The broad availability of cheap three-dimensional (3D) printing equipment has raised the need for a thorough analysis on its effects on clinical accuracy. Our aim is to determine whether the accuracy of 3D printing process is affected by the use of a low-budget workflow based on open source software and consumer's commercially available 3D printers. A group of test objects was scanned with a 64-slice computed tomography (CT) in order to build their 3D copies. CT datasets were elaborated using a software chain based on three free and open source software. Objects were printed out with a commercially available 3D printer. Both the 3D copies and the test objects were measured using a digital professional caliper. Overall, the objects' mean absolute difference between test objects and 3D copies is 0.23 mm and the mean relative difference amounts to 0.55 %. Our results demonstrate that the accuracy of 3D printing process remains high despite the use of a low-budget workflow.
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http://dx.doi.org/10.1007/s10278-015-9810-8 | DOI Listing |
Am J Sports Med
January 2025
Department of Orthopaedic Surgery, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA.
Background: Osteochondral allograft transplantation (OCA) is well established as a viable chondral restoration procedure for the treatment of symptomatic, focal chondral defects of the knee. The efficacy of secondary OCA in the setting of failed index cartilage repair or restoration is poorly understood.
Purpose: To evaluate radiographic and clinical outcomes, failures, and reoperations after OCA after failed index cartilage repair or restoration of the knee.
PLoS One
January 2025
Department of English and Communication, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China.
This study aims to provide an LLM (Large Language Model)-based method for the discourse analysis of media attitudes, and thereby investigate media attitudes towards China in a Hong Kong-based newspaper. Analysis of attitudes in large amounts of media data is crucial for understanding public opinions, market trends, social dynamics, etc. However, corpus-based approaches have traditionally focused on explicit linguistic expressions of attitudes, leaving implicit expressions unconsidered.
View Article and Find Full Text PDFMed Teach
January 2025
Tufts University School of Medicine, Boston, Massachusetts, USA.
Purpose: To explore graduating medical students' insights on the value of coaching experiences during each year of medical school while examining how coaching may support student development at various stages of training.
Methods: We invited all graduating students who participated in the coaching program from first through fourth year to participate in one 90-minute virtual focus group. We conducted a thematic analysis of all the focus group transcripts using inductive open coding to develop themes.
Neuroinformatics
January 2025
Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA.
This paper introduces the Automated Lesion and Feature Extraction (ALFE) pipeline, an open-source, Python-based pipeline that consumes MR images of the brain and produces anatomical segmentations, lesion segmentations, and human-interpretable imaging features describing the lesions in the brain. ALFE pipeline is modeled after the neuroradiology workflow and generates features that can be used by physicians for quantitative analysis of clinical brain MRIs and for machine learning applications. The pipeline uses a decoupled design which allows the user to customize the image processing, image registrations, and AI segmentation tools without the need to change the business logic of the pipeline.
View Article and Find Full Text PDFJ Am Med Inform Assoc
December 2024
Department of Radiology, Stanford University, Stanford, CA 94304, United States.
Objective: Brief hospital course (BHC) summaries are clinical documents that summarize a patient's hospital stay. While large language models (LLMs) depict remarkable capabilities in automating real-world tasks, their capabilities for healthcare applications such as synthesizing BHCs from clinical notes have not been shown. We introduce a novel preprocessed dataset, the MIMIC-IV-BHC, encapsulating clinical note and BHC pairs to adapt LLMs for BHC synthesis.
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