Clinical Trials

Machine learning validation of the AVAS classification compared to ultrasound mapping in a multicentre study.

The Arteriovenous Access Stage (AVAS) classification simplifies information about suitability of ves...

Deep learning-based defect detection in film-coated tablets using a convolutional neural network.

Film-coating is a critical step in pharmaceutical manufacturing. Traditional visual inspections for ...

Using artificial intelligence to semi-automate trustworthiness assessment of randomized controlled trials: a case study.

BACKGROUND AND OBJECTIVE: Randomized controlled trials (RCTs) are the cornerstone of evidence-based ...

Automatic machine learning accurately predicts the efficacy of immunotherapy for patients with inoperable advanced non-small cell lung cancer using a computed tomography-based radiomics model.

PURPOSE: Patients with advanced non-small cell lung cancer (NSCLC) have varying responses to immunot...

Artificial intelligence and machine learning in veterinary medicine: a regulatory perspective on current initiatives and future prospects.

The US FDA's Center for Veterinary Medicine (CVM) is advancing its leadership in veterinary science ...

The regulatory landscape of 5' UTRs in translational control during zebrafish embryogenesis.

The 5' UTRs of mRNAs are critical for translation regulation during development, but their in vivo r...

Characterizing the microbiome recruited by the endangered plant in phosphorus-deficient acidic soil.

Phosphorus (P)-deficient soils serve as crucial habitats for endangered plant species. Microbiomes p...

Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial.

BACKGROUND: With increasing adoption of remote clinical trials in digital mental health, identifying...

An integrative approach to generating explainable safety assessment scenarios for autonomous vehicles based on Vision Transformer and SHAP.

Automated Vehicles (AVs) are on the cusp of commercialization, prompting global governments to organ...

Artificial Intelligence-Driven Translation Tools in Intensive Care Units for Enhancing Communication and Research.

UNLABELLED: There is a need to improve communication for patients and relatives who belong to cultur...

Leveraging Large Language Models to Enhance Dermatology Clinical Trial Patient Recruitment and Retention.

A graph neural network-based model with out-of-distribution robustness for enhancing antiretroviral therapy outcome prediction for HIV-1.

Predicting the outcome of antiretroviral therapies (ART) for HIV-1 is a pressing clinical challenge,...

ImpACT Project: Improving Access to Clinical Trials in Victoria, an Artificial Intelligence-Based Approach.

PURPOSE: Enhancing the speed and efficiency of clinical trial recruitment is a key objective across ...

Toward Resolving Heterogeneous Mixtures of Nanocarriers in Drug Delivery Systems through Light Scattering and Machine Learning.

Nanocarriers (NCs) have emerged as a revolutionary approach in targeted drug delivery, promising to ...

Raman Spectroscopy and Exosome-Based Machine Learning Predicts the Efficacy of Neoadjuvant Therapy for HER2-Positive Breast Cancer.

Early prediction of the neoadjuvant therapy efficacy for HER2-positive breast cancer is crucial for ...

A narrative review focusing on randomized clinical trials of vitamin D supplementation for COVID-19 disease.

Current evidence is inconsistent on whether vitamin D supplementation can prevent COVID-19 infection...

Spatiotemporal multi-feature fusion vehicle trajectory anomaly detection for intelligent transportation: An improved method combining autoencoders and dynamic Bayesian networks.

With the continuous development of intelligent transportation systems, traffic safety has become a m...

Personalized stress optimization intervention to reduce adolescents' anxiety: A randomized controlled trial leveraging machine learning.

Anxiety symptoms are among the most prevalent mental health disorders in adolescents, highlighting t...

Evaluating generalizability of oncology trial results to real-world patients using machine learning-based trial emulations.

Randomized controlled trials (RCTs) evaluating anti-cancer agents often lack generalizability to rea...

A novel non-invasive murine model for rapidly testing drug activity via inhalation administration against .

The efficacy of many compounds against is often limited when administered via conventional oral or ...

Predicting rapid progression in knee osteoarthritis: a novel and interpretable automated machine learning approach, with specific focus on young patients and early disease.

OBJECTIVES: To facilitate the stratification of patients with osteoarthritis (OA) for new treatment ...