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

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Electronic Health Record-Based Prediction Models to Inform Decisions about HIV Pre-exposure Prophylaxis: A Systematic Review

Several clinical prediction models have been developed using electronic health records data to help ...

The Inherited Retinal Disease Pathway in the United Kingdom: a Patient Perspective and the Potential of AI

Inherited Retinal Diseases (IRDs) are the leading cause of blindness in young people in the UK. Desp...

Integrating Multidimensional Data Analytics for Precision Diagnosis of Chronic Low Back Pain

Low back pain (LBP) is a leading cause of disability worldwide, with up to 25% of cases become chron...

Underdiagnosis Bias of Chest Radiograph Diagnostic AI can be Decomposed and Mitigated via Dataset Bias Attributions

Inequitable diagnostic accuracy is a broad concern in AI-based models. However, current characteriza...

Evaluating the Diagnostic and Treatment Recommendation Capabilities of GPT-4 Vision in Dermatology

The integration of artificial intelligence (AI) in dermatology presents a promising frontier for enh...

VR-based Gamma Sensory Stimulation: A feasibility study

Alzheimer’s disease (AD) presents a critical global health challenge, with current therapies offerin...

Generative AI Mitigates Representation Bias and Improves Model Fairness Through Synthetic Health Data

Representation bias in health data can lead to unfair decisions and compromise the generalisability ...

Development and validation of a multivariable Prediction Model for Pre-diabetes and Diabetes using Easily Obtainable Clinical Data

In the US, pre-diabetes and diabetes are increasing in prevalence alongside other chronic diseases. ...

Quantifying Device Type and Handedness Biases in a Remote Parkinson’s Disease AI-Powered Assessment

Early detection of Parkinson’s Disease (PD) can enable early access to care, improving patient outco...

Advancing the prediction and understanding of placebo responses in chronic back pain using large language models

Placebo analgesia in chronic pain is a widely studied clinical phenomenon, where expectations about ...

Fair machine learning models for disease prediction: In-depth interviews with key health experts

Artificial intelligence (AI) and machine learning (ML) pose enormous potential for improving quality...

Assessing the Limitations of Large Language Models in Clinical Practice Guideline-concordant Treatment Decision-making on Real-world Data

Large Language Models (LLMs) have shown promise in therapeutic decision-making comparable to medical...

The Clinical Value of ChatGPT for Epilepsy Presurgical Decision Making: Systematic Evaluation on Seizure Semiology Interpretation

For patients with drug-resistant focal epilepsy (DRE), surgical resection of the epileptogenic zone ...

Artificial Intelligence (AI) Models for Cardiovascular Disease Risk Prediction in Primary and Ambulatory Care: A Scoping Review

Mortality from cardiovascular disease (CVD) has seen a dramatic increase over the past decades, whic...

Ovarian cancer recurrence prediction: comparing confirmatory to real world predictors with machine learning

Ovarian cancer is one of the deadliest cancers in women, with a 5-year survival rate of 17-28% in ad...

Is Multimodal Better? A Systematic Review of Multimodal versus Unimodal Machine Learning in Clinical Decision-Making

Machine learning has demonstrated success in clinical decision-making, yet the added value of multim...

Socio-Demographic Modifiers Shape Large Language Models’ Ethical Decisions

Large language models’ (LLMs) alignment with ethical standards is unclear. We tested whether LLMs sh...

Evaluating the Reliability of a Custom GPT in Full-Text Screening of a Systematic Review

Systematic reviewing is a time-consuming process that can be aided by artificial intelligence (AI). ...

Analyzing the Capacity of ChatGPT and Google to Provide Medical Information: Insights from Umbilical Cord Clamping

The optimal timing of umbilical cord clamping in neonatal care has been a subject of debate for deca...

AI-Driven and Automated Continuous Oxygen Saturation Monitoring and LTOT: A Systematic Review

Long-term oxygen therapy (LTOT) is essential for patients with chronic hypoxemia, particularly due t...

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