AIMC Topic: Algorithms

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Application of artificial intelligence in the assessment of thyroid eye disease (TED) - a scoping review.

Frontiers in endocrinology
BACKGROUND: There is emerging evidence which suggests the utility of artificial intelligence (AI) in the diagnostic assessment and pre-treatment evaluation of thyroid eye disease (TED). This scoping review aims to (1) identify the extent of the avail...

Hybrid grey assisted whale optimization based machine learning for the COVID-19 prediction.

Computer methods in biomechanics and biomedical engineering
Recently, COVID-19 (coronavirus) has been a huge influence on the socio and economic field. COVID-19 cases are seriously increasing day-day and also don't identified proper vaccine for COVID-19. Hence, COVID-19 is fast spreading virus and it causes m...

Real-time carotid plaque recognition from dynamic ultrasound videos based on artificial neural network.

Ultraschall in der Medizin (Stuttgart, Germany : 1980)
PURPOSE: Carotid ultrasound allows noninvasive assessment of vascular anatomy and function with real-time display. Based on the transfer learning method, a series of research results have been obtained on the optimal image recognition and analysis of...

Precise localization of corneal reflections in eye images using deep learning trained on synthetic data.

Behavior research methods
We present a deep learning method for accurately localizing the center of a single corneal reflection (CR) in an eye image. Unlike previous approaches, we use a convolutional neural network (CNN) that was trained solely using synthetic data. Using on...

Ultra-wide field and new wide field composite retinal image registration with AI-enabled pipeline and 3D distortion correction algorithm.

Eye (London, England)
PURPOSE: This study aimed to compare a new Artificial Intelligence (AI) method to conventional mathematical warping in accurately overlaying peripheral retinal vessels from two different imaging devices: confocal scanning laser ophthalmoscope (cSLO) ...

Towards safer imaging: A comparative study of deep learning-based denoising and iterative reconstruction in intraindividual low-dose CT scans using an in-vivo large animal model.

European journal of radiology
PURPOSE: Computed tomography (CT) scans are a significant source of medically induced radiation exposure. Novel deep learning-based denoising (DLD) algorithms have been shown to enable diagnostic image quality at lower radiation doses than iterative ...

Deep learning-based burned forest areas mapping via Sentinel-2 imagery: a comparative study.

Environmental science and pollution research international
In order to evaluate the effects of forest fires on the dynamics of the function and structure of ecosystems, it is necessary to determine burned forest areas with high accuracy, effectively, economically, and practically using satellite images. Extr...

Artificial Intelligence and Acute Appendicitis: A Systematic Review of Diagnostic and Prognostic Models.

World journal of emergency surgery : WJES
BACKGROUND: To assess the efficacy of artificial intelligence (AI) models in diagnosing and prognosticating acute appendicitis (AA) in adult patients compared to traditional methods. AA is a common cause of emergency department visits and abdominal s...

Deep learning for classifying the stages of periodontitis on dental images: a systematic review and meta-analysis.

BMC oral health
BACKGROUND: The development of deep learning (DL) algorithms for use in dentistry is an emerging trend. Periodontitis is one of the most prevalent oral diseases, which has a notable impact on the life quality of patients. Therefore, it is crucial to ...

A new convolutional neural network based on combination of circlets and wavelets for macular OCT classification.

Scientific reports
Artificial intelligence (AI) algorithms, encompassing machine learning and deep learning, can assist ophthalmologists in early detection of various ocular abnormalities through the analysis of retinal optical coherence tomography (OCT) images. Despit...