Stem Cell Research

Advances and applications in tumor organoid research Harnessing human tumor organoids for cancer modeling and precision therapy.

Human tumor organoids represent a paradigm shift in cancer modeling, overcoming critical limitations of conventional systems by faithfully recapitulating genetic heterogeneity, three-dimensional architecture, and tumor microenvironment dynamics of patient tumors. Our review explores how human tumor organoids serve as a transformative preclinical platform, bridging the gap between basic research an...

A Flexible Hybrid Quantum-classical Training Framework of Organ-at-Risk and Tumor Segmentation Models for Radiation Therapy Planning.

Deep learning-based Organ-at-Risk (OAR) and tumor segmentation is vital for radiation therapy planning but often suffers from over-parameterization, requiring large datasets to avoid overfitting, which is impractical in small-sample medical settings. Traditional trainable parameter reduction methods, relying on structural lightweighting or low-rank approximation, may artificially limit model expre...

Use of smart glasses for ultrasound-guided radial arterial catheterisation in obese patients: study protocol for a single-centre randomised clinical trial in China.

INTRODUCTION: Ultrasound guidance improves the success rate and efficiency of radial arterial catheterisation (RAC). However, the procedure remains mo...

Development of a Predictive Calculator for the Need for Abdominoperineal Resection after Chemoradiation Therapy in Anal Squamous Cell Carcinoma.

BACKGROUND: Chemoradiation therapy (CRT) is standard treatment for anal squamous cell carcinoma (ASCC). Abdominoperineal resection (APR) is usually re...

Spatiotemporal Remodeling of Bone as a Reversibly Adaptive Biological Material in Djungarian Hamsters under Regulated Photoperiod Conditions.

Bone loss in humans is typically progressive and difficult to reverse, posing challenges for both pharmacological therapy and the long-term performanc...

Natural and Artificial Hematopoietic Cell Reprogramming.

Hematopoietic cell reprogramming, defined as the conversion from one hematopoietic or immune cell type into another, has been shown to hold transforma...

Responsible AI in Canadian Healthcare: Evaluation Frameworks, Challenges, and Policy Directions.

Artificial intelligence (AI) is transforming healthcare through advances in imaging, predictive analytics, and workflow optimization. However, its ado...

Artificial intelligence to improve the detection and risk stratification of acute pulmonary embolism (AID-PE): protocol for a pragmatic quasi-experimental comparator study.

INTRODUCTION: Pulmonary embolism (PE) is a potentially fatal condition requiring timely diagnosis and treatment. CT pulmonary angiography (CTPA) is th...

The use of advanced machine learning to predict outcomes after atezolizumab plus bevacizumab for advanced hepatocellular carcinoma: a retrospective cohort study.

BACKGROUND: Combination immune checkpoint inhibitors are recommended as first-line therapy for advanced hepatocellular carcinoma. However, only a thir...

AI-Enhanced Continuing Professional Development as an Evolving Sociotechnical System: Multimethod Theoretical Framework Development Study.

BACKGROUND: Artificial intelligence (AI) is changing continuing professional development (CPD) in health care and its interactions with the broader he...

AI help in grant proposals tied to higher funding odds at NIH.

Comparison and validation of multiple machine learning algorithms for predicting MDRO infection in catheter-related bloodstream patients: a multicenter cohort study.

UNLABELLED: Early identification of patients at high risk for multidrug-resistant organism (MDRO) infection in catheter-related bloodstream infection ...

Advancing prussian blue nanoparticle-mediated photothermal therapy through machine learning and multiomics integration.

Prussian blue nanoparticles (PBNPs) are a versatile platform for administering photothermal therapy (PTT) in cancer therapy applications. PBNPs combin...

State and Diffusion of National Institutes of Health Funding of AI in Radiology.

Artificial intelligence research has profound implications for the future of radiology, making it essential to understand funding patterns and diffusi...

Artificial Intelligence for Gastroenterology Practice: A Modified Delphi Consensus.

BACKGROUND: The American College of Gastroenterology (ACG) assembled a multidisciplinary task force to evaluate the current state and future direction...

Integration of Multi-Omics and Machine Learning Identifies TGFB1 and SERPINE1 as Biomarkers of Vascular Smooth Muscle Cell Senescence in Intracranial Aneurysms.

Intracranial aneurysms (IAs) are severe cerebrovascular disorders lacking effective gene therapy or pharmacological interventions. Vascular smooth mus...

Practical machine learning model for early and accurate prediction of disseminated intravascular coagulation before its progression to an overt stage.

BACKGROUND AND AIMS: In patients with sepsis, anticoagulant therapy is expected to have maximal efficacy when administered before the development of s...

Understanding patient experience during Lokomat rehabilitation in children and adolescents: a clinical observational study combining self-evaluation and physiological metrics.

OBJECTIVES: To examine the emotional, cognitive and dispositional experience of children and adolescents undergoing Lokomat rehabilitation by integrat...

Data-driven multiscale design of composite biomaterials: Integrating experiments, imaging, and computational modeling for biomedical engineering.

Composite biomaterials are central to biomedical engineering, where implants and scaffolds must simultaneously meet mechanical, biological, and functi...

Dental students' knowledge, perceptions, and educational needs regarding artificial intelligence: a multinational cross-sectional survey.

AIMS: To explore undergraduate dental students' AI knowledge, perceptions, and concerns, and to identify their educational needs based on these findin...