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...

Oct 2024 39447842
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...

Oct 2024 39453506
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...

Oct 2024 39446771
OSAIRIS: Lessons Learned From the Hospital-Based Implementation and Evaluation of an Open-Source Deep-Learning Model for Radiotherapy Image Segmentation.

Several studies report the benefits and accuracy of using autosegmentation for organ at risk (OAR) o...

Oct 2024 39522322
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 ...

Oct 2024 39413064
Enhanced drug classification using machine learning with multiplexed cardiac contractility assays.

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

Oct 2024 39396765
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...

Oct 2024 39998535
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 ...

Oct 2024 39389283
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...

Oct 2024 39378791
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...

Oct 2024 39362109
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...

Sep 2024 39348420
Investigation of a surrogate measure-based safety index for predicting injury crashes at signalized intersections.

OBJECTIVES: The paper develops a machine learning-based safety index for classifying traffic conflic...

Sep 2024 39325686
The Impact of Medical Explainable Artificial Intelligence on Nurses' Innovation Behaviour: A Structural Equation Modelling Approach.

This study aims to investigate the influence of medical explainable artificial intelligence (XAI) o...

Sep 2024 40224836
Randomized controlled trial of an artificial intelligence diagnostic system for the detection of esophageal squamous cell carcinoma in clinical practice.

BACKGROUND: Artificial intelligence (AI) has made remarkable progress in image recognition using dee...

Sep 2024 39317205
How can quantum computing be applied in clinical trial design and optimization?

Clinical trials are necessary for assessing the safety and efficacy of treatments. However, trial ti...

Sep 2024 39317621
Machine learning approaches to evaluate heterogeneous treatment effects in randomized controlled trials: a scoping review.

BACKGROUND AND OBJECTIVES: Estimating heterogeneous treatment effects (HTEs) in randomized controlle...

Sep 2024 39305940
Using deep learning and pretreatment EEG to predict response to sertraline, bupropion, and placebo.

OBJECTIVE: Predicting an individual's response to antidepressant medication remains one of the most ...

Sep 2024 39332081
Sensory Stimulation and Robot-Assisted Arm Training After Stroke: A Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Functional recovery after stroke is often limited, despite various treatment...

Sep 2024 38912852
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