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Identifying and Reporting Dependent Adult abuse

Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.

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Showing 988-1008 of 2,385 articles
Quantifying new threats to health and biomedical literature integrity from rapidly scaled publications and problematic research

The last three years have seen an explosion in published manuscripts analysing open-access health da...

Calibrating CONSORT-AI with FAIR Principles to enhance reproducibility in AI-driven clinical trials

Artificial intelligence (AI) is increasingly embedded in clinical trials, yet poor reproducibility r...

Association between zidovudine and adverse pregnancy outcomes/congenital malformations: A pharmacovigilance study using FAERS data

Zidovudine (AZT), a key antiretroviral drug used for HIV treatment and preventing mother-to-child tr...

Signal Mining and Analysis of Adverse Events of Isotretinoin: 20-year real-world pharmacovigilance analysis based on the FAERS database

To identify post-marketing adverse event (AE) signals associated with isotretinoin using real-world ...

Towards Participatory Precision Health: Systematic Review and Co-designed Guidelines For Adolescent Just-in-time Adaptive Interventions

Adolescence and young adulthood (10-25 years) constitute a sensitive developmental period marked by ...

AutoReporter: Development of an artificial intelligence tool for automated assessment of research reporting guideline adherence

To develop AutoReporter, a large-language-model system that automates evaluation of adherence to res...

Aligning computational pathology with clinical practice for colorectal cancer

Pathology reporting of colorectal cancer (CRC) follows the International Collaboration on Cancer Rep...

A systematic review of early neuroimaging and neurophysiological biomarkers for post-stroke mobility prognostication

Accurate prognostication of mobility outcomes is essential to guide rehabilitation and manage patien...

Real-Time EEG-Based Epileptic Seizure Prediction Using Artificial Intelligence: A Systematic Review

Epilepsy affects approximately 50 million people worldwide, and seizures remain difficult to predict...

Costing Methods for Artificial Intelligence: Systematic Review and Recommended Cost Inventory for in Health Technology Assessment

Economic evaluations of artificial intelligence (AI) in healthcare are expanding rapidly, yet underl...

Patient-Reported Challenges in Lymphoma Diagnosis: Analysis of Online Forum Narratives Using Artificial Intelligence

Lymphoma diagnosis remains challenging due to diverse subtypes and nonspecific presentations. While ...

TabGraphSyn: Graph-Guided Latent Diffusion for High-Fidelity and Privacy-Conscious Clinical Data Generation

The critical need for accessible patient data in clinical research is often hindered by privacy regu...

Demographics, Overlap, and Latency of Severe Cutaneous Adverse Reactions in an FDA Database

Severe cutaneous adverse reactions (SCARs), including Stevens-Johnson syndrome/toxic epidermal necro...

Evaluation of SSI risk prediction model after spinal surgery: A systematic review and critical appraisal

This study aimed to systematically review and critically evaluate the risk of bias and applicability...

Machine learning-enabled risk prediction of self-neglect among community-dwelling older adults in China.

BACKGROUND: Elder self-neglect (ESN) is usually ignored as a private problem and impairs the health ...

Jan 2025 39814081
[Risk prediction of Reduning Injection batches by near-infrared spectroscopy combined with multiple machine learning algorithms].

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial pr...

Jan 2025 39929624
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