Acetyl-coenzyme A carboxylase (ACC) and diacylglycerol acyltransferase 2 (DGAT2) are recognized as p...

Hybrid deep learning models for the screening of Diabetic Macular Edema in optical coherence tomography volumes.

Several studies published so far used highly selective image datasets from unclear sources to train ...

A deep learning framework for predicting endometrial cancer from cytopathologic images with different staining styles.

Endometrial cancer screening is crucial for clinical treatment. Currently, cytopathologists analyze ...

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