AIMC Topic: Sensitivity and Specificity
Clear Filters Showing 2401 to 2410 of 2922 articles
[A new artificial intelligence tool for assessing symptoms in patients seeking emergency department care: the Mediktor application].
Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias
May 13, 2025
OBJECTIVES: To analyze agreement between diagnoses issued by the Mediktor application and those of an attending physician, and to evaluate the usefulness of this application in patients who seek emergency care.
Tertiary Care Centers
Hospitals, University
Computers, Handheld
Mobile Applications
Diagnosis, Differential
Emergency Service, Hospital
Double-Blind Method
Middle Aged
Surveys and Questionnaires
Decision Support Systems, Clinical
Prospective Studies
Clinical Decision-Making
Female
Aged
Aged, 80 and over
Adult
Sensitivity and Specificity
Male
Humans
Artificial Intelligence
Machine learning for the prediction of diabetes-related amputation: a systematic review and meta-analysis of diagnostic test accuracy.
Clinical and experimental medicine
May 10, 2025
Although machine learning is frequently used in medicine for predictive purposes, its accuracy in diabetes-related amputation (DRA) remains unclear. From establishing the database until December 2024, we conducted a comprehensive search of PubMed, We...
Using machine learning models to predict the impact of template mismatches on polymerase chain reaction assay performance.
Scientific reports
May 9, 2025
Molecular assays are critical tools for the diagnosis of infectious diseases. These assays have been extremely valuable during the COVID pandemic, used to guide both patient management and infection control strategies. Sustained transmission and unhi...
Validation of artificial intelligence algorithm LuxIA for screening of diabetic retinopathy from a single 45° retinal colour fundus images: the CARDS study.
BMJ open ophthalmology
May 8, 2025
OBJECTIVE: This study validated the artificial intelligence (AI)-based algorithm LuxIA for screening more-than-mild diabetic retinopathy (mtmDR) from a single 45° colour fundus image of patients with diabetes mellitus (DM, type 1 or type 2) in Spain....
Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning.
BMC psychiatry
May 8, 2025
BACKGROUND AND OBJECTIVE: Accurate detection of schizophrenia poses a grand challenge as a complex and heterogeneous mental disorder. Current diagnostic criteria rely primarily on clinical symptoms, which may not fully capture individual differences ...
[A Meta-analysis of the application of artificial intelligence in cervical cytopathology diagnosis].
Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]
May 6, 2025
To systematically evaluate the application of artificial intelligence (AI) in cervical cytopathology diagnosis. A systematic search was conducted using the keywords ''cervical cancer'' ''cytology'' ''artificial intelligence'' ''sensitivity'' and ''...
Accuracy of Low-Dose Chest CT-Based Artificial Intelligence Models in Osteoporosis Detection: A Systematic Review and Meta-analysis.
Calcified tissue international
May 2, 2025
The purpose of this study is to systematically review and evaluate the accuracy of low-dose chest CT-based artificial intelligence in osteoporosis screening. A systematic literature search for relevant studies up to 13th December 2024 was performed i...
Interactive Explainable Deep Learning Model for Hepatocellular Carcinoma Diagnosis at Gadoxetic Acid-enhanced MRI: A Retrospective, Multicenter, Diagnostic Study.
Radiology. Imaging cancer
May 1, 2025
Purpose To develop an artificial intelligence (AI) model based on gadoxetic acid-enhanced MRI to assist radiologists in hepatocellular carcinoma (HCC) diagnosis. Materials and Methods This retrospective study included patients with focal liver lesion...
Evaluating Automated Tools for Lesion Detection on F Fluoroestradiol PET/CT Images and Assessment of Concordance with Standard-of-Care Imaging in Metastatic Breast Cancer.
Radiology. Imaging cancer
May 1, 2025
Purpose To evaluate two automated tools for detecting lesions on fluorine 18 (F) fluoroestradiol (FES) PET/CT images and assess concordance of F-FES PET/CT with standard diagnostic CT and/or F fluorodeoxyglucose (FDG) PET/CT in patients with breast c...
Light Bladder Net: Non-invasive Bladder Cancer Prediction by Weighted Deep Learning Approaches and Graphical Data Transformation.
Anticancer research
May 1, 2025
BACKGROUND/AIM: Bladder cancer (BCa) is associated with high recurrence rates, emphasizing the importance of early and accurate detection. This study aimed to develop a lightweight and fast deep learning model, Light-Bladder-Net (LBN), for non-invasi...
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