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| http://dx.doi.org/10.5664/jcsm.1798 | DOI Listing |
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The Added Effect of Artificial Intelligence in CT Assessment of Abdominal Lymphadenopathy.
Lymphology
January 2024
Medical Biophysics Department, Medical Research Institute, Alexandria University, Alexandria, Egypt.
Lymphadenopathy is associated with lymph node abnormal size or consistency due to many causes. We employed the deep convolutional neural network ResNet-34 to detect and classify CT images from patients with abdominal lymphadenopathy and healthy controls. We created a single database containing 1400 source CT images for patients with abdominal lymphadenopathy (n = 700) and healthy controls (n = 700).
View Article and Find Full Text PDFDual-energy CT iodine concentration as a biomarker for immunotherapy treatment response in metastatic melanoma and renal cell carcinoma patients.
Eur Radiol
January 2025
Department of Radiology, University of Washington, Seattle, WA, USA.
Objective: To investigate the predictive value of tumor iodine concentration obtained with dual-energy CT (DECT) for treatment response in patients treated with immune checkpoint inhibitors (ICI).
Materials And Methods: Retrospective single-center study of consecutive metastatic melanoma and renal cell carcinoma (RCC) patients undergoing first-line ICI treatment. The iodine concentration measurement time points include prior to initiation of therapy (baseline [BL]), after initiation (follow-up [FU1]), and either time point nearest to 12 months or at time of progression (final follow-up [FFU]).
Effects of Photobiomodulation on Burning Mouth Syndrome: A Systematic Review and Meta-Analysis.
J Oral Rehabil
January 2025
Universidade Federal de São Paulo-Escola Paulista de Medicina-UNIFESP-EPM, São Paulo, Brazil.
Objective: The objective of this research is to evaluate the effectiveness and safety of photobiomodulation or low-level laser therapy on burning mouth syndrome compared to placebo, no-laser, clonazepam and alpha-lipoic acid.
Methods: A systematic review of randomised clinical trials was performed. The databases consulted were MEDLINE, CENTRAL, LILACS, EMBASE and clinical trial registries ClincalTrial.
Evaluating Computerised Assessment of Motor Imitation (CAMI) for identifying autism-specific difficulties not observed for attention-deficit hyperactivity disorder or neurotypical development.
Br J Psychiatry
January 2025
Department of Psychology, Nottingham Trent University, UK; and Institute of Human Sciences, University of Oxford, UK.
Background: Reliable and specific biomarkers that can distinguish autism spectrum disorders (ASDs) from commonly co-occurring attention-deficit/hyperactivity disorder (ADHD) are lacking, causing misses and delays in diagnosis, and reducing access to interventions and quality of life.
Aims: To examine whether an innovative, brief (1-min), videogame method called Computerised Assessment of Motor Imitation (CAMI), can identify ASD-specific imitation differences compared with neurotypical children and children with ADHD.
Method: This cross-sectional study used CAMI alongside standardised parent-report (Social Responsiveness Scale, Second Edition) and observational measures of autism (Autism Diagnostic Observation Schedule-Second Edition; ADOS-2), ADHD (Conners) and motor ability (Physical and Neurological Examination for Soft Signs).
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