AIMC Topic: Observational Studies as Topic

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Efficacy of Artificial Intelligence-Assisted Appliances in the Selection of Tooth Shade: Protocol for an Observational Study.

JMIR research protocols
BACKGROUND: Accurate shade matching in dentistry is crucial for achieving aesthetic outcomes, with increasing patient expectations driving advancements in shade selection technologies. Color perception is influenced by multiple factors such as incide...

Pretrained language models for semantics-aware data harmonisation of observational clinical studies in the era of big data.

BMC medical informatics and decision making
BACKGROUND: In clinical research, there is a strong drive to leverage big data from population cohort studies and routine electronic healthcare records to design new interventions, improve health outcomes and increase the efficiency of healthcare del...

Assessing the potential utility of large language models for assisting community health workers: protocol for a prospective, observational study in Rwanda.

BMJ open
INTRODUCTION: Community health workers (CHWs) are critical to healthcare delivery in low-resource settings but often lack formal clinical training, limiting their decision-making. Large language models (LLMs) could provide real-time, context-specific...

Development and validation of diagnostic and prognostic prediction tools for dental caries in young children through prospective and cross-sectional observational studies: a protocol.

BMJ open
INTRODUCTION: Dental caries is the most common oral disease worldwide, affecting up to 90% of children globally. It can lead to pain, infection and impaired quality of life. Early prevention is a key strategy for reducing the prevalence of dental car...

Does AI help humans make better decisions? A statistical evaluation framework for experimental and observational studies.

Proceedings of the National Academy of Sciences of the United States of America
The use of AI, or more generally data-driven algorithms, has become ubiquitous in today's society. Yet, in many cases and especially when stakes are high, humans still make final decisions. The critical question, therefore, is whether AI helps humans...

Predictive modelling of clinically significant depressive symptoms after coronary artery bypass graft surgery: protocol for a multicentre observational study in two Swiss hospitals (the PsyCor study).

BMJ open
INTRODUCTION: Coronary artery bypass grafting (CABG) remains one of the most commonly performed cardiac surgeries worldwide. Despite surgical advancements, a significant proportion of patients experience psychological distress following surgery, with...

Imaging analysis using Artificial Intelligence to predict outcomes after endovascular aortic aneurysm repair: protocol for a retrospective cohort study.

BMJ open
INTRODUCTION: Endovascular aortic aneurysm repair (EVAR) requires long-term surveillance to detect and treat postoperative complications. However, prediction models to optimise follow-up strategies are still lacking. The primary objective of this stu...

PREACT-digital: study protocol for a longitudinal, observational multicentre study on digital phenotypes of non-response to cognitive behavioural therapy for internalising disorders.

BMJ open
INTRODUCTION: Cognitive behavioural therapy (CBT) serves as a first-line treatment for internalising disorders (ID), encompassing depressive, anxiety or obsessive-compulsive disorders. Nonetheless, a substantial proportion of patients do not experien...

Jackalope Plus tool for post-coordination, ontology development, and precise mapping in observational health studies.

Scientific reports
Accurate mapping of complex health data to the OMOP CDM while preserving clinical nuance remains a challenge. We introduce Jackalope Plus, a novel tool leveraging SNOMED CT post-coordination and a GPT-4o mini LLM, to significantly enhance the precisi...