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Characterization of Biological Absorption Spectra Spanning the Visible to the Short-Wave Infrared.
J Vis Exp
January 2025
Department of Biomedical Engineering, Washington University in St. Louis; Department of Obstetrics & Gynecology, Washington University in St. Louis;
For noninvasive light-based physiological monitoring, optimal wavelengths of individual tissue components can be identified using absorption spectroscopy. However, because of the lack of sensitivity of hardware at longer wavelengths, absorption spectroscopy has typically been applied for wavelengths in the visible (VIS) and near-infrared (NIR) range from 400 to 1,000 nm. Hardware advancements in the short-wave infrared (SWIR) range have enabled investigators to explore wavelengths in the ~1,000 nm to 3,000 nm range in which fall characteristic absorption peaks for lipid, protein, and water.
View Article and Find Full Text PDFMisses and Near Misses in Paediatric Appendicitis: An Eight-Year, Single-Centre Retrospective Review.
Acta Paediatr
January 2025
Department of Pathology, Sourasky Medical Center, Tel Aviv, Israel.
Aim: Diagnostic error can result in the appendectomy of a normal appendix, commonly known as negative appendectomy (NA). Missed appendicitis (MA) is related to a poor outcome. The aim of this study was to determine whether there are factors in presentation associated with NA or MA.
View Article and Find Full Text PDFLarge Language Models Outperform Traditional Natural Language Processing Methods in Extracting Patient-Reported Outcomes in Inflammatory Bowel Disease.
Gastro Hep Adv
October 2024
Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California.
Background And Aims: Patient-reported outcomes (PROs) are vital in assessing disease activity and treatment outcomes in inflammatory bowel disease (IBD). However, manual extraction of these PROs from the free-text of clinical notes is burdensome. We aimed to improve data curation from free-text information in the electronic health record, making it more available for research and quality improvement.
View Article and Find Full Text PDFA Deep Learning Framework for Automated Classification and Archiving of Orthodontic Diagnostic Documents.
Cureus
December 2024
Department of Orthodontics, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, IRN.
Background Orthodontic diagnostic workflows often rely on manual classification and archiving of large volumes of patient images, a process that is both time-consuming and prone to errors such as mislabeling and incomplete documentation. These challenges can compromise treatment accuracy and overall patient care. To address these issues, we propose an artificial intelligence (AI)-driven deep learning framework based on convolutional neural networks (CNNs) to automate the classification and archiving of orthodontic diagnostic images.
View Article and Find Full Text PDFDiagnostic inequalities relating to physical healthcare among people with mental health conditions: a systematic review.
EClinicalMedicine
February 2025
The Healthcare Improvement Studies (THIS) Institute, University of Cambridge, Cambridge, UK.
Background: Inaccurate diagnosis of physical health problems in people with mental health conditions may contribute to poorer health outcomes. We review the evidence on whether individuals with mental health conditions are at risk of diagnostic inequalities related to their physical health.
Methods: We searched MEDLINE, PsycINFO, Embase, and CINAHL, 1 September 2002-18 Septemebr 2024 (PROSPERO 2022: CRD42022375892).
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