AIMC Topic: Sensitivity and Specificity
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Development and External Validation of a Detection Model to Retrospectively Identify Patients With Acute Respiratory Distress Syndrome.
Critical care medicine
Jun 1, 2025
OBJECTIVE: The aim of this study was to develop and externally validate a machine-learning model that retrospectively identifies patients with acute respiratory distress syndrome (acute respiratory distress syndrome [ARDS]) using electronic health re...
Accuracy of a deep neural network for automated pulmonary embolism detection on dedicated CT pulmonary angiograms.
European journal of radiology
Jun 1, 2025
PURPOSE: To assess the performance of a Deep Neural Network (DNN)-based prototype algorithm for automated PE detection on CTPA scans.
Humans
Neural Networks, Computer
Algorithms
Retrospective Studies
Female
Reproducibility of Results
Aged
Aged, 80 and over
Pulmonary Artery
Adult
Sensitivity and Specificity
Male
Middle Aged
Deep Learning
Radiographic Image Interpretation, Computer-Assisted
Pulmonary Embolism
Computed Tomography Angiography
ChatGPT-4's Accuracy in Estimating Thyroid Nodule Features and Cancer Risk From Ultrasound Images.
Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
Jun 1, 2025
OBJECTIVE: To evaluate the performance of GPT-4 and GPT-4o in accurately identifying features and categories from thyroid nodule ultrasound images following the American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS).
Chat-GPT in triage: Still far from surpassing human expertise - An observational study.
The American journal of emergency medicine
Jun 1, 2025
BACKGROUND: Triage is essential in emergency departments (EDs) to prioritize patient care based on clinical urgency. Recent investigations have explored the role of large language models (LLMs) in triage, but their effectiveness compared to human tri...
Deep learning based on ultrasound images predicting cervical lymph node metastasis in postoperative patients with differentiated thyroid carcinoma.
The British journal of radiology
Jun 1, 2025
OBJECTIVES: To develop a deep learning (DL) model based on ultrasound (US) images of lymph nodes for predicting cervical lymph node metastasis (CLNM) in postoperative patients with differentiated thyroid carcinoma (DTC).
Development and validation of the Open-Source Automatic Bowel Preparation Scale.
Gastrointestinal endoscopy
Jun 1, 2025
BACKGROUND AND AIMS: Insufficient bowel preparation accounts for up to 42% of missed adenomas in colonoscopy. However, major analysis programs found no correlation between adenoma detection rate and the human-rated Boston Bowel Preparation Scale (BBP...
Development and validation of an integrated residual-recurrent neural network model for automated heart murmur detection in pediatric populations.
Scientific reports
May 31, 2025
Congenital heart disease affects approximately 1% of children worldwide, with a number of cases in resource-limited settings remaining undiagnosed through school age. While cardiac auscultation is a key screening method, its effectiveness varies wide...
Integrating SEResNet101 and SE-VGG19 for advanced cervical lesion detection: a step forward in precision oncology.
BMC cancer
May 28, 2025
BACKGROUND: Cervical cancer remains a significant global health issue, with accurate differentiation between low-grade (LSIL) and high-grade squamous intraepithelial lesions (HSIL) crucial for effective screening and management. Current methods, such...
A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis.
Nature communications
May 27, 2025
Sepsis is a life-threatening organ dysfunction due to a dysfunctional response to infection. Delays in diagnosis have substantial impact on survival. Herein, blood samples from 586 in-house patients with suspected sepsis are used in conjunction with ...
A comparative analysis of deep learning models for assisting in the diagnosis of periapical lesions in periapical radiographs.
BMC oral health
May 26, 2025
PURPOSE: Numerous studies have investigated the use of convolutional neural network (CNN) models for detecting periapical lesions(PLs). However, limited research has focused on evaluating their potential in assisting clinicians with diagnosis. This s...
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