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Domestic Violence

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

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Achieving Equity with Predictive Policing Algorithms: A Social Safety Net Perspective.

Whereas using artificial intelligence (AI) to predict natural hazards is promising, applying a predi...

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...

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...

Computational Models Used to Predict Cardiovascular Complications in Chronic Kidney Disease Patients: A Systematic Review.

cardiovascular complications (CVC) are the leading cause of death in patients with chronic kidney d...

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...

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...

Reporting guidelines for artificial intelligence in healthcare research.

Reporting guidelines are structured tools developed using explicit methodology that specify the mini...

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...

Fast screening of covariates in population models empowered by machine learning.

One of the objectives of Pharmacometry (PMX) population modeling is the identification of significan...

Artificial intelligence for advance requesting of immunohistochemistry in diagnostically uncertain prostate biopsies.

The use of immunohistochemistry in the reporting of prostate biopsies is an important adjunct when t...

Radiomics and deep learning methods in expanding the use of screening breast MRI.

• The use of screening breast MRI is expanding beyond high-risk women to include intermediate- and a...

AI based colorectal disease detection using real-time screening colonoscopy.

Colonoscopy is an effective tool for early screening of colorectal diseases. However, the applicatio...

Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography.

Cancer patients have a higher risk of cardiovascular disease (CVD) mortality than the general popula...

Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs.

We aimed to develop a deep learning algorithm detecting 10 common abnormalities (DLAD-10) on chest r...

Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT.

Background Accurate estimation of the malignancy risk of pulmonary nodules at chest CT is crucial fo...

[Main biological tools applied to newborn screening: Landscape and future perspectives].

Over the past fifty years, neonatal screening has become essential in the public health programs of ...

Breast cancer risk prediction in African women using Random Forest Classifier.

INTRODUCTION: One of the most important steps in combating breast cancer is early and accurate diagn...

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