AIMC Topic: Systematic Reviews as Topic
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Barriers and facilitators to nurses' adoption of artificial intelligence-driven solutions in clinical practice: a protocol for a systematic review of qualitative studies.
BMJ open
Aug 21, 2025
INTRODUCTION: Artificial intelligence (AI) technologies are increasingly being developed and deployed to support clinical decision-making, care delivery and patient monitoring in healthcare. However, the adoption of AI-driven solutions by nurses, who...
Evaluating a Customized Version of ChatGPT for Systematic Review Data Extraction in Health Research: Development and Usability Study.
JMIR formative research
Aug 11, 2025
BACKGROUND: Systematic reviews are essential for synthesizing research in health sciences; however, they are resource-intensive and prone to human error. The data extraction phase, in which key details of studies are identified and recorded in a syst...
Predicting patient deterioration with physiological data using AI: systematic review protocol.
BMJ health & care informatics
Aug 5, 2025
INTRODUCTION: The second iteration of the National Early Warning Score has been adopted widely within the UK and internationally. It uses routinely collected physiological measurements to standardise the assessment and response to acute illness. Its ...
Using a large language model (ChatGPT) to assess risk of bias in randomized controlled trials of medical interventions: protocol for a pilot study of interrater agreement with human reviewers.
BMC medical research methodology
Jul 31, 2025
BACKGROUND: Risk of bias (RoB) assessment is an essential part of systematic reviews that requires reading and understanding each eligible trial and RoB tools. RoB assessment is subject to human error and is time-consuming. Machine learning-based too...
Effectiveness of predictive scoring systems in predicting mortality in relation to baseline kidney function in adult intensive care unit patients: a systematic review protocol.
BMJ open
Jul 17, 2025
INTRODUCTION: Predictive scoring systems support clinicians in decision-making by estimating the prognosis of patients in intensive care units (ICUs). However, there is limited evidence on the accuracy of these systems in predicting mortality and org...
Integrating artificial intelligence in community-based diabetes care programmes: enhancing inclusiveness, diversity, equity and accessibility a realist review protocol.
BMJ open
Jul 15, 2025
INTRODUCTION: Marginalised populations-such as racialised groups, low-income individuals, newcomers and those in rural areas-disproportionately experience severe diabetes-related complications, including diabetic foot ulcers, retinopathy and amputati...
Large Language Models and the Analyses of Adherence to Reporting Guidelines in Systematic Reviews and Overviews of Reviews (PRISMA 2020 and PRIOR).
Journal of medical systems
Jun 12, 2025
In the context of Evidence-Based Practice (EBP), Systematic Reviews (SRs), Meta-Analyses (MAs) and overview of reviews have become cornerstones for the synthesis of research findings. The Preferred Reporting Items for Systematic Reviews and Meta-Anal...
Use of deep learning-based NLP models for full-text data elements extraction for systematic literature review tasks.
Scientific reports
Jun 3, 2025
Systematic literature review (SLR) is an important tool for Health Economics and Outcomes Research (HEOR) evidence synthesis. SLRs involve the identification and selection of pertinent publications and extraction of relevant data elements from full-t...
Do it faster with PICOS: Generative AI-Assisted systematic review screening.
Journal of biomedical informatics
May 28, 2025
BACKGROUND: Systematic reviews (SRs) require substantial time and human resources, especially during the screening phase. Large Language Models (LLMs) have shown the potential to expedite screening. However, their use in generating structured PICOS (...
Streamlining systematic reviews with large language models using prompt engineering and retrieval augmented generation.
BMC medical research methodology
May 10, 2025
BACKGROUND: Systematic reviews (SRs) are essential to formulate evidence-based guidelines but require time-consuming and costly literature screening. Large Language Models (LLMs) can be a powerful tool to expedite SRs.
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