AIMC Topic: Sensitivity and Specificity

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AI-supported versus manual microscopy of Kato-Katz smears for diagnosis of soil-transmitted helminth infections in a primary healthcare setting.

Scientific reports
Soil-transmitted helminths primarily comprise Ascaris lumbricoides, Trichuris trichiura, and hookworms, infecting more than 600 million people globally, particularly in underserved communities. Manual microscopy of Kato-Katz thick smears is a widely ...

Design and optimization of an automatic deep learning-based cerebral reperfusion scoring (TICI) using thrombus localization.

Journal of neuroradiology = Journal de neuroradiologie
BACKGROUND: The Thrombolysis in Cerebral Infarction (TICI) scale is widely used to assess angiographic outcomes of mechanical thrombectomy despite significant variability. Our objective was to create and optimize an artificial intelligence (AI)-based...

Diagnosis of knee meniscal injuries using artificial intelligence: A systematic review and meta-analysis of diagnostic performance.

PloS one
AIM OF THE STUDY: The aim was to systematically review the literature and perform a meta-analysis to estimate the performance of artificial intelligence (AI) algorithms in detecting meniscal injuries.

Technologies for the point-of-care diagnosis of malaria: a scoping review.

Infectious diseases of poverty
BACKGROUND: Malaria continues to pose a significant health challenge, particularly in low-resource settings (LRS), where access to reliable and timely diagnostics is often limited. In this context, point-of-care (POC) in vitro diagnostics (IVDs) play...

Detection of breast cancer using fractional discrete sinc transform based on empirical Fourier decomposition.

Bio-medical materials and engineering
Breast cancer is the most common cause of death among women worldwide. Early detection of breast cancer is important; for saving patients' lives. Ultrasound and mammography are the most common noninvasive methods for detecting breast cancer. Computer...

Deep learning detects retropharyngeal edema on MRI in patients with acute neck infections.

European radiology experimental
BACKGROUND: In acute neck infections, magnetic resonance imaging (MRI) shows retropharyngeal edema (RPE), which is a prognostic imaging biomarker for a severe course of illness. This study aimed to develop a deep learning-based algorithm for the auto...

A multicentric study examining a deep-learning-based computer model for classifying bipolar disorder using retinal vascular images.

Journal of affective disorders
OBJECTIVES: Due to easy accessibility, the retina is considered a window to the brain. Recent studies have reported retinal vascular abnormalities in bipolar disorder. Deep learning analysis, an advanced computational approach, has been implemented i...

Artificial intelligence for glaucoma.

The Cochrane database of systematic reviews
This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To determine the accuracy of artificial intelligence (AI) algorithms as a diagnostic tool for glaucoma compared with human graders in a community or secondary care ...

An anxiety screening framework integrating multimodal data and graph node correlation.

Artificial intelligence in medicine
Anxiety disorders are a significant global health concern, profoundly impacting patients' lives and social functioning while imposing considerable burdens on families and economies. However, current anxiety screening methods face limitations due to c...