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Domestic Violence

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

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Showing 1366-1386 of 3,663 articles
Utilization of machine learning to test the impact of cognitive processing and emotion recognition on the development of PTSD following trauma exposure.

BACKGROUND: Though lifetime exposure to traumatic events is significant, only a minority of individu...

Jun 2020 32576245
A preliminary evaluation of still face images by deep learning: A potential screening test for childhood developmental disabilities.

Most developmental disorders are defined by their clinical symptoms and many disorders share common ...

Jun 2020 32540607
An innovative method for screening and evaluating the degree of diabetic retinopathy and drug treatment based on artificial intelligence algorithms.

Current methods of evaluating the degree of diabetic retinopathy are highly subjective and have no q...

Jun 2020 32502641
Improvement of oral cancer screening quality and reach: The promise of artificial intelligence.

Oral cancer is easily detectable by physical (self) examination. However, many cases of oral cancer ...

May 2020 32162398
Deep learning in generating radiology reports: A survey.

Substantial progress has been made towards implementing automated radiology reporting models based o...

May 2020 32425358
LIT-PCBA: An Unbiased Data Set for Machine Learning and Virtual Screening.

Comparative evaluation of virtual screening methods requires a rigorous benchmarking procedure on di...

Apr 2020 32282202
Exploring the Role of Artificial Intelligence in an Emergency and Trauma Radiology Department.

Emergency and trauma radiologists, emergency department's physicians and nurses, researchers, depart...

Apr 2020 32309989
Flaws (and quality) in research today: can artificial intelligence intervene?

The existing flaws in both conducting and reporting of research have been outlined and criticized in...

Apr 2020 32267779
Machine learning for screening prioritization in systematic reviews: comparative performance of Abstrackr and EPPI-Reviewer.

BACKGROUND: Improving the speed of systematic review (SR) development is key to supporting evidence-...

Apr 2020 32241297
Artificial Intelligence in Dermatology: A Primer.

Artificial intelligence is becoming increasingly important in dermatology, with studies reporting ac...

Mar 2020 32229141
Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies.

OBJECTIVE: To systematically examine the design, reporting standards, risk of bias, and claims of st...

Mar 2020 32213531
Reporting quality of studies using machine learning models for medical diagnosis: a systematic review.

AIMS: We conducted a systematic review assessing the reporting quality of studies validating models ...

Mar 2020 32205374
Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness.

Machine learning, artificial intelligence, and other modern statistical methods are providing new op...

Mar 2020 32198138
Development of an early-warning system for high-risk patients for suicide attempt using deep learning and electronic health records.

Suicide is the tenth leading cause of death in the United States (US). An early-warning system (EWS)...

Feb 2020 32080165
Automatic opportunistic osteoporosis screening using low-dose chest computed tomography scans obtained for lung cancer screening.

OBJECTIVE: Osteoporosis is a prevalent and treatable condition, but it remains underdiagnosed. In th...

Feb 2020 32072260
Applying Machine Learning to Ultrafast Shape Recognition in Ligand-Based Virtual Screening.

Ultrafast Shape Recognition (USR), along with its derivatives, are Ligand-Based Virtual Screening (L...

Feb 2020 32140104
Factors Influencing Delivery of Cancer Survivorship Care Plans: A National Patterns of Care Study.

Nearly half of all Americans will develop cancer at least once in their lifetime. Through improved s...

Jan 2020 32083018
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