AIMC Topic: Research Design

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Artificial intelligence (AI) for paediatric fracture detection: a multireader multicase (MRMC) study protocol.

BMJ open
INTRODUCTION: Paediatric fractures are common but can be easily missed on radiography leading to potentially serious implications including long-term pain, disability and missed opportunities for safeguarding in cases of inflicted injury. Artificial ...

Artificial intelligence applied in human health technology assessment: a scoping review protocol.

JBI evidence synthesis
OBJECTIVE: This scoping review aims to map studies that applied artificial intelligence (AI) tools to perform health technology assessment tasks in human health care. The review also aims to understand specific processes in which the AI tools were ap...

Integrating large language models in systematic reviews: a framework and case study using ROBINS-I for risk of bias assessment.

BMJ evidence-based medicine
Large language models (LLMs) may facilitate and expedite systematic reviews, although the approach to integrate LLMs in the review process is unclear. This study evaluates GPT-4 agreement with human reviewers in assessing the risk of bias using the R...

Pilot study protocol evaluating the impact of telerobotics interactions with autistic children during a Denver intervention on communication skills using single-case experimental design.

BMJ open
INTRODUCTION: For several years, studies have been conducted on the contribution of social robots as an intervention tool for children with autism spectrum disorder (ASD). One of the early intervention models recommended by the French National Author...

Optimising the production of PLGA nanoparticles by combining design of experiment and machine learning.

International journal of pharmaceutics
Poly(lactic-co-glycolic acid) (PLGA) is a widely used biodegradable polymer in drug delivery and nanoparticle (NP) formulation due to its controlled drug release properties and safety profiles. Among the methods available for NP production, nanopreci...

An evaluation of the performance of stopping rules in AI-aided screening for psychological meta-analytical research.

Research synthesis methods
Several AI-aided screening tools have emerged to tackle the ever-expanding body of literature. These tools employ active learning, where algorithms sort abstracts based on human feedback. However, researchers using these tools face a crucial dilemma:...

Larger and more instructable language models become less reliable.

Nature
The prevailing methods to make large language models more powerful and amenable have been based on continuous scaling up (that is, increasing their size, data volume and computational resources) and bespoke shaping up (including post-filtering, fine ...

How can quantum computing be applied in clinical trial design and optimization?

Trends in pharmacological sciences
Clinical trials are necessary for assessing the safety and efficacy of treatments. However, trial timelines are severely delayed with minimal success due to a multitude of factors, including imperfect trial site selection, cohort recruitment challeng...

Trial Factors Associated With Completion of Clinical Trials Evaluating AI: Retrospective Case-Control Study.

Journal of medical Internet research
BACKGROUND: Evaluation of artificial intelligence (AI) tools in clinical trials remains the gold standard for translation into clinical settings. However, design factors associated with successful trial completion and the common reasons for trial fai...

Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies Using AI (QUADAS-AI): Protocol for a Qualitative Study.

JMIR research protocols
BACKGROUND: Quality assessment of diagnostic accuracy studies (QUADAS), and more recently QUADAS-2, were developed to aid the evaluation of methodological quality within primary diagnostic accuracy studies. However, its current form, QUADAS-2 does no...