Clinical Trials

Insights into the use of artificial intelligence in the drug discovery and delivery of nanosystems for the treatment of infectious diseases and neoplasms.

Artificial Intelligence (AI) has become a fundamental driver of scientific progress, particularly in disease diagnosis, drug development, and drug delivery optimization. The intersection of AI, drug design, and nanosystems for delivery is accelerating the advancement of personalized nanomedicines and innovative diananostic and therapeutic approaches. This narrative review explores the integration ...

Two‑tier prediction framework with OR‑voting for real‑time freeway secondary-crash prediction: Balancing sensitivity and specificity.

OBJECTIVES: Secondary crashes on freeways pose significant safety risks and are often preventable with timely intervention. This study aims to develop a real-time prediction framework for secondary-crash risk using traffic flow precursor characteristics, enabling proactive traffic safety management. METHODS: A novel secondary-crash identification method based on a crash buffer and speed contour ma...

The role and mechanism of diosgenin glucoside in modulating megakaryopoiesis through promotion of autophagy via the AMPK/mTOR/ULK1 signaling pathway.

BACKGROUND: Radiation-induced thrombocytopenia (RIT) is a severe, dose-limiting complication of cancer radiotherapy with limited clinical management o...

Machine Learning Models for Predicting Pain, Fatigue, Depression, Anxiety, and Malnutrition in Cancer Patients: A Systematic Review and Meta-Analysis.

INTRODUCTION: Cancer-related symptoms including pain, fatigue, depression, anxiety, and malnutrition drive poor quality of life and adverse clinical o...

Assessment of atypical glandular cell interpretation in Pap tests using the Hologic Genius Digital Diagnostics System.

Atypical glandular cells (AGC) are a diagnostic challenge. The aim of this study was to evaluate the efficacy and diagnostic performance of AGC detect...

Manual, digital, and AI tumour-infiltrating lymphocyte scoring: a secondary analysis of the APHINITY randomised trial.

BACKGROUND: Stromal tumour-infiltrating lymphocytes (sTILs) are prognostic in early-stage HER2-positive breast cancer, but their role in the context o...

Automating cost-effectiveness models with agentic artificial intelligence: Case study and implications for value assessment.

BACKGROUND: Health economic modeling is conceptually sophisticated but operationally repetitive and resource intensive. Recent advances in large langu...

Evaluating the Accuracy, Empathy, and Readability of Generative AI Versus Registered Nurses in Discharge Planning: A Vignette-Based Study.

AIM: To compare the multidimensional performance of discharge instructions generated by generative AI (GPT-4) versus those created by clinical registe...

The Evolution and Global Impact of Uniportal Endoscopic Spine Surgery : A Korean Perspective and Historical Legacy.

Uniportal full-endoscopic spine surgery (FESS) has expanded over three decades from percutaneous discectomy to include multilevel decompression, endos...

Sample Size Reduction by Applying ML Based Causal Inference Methods.

We conducted a comprehensive comparative analysis of causal machine learning (ML) methods to assess their utility in improving the efficiency of clini...

Artificial Intelligence in Xenotransplantation: A Prioritized Roadmap for Early Clinical Translation, Opportunities and Challenges.

Xenotransplantation represents a potential solution to the persistent global organ shortage, yet its clinical application remains stalled by complex i...

Evaluation of Artificial Intelligence (AI) for Myocardial Infarction Health Information: Expert Accuracy Assessment and User Trust Survey.

BACKGROUND: Artificial intelligence chatbots, particularly ChatGPT, have emerged as increasingly popular sources of health information for the general...

From rules to foundation models: a comprehensive review of machine learning approaches for siRNA design.

Small interfering RNAs (siRNAs) are a clinically validated therapeutic modality with eight FDA-approved drugs, yet designing effective siRNAs remains ...

Artificial intelligence for translational personalized neoantigen cancer vaccine development.

Personalized neoantigen cancer vaccine is a promising strategy for precision immunotherapy by targeting patient-specific and mutation-derived tumor an...

Vaginal drug delivery for precision therapy in polyendocrine metabolic ovarian syndrome: emerging technologies, translational challenges and future perspectives.

INTRODUCTION: Polyendocrine Metabolic Ovarian Syndrome (PMOS) is an endocrine disorder characterized by metabolic dysfunction, hormonal imbalance, inf...

Artificial intelligence in Latin American hepatology: current evidence, implementation barriers, and strategic priorities.

Chronic liver diseases are an increasing cause of morbidity and mortality in Latin America, driven by the convergence of alcohol and metabolic-associa...

Evaluation of Large Language Model-Generated Recommendations in Glaucoma Surgical Decision-Making.

OBJECTIVE: To evaluate the utility, rationality, and safety of glaucoma surgery recommendations generated by three prominent large language models (LL...

Technology and Obesity: A Year in Review.

SMART technological advancements help diagnose, treat, and monitor various diseases at the earliest stages. It presents an opportunity to maintain the...

Predictive Safety in the Era of Artificial Intelligence: Promises, Limits, and the Case for an Enterprise Lifecycle Evidence Ecosystem.

Drug safety remains central to patient benefit, as maximizing the value of beneficial therapies requires recognition, appropriate characterization, an...

Artificial intelligence-driven study selection in systematic reviews of randomized controlled trials, emulated trials and economic evaluation studies using large language models.

Systematic reviews (SRs) are key to evidence-based medicine but are often labor-intensive, especially in the study selection step. This study assessed...