AIMC Topic: Sensitivity and Specificity
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Validation of Vetscan Imagyst, a diagnostic test utilizing an artificial intelligence deep learning algorithm, for detecting strongyles and Parascaris spp. in equine fecal samples.
Parasites & vectors
Nov 12, 2024
BACKGROUND: Current methods for obtaining fecal egg counts in horses are often inaccurate and variable depending on the analyst's skill and experience. Automated digital scanning of fecal sample slides integrated with analysis by an artificial intell...
Diagnostic accuracy of radiomics and artificial intelligence models in diagnosing lymph node metastasis in head and neck cancers: a systematic review and meta-analysis.
Neuroradiology
Nov 11, 2024
INTRODUCTION: Head and neck cancers are the seventh most common globally, with lymph node metastasis (LNM) being a critical prognostic factor, significantly reducing survival rates. Traditional imaging methods have limitations in accurately diagnosin...
Image-based deep learning in diagnosing mycoplasma pneumonia on pediatric chest X-rays.
BMC pediatrics
Nov 11, 2024
BACKGROUND: Correctly diagnosing and accurately distinguishing mycoplasma pneumonia in children has consistently posed a challenge in clinical practice, as it can directly impact the prognosis of affected children. To address this issue, we analyzed ...
Machine learning and deep learning models for preoperative detection of lymph node metastasis in colorectal cancer: a systematic review and meta-analysis.
Abdominal radiology (New York)
Nov 10, 2024
OBJECTIVE: To evaluate the diagnostic performance of Machine Learning (ML) and Deep Learning (DL) models for predicting preoperative Lymph Node Metastasis (LNM) in Colorectal Cancer (CRC) patients.
Introduction and accuracy assessment of Nicolab's StrokeViewer in a developing stroke thrombectomy UK service. a service development/improvement project.
Clinical radiology
Nov 8, 2024
AIM: The aim of this study was to evaluate the implementation of artificial intelligence (AI) software in a quaternary stroke centre as well as assess the accuracy and efficacy of StrokeViewer software in large vessel occlusion detection and its pote...
Artificial intelligence-enhanced infrared thermography as a diagnostic tool for thyroid malignancy detection.
Annals of medicine
Nov 8, 2024
INTRODUCTION: Thyroid nodules are common, and investigation is crucial for excluding malignancy. Increased intranodular vascularity is frequently observed in malignant tumors, which can be detected through increased skin surface temperatures using no...
PACT-3D, a deep learning algorithm for pneumoperitoneum detection in abdominal CT scans.
Nature communications
Nov 7, 2024
Delays or misdiagnoses in detecting pneumoperitoneum can significantly increase mortality and morbidity. We developed and validated a deep learning model designed to identify pneumoperitoneum in computed tomography images. The model is trained on abd...
Artificial Intelligence Efficacy as a Function of Trainee Interpreter Proficiency: Lessons from a Randomized Controlled Trial.
AJNR. American journal of neuroradiology
Nov 7, 2024
BACKGROUND AND PURPOSE: Recently, artificial intelligence tools have been deployed with increasing speed in educational and clinical settings. However, the use of artificial intelligence by trainees across different levels of experience has not been ...
Establishing an AI model and application for automated capsule endoscopy recognition based on convolutional neural networks (with video).
BMC gastroenterology
Nov 6, 2024
BACKGROUND: Although capsule endoscopy (CE) is a crucial tool for diagnosing small bowel diseases, the need to process a vast number of images imposes a significant workload on physicians, leading to a high risk of missed diagnoses. This study aims t...
A generalised computer vision model for improved glaucoma screening using fundus images.
Eye (London, England)
Nov 5, 2024
IMPORTANCE: Worldwide, glaucoma is a leading cause of irreversible blindness. Timely detection is paramount yet challenging, particularly in resource-limited settings. A novel, computer vision-based model for glaucoma screening using fundus images co...
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