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http://dx.doi.org/10.1016/j.idnow.2023.104719 | DOI Listing |
Int Endod J
January 2025
Department of Endodontics and Restorative Dentistry, Faculty of Dental Medicine, University of Rijeka, Rijeka, Croatia.
Aim: This study aimed to evaluate the compliance of dentists in Croatia and the Czech Republic with endodontic recommendations and identify the subjective and objective factors influencing their adherence to them.
Methodology: A total of 1386 dentists from Croatia and the Czech Republic participated in an online survey through a self-administered, author-designed questionnaire. After excluding those who did not perform root canal treatments (RCT), 1376 responses (394 from Croatia and 982 from the Czech Republic) were statistically analysed.
J Am Med Inform Assoc
January 2025
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37212, United States.
Objective: The objectives of this study are to synthesize findings from recent research of retrieval-augmented generation (RAG) and large language models (LLMs) in biomedicine and provide clinical development guidelines to improve effectiveness.
Materials And Methods: We conducted a systematic literature review and a meta-analysis. The report was created in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 analysis.
Ophthalmol Ther
January 2025
Pediatric Ophthalmology and Strabismus Division, King Khaled Eye Specialist Hospital, Al Urubah Branche Rd., West Building 2nd Floor, 11462, Riyadh, Saudi Arabia.
Introduction: Persistent fetal vasculature (PFV) is a congenital anomaly associated with significant surgical challenges, including a high risk of postoperative retinal detachment (RD). This study aimed to evaluate the impact of surgical approach and axial length (AL) on RD risk and visual outcomes in pediatric PFV management.
Methods: A retrospective cohort study was conducted involving 76 eyes of 74 patients who underwent cataract surgery for PFV between 2014 and 2022.
Eur Radiol
January 2025
Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Objective: This study aimed to develop an open-source multimodal large language model (CXR-LLaVA) for interpreting chest X-ray images (CXRs), leveraging recent advances in large language models (LLMs) to potentially replicate the image interpretation skills of human radiologists.
Materials And Methods: For training, we collected 592,580 publicly available CXRs, of which 374,881 had labels for certain radiographic abnormalities (Dataset 1) and 217,699 provided free-text radiology reports (Dataset 2). After pre-training a vision transformer with Dataset 1, we integrated it with an LLM influenced by the LLaVA network.
Int Endod J
January 2025
School of Medicine and Dentistry, Griffith University, Gold Coast, Australia.
Introduction: Biofilms may show varying adherence strengths to dentine. This study quantified the shear force required for the detachment of multispecies biofilm from the dentine using fluid dynamic gauging (FDG) and computation fluid dynamics (CFD). To date this force has not been quantified.
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