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Latest AI and machine learning research in surveys for healthcare professionals.

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Descriptive overview of AI applications in x-ray imaging and radiotherapy.

Artificial intelligence (AI) is transforming medical radiation applications by handling complex data...

Role of artificial intelligence in magnetic resonance imaging-based detection of temporomandibular joint disorder: a systematic review.

This systematic review aimed to evaluate the application of artificial intelligence (AI) in the iden...

Development of a short form of the Geriatric Depression Scale-30 based on item response theory and the RiskSLIM algorithm.

Recently, methods of quickly and accurately screening for geriatric depression have attracted substa...

Can artificial intelligence improve patient educational material readability? A systematic review and narrative synthesis.

Enhancing patient comprehension of their health is crucial in improving health outcomes. The integra...

Unveiling predictive factors for household-level stunting in India: A machine learning approach using NFHS-5 and satellite-driven data.

OBJECTIVES: Childhood stunting remains a significant public health issue in India, affecting approxi...

Enhancing drug discovery and patient care through advanced analytics with the power of NLP and machine learning in pharmaceutical data interpretation.

This study delves into the transformative potential of Machine Learning (ML) and Natural Language Pr...

Optimizing sequence data analysis using convolution neural network for the prediction of CNV bait positions.

BACKGROUND: Accurate prediction of copy number variations (CNVs) from targeted capture next-generati...

Embedded Ethics in Practice: A Toolbox for Integrating the Analysis of Ethical and Social Issues into Healthcare AI Research.

Integrating artificial intelligence (AI) into critical domains such as healthcare holds immense prom...

A comprehensive and bias-free machine learning approach for risk prediction of preeclampsia with severe features in a nulliparous study cohort.

Preeclampsia is one of the leading causes of maternal morbidity, with consequences during and after ...

Deep Learning-Enabled Rapid Metabolic Decoding of Small Extracellular Vesicles via Dual-Use Mass Spectroscopy Chip Array.

The increasing focus of small extracellular vesicles (sEVs) in liquid biopsy has created a significa...

Biosecurity measures reducing spp. and hepatitis E virus prevalence in pig farms-a systematic review and meta-analysis.

spp. and hepatitis E virus (HEV) are significant foodborne zoonotic pathogens that impact the healt...

Enhancing consistency and mitigating bias: A data replay approach for incremental learning.

Deep learning systems are prone to catastrophic forgetting when learning from a sequence of tasks, a...

Healthcare ethics and artificial intelligence: a UK doctor survey.

OBJECTIVES: To survey UK doctors on their uses of artificial intelligence (AI) and of their views on...

Early Attrition Prediction for Web-Based Interpretation Bias Modification to Reduce Anxious Thinking: A Machine Learning Study.

BACKGROUND: Digital mental health is a promising paradigm for individualized, patient-driven health ...

Reliability of post-contrast deep learning-based highly accelerated cardiac cine MRI for the assessment of ventricular function.

OBJECTIVE: The total examination time can be reduced if high-quality two-dimensional (2D) cine image...

Enhancing AI reliability: A foundation model with uncertainty estimation for optical coherence tomography-based retinal disease diagnosis.

Inability to express the confidence level and detect unseen disease classes limits the clinical impl...

Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson's Disease Mobility Assessments.

Mobility tasks like the Timed Up and Go test (TUG), cognitive TUG (cogTUG), and walking with turns p...

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