Public Health & Policy

Clinical Trials

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

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Optimizing lipid nanoparticles for fetal gene delivery in vitro, ex vivo, and aided with machine learning.

There is a clinical need to develop lipid nanoparticles (LNPs) to deliver congenital therapies to th...

Artificial intelligence in rheumatology: perspectives and insights from a nationwide survey of U.S. rheumatology fellows.

Artificial Intelligence (AI) is poised to revolutionize healthcare by enhancing clinical practice, d...

Active Quantum Biomaterials-Enhanced Microrobots for Food Safety.

Timely disruptive tools for the detection of pathogens in foods are needed to face global health and...

Harnessing explainable artificial intelligence for patient-to-clinical-trial matching: A proof-of-concept pilot study using phase I oncology trials.

This study aims to develop explainable AI methods for matching patients with phase 1 oncology clinic...

Implementing AI-Driven Bed Sensors: Perspectives from Interdisciplinary Teams in Geriatric Care.

Sleep is a crucial aspect of geriatric assessment for hospitalized older adults, and implementing AI...

Enhancing self-directed learning with custom GPT AI facilitation among medical students: A randomized controlled trial.

OBJECTIVE: This study aims to assess the impact of LearnGuide, a specialized ChatGPT tool designed t...

Machine learning reveals prominent spontaneous behavioral changes and treatment efficacy in humanized and transgenic Alzheimer's disease models.

Computer-vision and machine-learning (ML) approaches are being developed to provide scalable, unbias...

TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs.

Characterization of breast parenchyma in dynamic contrast-enhanced magnetic resonance imaging (DCE-M...

Machine learning algorithms to predict treatment success for patients with pulmonary tuberculosis.

Despite advancements in detection and treatment, tuberculosis (TB), an infectious illness caused by ...

Enhanced drug classification using machine learning with multiplexed cardiac contractility assays.

Cardiac screening of newly discovered drugs remains a longstanding challenge for the pharmaceutical ...

Multi-label material and human risk factors recognition model for construction site safety management.

INTRODUCTION: Construction sites are prone to numerous safety risk factors, but safety managers have...

Learning to match patients to clinical trials using large language models.

OBJECTIVE: This study investigates the use of Large Language Models (LLMs) for matching patients to ...

Unraveling the determinants of traffic incident duration: A causal investigation using the framework of causal forests with debiased machine learning.

Predicting the duration of traffic incidents is challenging due to their stochastic nature. Accurate...

Uncertainty-aware probabilistic graph neural networks for road-level traffic crash prediction.

Traffic crashes present substantial challenges to human safety and socio-economic development in urb...

Managing spatio-temporal heterogeneity of susceptibles by embedding it into an homogeneous model: A mechanistic and deep learning study.

Accurate prediction of epidemics is pivotal for making well-informed decisions for the control of in...

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