Clinical Trials

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...

Machine learning-assisted assessment of municipal solid waste thermal treatment efficacy via rapid image recognition and visual analysis.

Decentralized thermal treatment is a common method for municipal solid waste (MSW) disposal in rural...

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...

Efficacy and empathy of AI chatbots in answering frequently asked questions on oral oncology.

OBJECTIVES: Artificial intelligence chatbots have demonstrated feasibility and efficacy in improving...

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

Multimodal deep-learning model using pre-treatment endoscopic images and clinical information to predict efficacy of neoadjuvant chemotherapy in esophageal squamous cell carcinoma.

BACKGROUND: Neoadjuvant chemotherapy is standard for advanced esophageal squamous cell carcinoma, th...

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,...

The biomedical applications of artificial intelligence: an overview of decades of research.

A significant area of computer science called artificial intelligence (AI) is successfully applied t...

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 ...

The effect of renal function on the clinical outcomes and management of patients hospitalized with hyperglycemic crises.

BACKGROUND: The global prevalence of diabetes has been rising rapidly in recent years, leading to an...

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 ...

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 ...

Artificial intelligence in healthcare: transforming patient safety with intelligent systems-A systematic review.

INTRODUCTION: Adverse events in hospitals significantly compromise patient safety and trust in healt...

Research on the self-efficacy and resilience of female graduate students in the era of artificial intelligence: analysis of the mechanism of mobile phone dependence, anxiety and mentoring relationship.

PURPOSE: The purpose of this study is to investigate the impact of the employment situation on the a...

A randomized sequential allocation study on the optimum programmed intermittent epidural boluses interval time with different concentrations of ropivacaine combined with the dural puncture epidural technique for labor analgesia.

BACKGROUND: The combined technique of programmed intermittent epidural boluses (PIEB) and dural punc...

The efficacy of core decompression combined with regenerative therapy in early femoral head necrosis: a systematic review and meta-analysis involving 954 subjects.

BACKGROUND: The debate continues on whether combining core decompression (CD) with regenerative ther...

Prediction of clinical efficacy of acupuncture intervention on upper limb dysfunction after ischemic stroke based on machine learning: a study driven by DSA diagnostic reports data.

OBJECTIVE: To develop a machine learning-based model for predicting the clinical efficacy of acupunc...

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...

Deep learning-based prediction of HER2 status and trastuzumab treatment efficacy of gastric adenocarcinoma based on morphological features.

BACKGROUND: First-line treatment for advanced gastric adenocarcinoma (GAC) with human epidermal grow...

Optimizing the production and efficacy of antimicrobial bioactive compounds from in combating multi-drug-resistant pathogens.

BACKGROUND: The rise of antibiotic-resistant pathogens has intensified the search for novel antimicr...