Public Health & Policy

Clinical Trials

Latest AI and machine learning research in clinical trials for healthcare professionals.

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Novel glassbox based explainable boosting machine for fault detection in electrical power transmission system.

The reliable operation of electrical power transmission systems is crucial for ensuring consumer's s...

Digital health in stroke: a narrative review.

Digital health is significantly transforming stroke care, particularly in remote and economically di...

Machine learning based identification potential feature genes for prediction of drug efficacy in nonalcoholic steatohepatitis animal model.

BACKGROUND: Nonalcoholic Steatohepatitis (NASH) results from complex liver conditions involving meta...

Recruitment in Appalachian, Rural and Older Adult Populations in an Artificial Intelligence World: Study Using Human-Mediated Follow-Up.

BACKGROUND: Participant recruitment in rural and hard-to-reach (HTR) populations can present unique ...

Gauging road safety advances using a hybrid EWM-PROMETHEE II-DBSCAN model with machine learning.

INTRODUCTION: Enhancing road safety conditions alleviates socioeconomic hazards from traffic acciden...

LERCause: Deep learning approaches for causal sentence identification from nuclear safety reports.

Identifying causal sentences from nuclear incident reports is essential for advancing nuclear safety...

Feasibility of Artificial Intelligence Powered Adverse Event Analysis: Using a Large Language Model to Analyze Microwave Ablation Malfunction Data.

Determine if a large language model (LLM, GPT-4) can label and consolidate and analyze intervention...

Integrating ChatGPT in Orthopedic Education for Medical Undergraduates: Randomized Controlled Trial.

BACKGROUND: ChatGPT is a natural language processing model developed by OpenAI, which can be iterati...

Machine learning and natural language processing in clinical trial eligibility criteria parsing: a scoping review.

Automatic eligibility criteria parsing in clinical trials is crucial for cohort recruitment leading ...

Predicting drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra.

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) is widel...

Definition and Validation of Prognostic Phenotypes in Moderate Aortic Stenosis.

BACKGROUND: Adverse outcomes from moderate aortic stenosis (AS) may be caused by progression to seve...

Advancing aneurysm management: the potential of AI and machine learning in enhancing safety and predictive accuracy.

Cerebral aneurysm rupture, the predominant cause of non-traumatic subarachnoid hemorrhage, underscor...

Randomized algorithms for large-scale dictionary learning.

Dictionary learning is an important sparse representation algorithm which has been widely used in ma...

Prognostic enrichment for early-stage Huntington's disease: An explainable machine learning approach for clinical trial.

BACKGROUND: In Huntington's disease clinical trials, recruitment and stratification approaches prima...

Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.

To assess the value of deep learning in selecting the optimal embryo for in vitro fertilization, a m...

Unraveling the impact of therapeutic drug monitoring via machine learning for patients with sepsis.

Clinical studies investigating the benefits of beta-lactam therapeutic drug monitoring (TDM) among c...

Establishing the importance of co-creation and self-efficacy in creative collaboration with artificial intelligence.

The emergence of generative AI technologies has led to an increasing number of people collaborating ...

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