AIMC Topic: Sensitivity and Specificity
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Assessing the performance of an artificial intelligence based chatbot in the differential diagnosis of oral mucosal lesions: clinical validation study.
Clinical oral investigations
Mar 18, 2025
OBJECTIVES: Artificial intelligence (AI) is becoming more popular in medicine. The current study aims to investigate, primarily, if an AI-based chatbot, such as ChatGPT, could be a valid tool for assisting in establishing a differential diagnosis of ...
Combining artificial intelligence assisted image segmentation and ultrasound based radiomics for the prediction of carotid plaque stability.
BMC medical imaging
Mar 17, 2025
PURPOSE: Utilizing artificial intelligence (AI) technology for the segmentation of plaques on ultrasound images to evaluate the stability of carotid artery plaques and analyze its diagnostic accuracy in differentiating vulnerable plaques from stable ...
Deep learning-based fully automated detection and segmentation of pelvic lymph nodes on diffusion-weighted images for prostate cancer: a multicenter study.
Cancer imaging : the official publication of the International Cancer Imaging Society
Mar 17, 2025
BACKGROUND: Accurate identification and evaluation of lymph nodes (LNs) in prostate cancer (PCa) patients is crucial for effective staging but can be time-consuming. We utilized a 3D V-Net model to improve the efficiency and accuracy of LN detection ...
Classification of pulmonary diseases from chest radiographs using deep transfer learning.
PloS one
Mar 17, 2025
Pulmonary diseases are the leading causes of disabilities and deaths worldwide. Early diagnosis of pulmonary diseases can reduce the fatality rate. Chest radiographs are commonly used to diagnose pulmonary diseases. In clinical practice, diagnosing p...
Automated classification of panoramic radiographs with inflammatory periapical lesions using a CNN-LSTM architecture.
Journal of dentistry
Mar 16, 2025
OBJECTIVES: Considering Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network approaches have shown promising image classification performance, the aim of this study was to compare the performance of novel Convolutional Neural ...
Optimized attention-enhanced U-Net for autism detection and region localization in MRI.
Psychiatry research. Neuroimaging
Mar 14, 2025
Autism spectrum disorder (ASD) is a neurodevelopmental condition that affects a child's cognitive and social skills, often diagnosed only after symptoms appear around age 2. Leveraging MRI for early ASD detection can improve intervention outcomes. Th...
Interpretable machine learning for thyroid cancer recurrence predicton: Leveraging XGBoost and SHAP analysis.
European journal of radiology
Mar 14, 2025
PURPOSE: For patients suffering from differentiated thyroid cancer (DTC), several clinical, laboratory, and pathological features (including patient age, tumor size, extrathyroidal extension, or serum thyroglobulin levels) are currently used to ident...
Circulating lncRNAs as biomarkers for severe dengue using a machine learning approach.
The Journal of infection
Mar 14, 2025
OBJECTIVES: Dengue virus (DENV) infection is a significant global health concern, causing severe morbidity and mortality. While many cases present as a mild febrile illness, some progress to life-threatening severe dengue (SD). Early intervention is ...
Radiomics and machine learning models for diagnosing microvascular invasion in cholangiocarcinoma: a systematic review and meta-analysis of diagnostic test accuracy studies.
Clinical imaging
Mar 13, 2025
PURPOSE: We aimed to systematically assess the value of radiomics/machine learning (ML) models for diagnosing microvascular invasion (MVI) in patients with cholangiocarcinoma (CCA) using various radiologic modalities.
Artificial Intelligence-Assisted Capsule Endoscopy Versus Conventional Capsule Endoscopy for Detection of Small Bowel Lesions: A Systematic Review and Meta-Analysis.
Journal of gastroenterology and hepatology
Mar 13, 2025
BACKGROUND: Capsule endoscopy (CE) is a valuable tool used in the diagnosis of small intestinal lesions. The study aims to systematically review the literature and provide a meta-analysis of the diagnostic accuracy, specificity, sensitivity, and nega...
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