AIMC Topic: Research Design

Clear Filters Showing 581 to 590 of 682 articles

[Artificial intelligence for randomized controlled trials in cardiology: applications and future perspectives].

Giornale italiano di cardiologia (2006)
Integrating artificial intelligence (AI) into cardiovascular clinical trials is emerging as a key factor in streamlining patient selection, data collection, endpoint monitoring, and outcome analysis. On the one hand, machine learning and deep learnin...

A systematic methodological evaluation of sepsis guidelines: Protocol for quality assessment and consistency of recommendations.

Acta anaesthesiologica Scandinavica
BACKGROUND: Sepsis is a leading cause of mortality worldwide, characterized by a dysregulated host response to infection. Despite the development of multiple clinical practice guidelines (CPGs) to standardize sepsis management, substantial variabilit...

Artificial intelligence for difficult airway assessment: a protocol for a systematic review with meta-analysis.

BMJ open
INTRODUCTION: Identifying difficult airways and avoiding unanticipated difficult airways through difficult airway assessment are crucial for patient safety prior to airway management. Therefore, accurately predicting difficult airways through airway ...

Comprehensive reporting guidelines and checklist for studies developing and utilizing artificial intelligence models.

Korean journal of anesthesiology
BACKGROUND: The rapid advancement of artificial intelligence (AI) in healthcare necessitates comprehensive and standardized reporting guidelines to ensure transparency, reproducibility, and ethical applications in clinical research. Existing reportin...

Clinical Trial Design Approach to Auditing Language Models in Health Care Setting.

JCO clinical cancer informatics
PURPOSE: Rapid advancements in natural language processing have led to the development of sophisticated language models. Inspired by their success, these models are now used in health care for tasks such as clinical documentation and medical record c...

Artificial Intelligence and Machine Learning Innovations to Improve Design and Representativeness in Oncology Clinical Trials.

American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
The integration of artificial intelligence (AI) and machine learning (ML) in oncology clinical trials is rapidly evolving alongside the broader field. For example, AI-driven adaptive trial designs may allow for real-time modifications based on emergi...

AI-DBS study: protocol for a longitudinal prospective observational cohort study of patients with Parkinson's disease for the development of neuronal fingerprints using artificial intelligence.

BMJ open
INTRODUCTION: Deep brain stimulation (DBS) is a proven effective treatment for Parkinson's disease (PD). However, titrating DBS stimulation parameters is a labourious process and requires frequent hospital visits. Additionally, its current applicatio...

Explosion of formulaic research articles, including inappropriate study designs and false discoveries, based on the NHANES US national health database.

PLoS biology
With the growth of artificial intelligence (AI)-ready datasets such as the National Health and Nutrition Examination Survey (NHANES), new opportunities for data-driven research are being created, but also generating risks of data exploitation by pape...