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Background: Early detection of cognitive impairment is crucial for maximizing the benefits of disease-modifying treatments for Alzheimer's disease (AD). Brief, automatically-scored digital cognitive assessments such as the Digital Clock and Recall (DCR) show promise in streamlining this early detection. However, wide adoption of such assessments in diverse populations requires evaluation of their demographic biases.
View Article and Find Full Text PDFDeep learning-based automation for segmentation and biometric measurement of the gestational sac in ultrasound images.
Front Pediatr
December 2024
Department of Radiology, University of Lahore Teaching Hospital, Lahore, Pakistan.
Introduction: Monitoring the morphological features of the gestational sac (GS) and measuring the mean sac diameter (MSD) during early pregnancy are essential for predicting spontaneous miscarriage and estimating gestational age (GA). However, the manual process is labor-intensive and highly dependent on the sonographer's expertise. This study aims to develop an automated pipeline to assist sonographers in accurately segmenting the GS and estimating GA.
View Article and Find Full Text PDFTB or not TB? Development and validation of a clinical decision support system to inform airborne isolation requirements in the evaluation of suspected tuberculosis.
Infect Control Hosp Epidemiol
January 2025
Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
Background: The study objective was to develop and validate a clinical decision support system (CDSS) to guide clinicians through the diagnostic evaluation of hospitalized individuals with suspected pulmonary tuberculosis (TB) in low-prevalence settings.
Methods: The "TBorNotTB" CDSS was developed using a modified Delphi method. The CDSS assigns points based on epidemiologic risk factors, TB history, symptoms, chest imaging, and sputum/bronchoscopy results.
Interobserver Variability in Manual Versus Semi-Automatic CT Assessments of Small Lung Nodule Diameter and Volume.
Tomography
December 2024
Centre for Research and Development, Uppsala University, Region Gävleborg, SE 801 88 Gävle, Sweden.
Background: This study aimed to assess the interobserver variability of semi-automatic diameter and volumetric measurements versus manual diameter measurements for small lung nodules identified on computed tomography scans.
Methods: The radiological patient database was searched for CT thorax examinations with at least one noncalcified solid nodule (∼3-10 mm). Three radiologists with four to six years of experience evaluated each nodule in accordance with the Fleischner Society guidelines using standard diameter measurements, semi-automatic lesion diameter measurements, and volumetric assessments.
Deep Learning-Based Diagnosis Algorithm for Alzheimer's Disease.
J Imaging
December 2024
College of Electrical and Information, Northeast Agricultural University, 600 Changjiang Road, Harbin 150038, China.
Alzheimer's disease (AD), a degenerative condition affecting the central nervous system, has witnessed a notable rise in prevalence along with the increasing aging population. In recent years, the integration of cutting-edge medical imaging technologies with forefront theories in artificial intelligence has dramatically enhanced the efficiency of identifying and diagnosing brain diseases such as AD. This paper presents an innovative two-stage automatic auxiliary diagnosis algorithm for AD, based on an improved 3D DenseNet segmentation model and an improved MobileNetV3 classification model applied to brain MR images.
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