AIMC Topic: Sensitivity and Specificity

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Machine learning to detect Alzheimer's disease with data on drugs and diagnoses.

The journal of prevention of Alzheimer's disease
BACKGROUND: Integrating machine learning with medical records offers potential for early detection of Alzheimer's disease (AD), enabling timely interventions.

Hand X-rays findings and a disease screening for Turner syndrome through deep learning model.

BMC pediatrics
BACKGROUND: Turner syndrome (TS) is one of the important causes of short stature in girls, but there are cases of misdiagnosis and missed diagnosis in clinical practice. Our aim is to analyze the hand skeletal characteristics of TS patients and estab...

Development and validation of computer-aided detection for colorectal neoplasms using deep learning incorporated with computed tomography colonography.

BMC gastroenterology
OBJECTIVES: Computed tomography (CT) colonography is increasingly recognized as a valuable modality for diagnosing colorectal lesions, however, the interpretation workload remains challenging for physicians. Deep learning-based artificial intelligenc...

AI and human interactions in prostate cancer diagnosis using MRI.

European radiology
This special report explores the integration of artificial intelligence (AI) into prostate MRI workflows to address limitations associated with single-reader interpretations, such as inter-reader variability and diagnostic errors. We review various A...

An artificial intelligence tool that may assist with interpretation of rapid plasma reagin test for syphilis: Development and on-site evaluation.

The Journal of infection
OBJECTIVES: The rapid plasma reagin (RPR) test, a traditional method for diagnosing syphilis and evaluating treatment efficacy, relies on subjective interpretation and requires high technical proficiency. This study aimed to develop and validate a us...

Artificial intelligence for the detection of airway nodules in chest CT scans.

European radiology
OBJECTIVES: Incidental airway tumors are rare and can easily be overlooked on chest CT, especially at an early stage. Therefore, we developed and assessed a deep learning-based artificial intelligence (AI) system for detecting and localizing airway n...

Added value of artificial intelligence for the detection of pelvic and hip fractures.

Japanese journal of radiology
PURPOSE: To assess the added value of artificial intelligence (AI) for radiologists and emergency physicians in the radiographic detection of pelvic fractures.

Artificial intelligence-based deep learning algorithms for ground-glass opacity nodule detection: A review.

Narra J
Ground-glass opacities (GGOs) are hazy opacities on chest computed tomography (CT) scans that can indicate various lung diseases, including early COVID-19, pneumonia, and lung cancer. Artificial intelligence (AI) is a promising tool for analyzing med...

Development and validation of automated three-dimensional convolutional neural network model for acute appendicitis diagnosis.

Scientific reports
Rapid, accurate preoperative imaging diagnostics of appendicitis are critical in surgical decisions of emergency care. This study developed a fully automated diagnostic framework using a 3D convolutional neural network (CNN) to identify appendicitis ...