Review and classification of AI-enabled COVID-19 CT imaging models based on computer vision tasks Author links open overlay panelHaseeb Hassan a b 1, Zhaoyu Ren a 1, Huishi Zhao a 1, Shoujin Huang a, Dan Li a, Shaohua Xiang a, Yan Kang b c, Sifan Chen d e, Bingding Huang a...
Purpose:To evaluate the generalizability of artificial intelligence (AI)-otoscopy algorithms to identify middle ear disease using otoscopic images. Methods:1842 otoscopic images were collected from 3 independent sources: a) Van, Turkey...
Combining fuzzy rules with learning algorithms can become a powerful tool to perform reasoning and for instance, explain the inner logic of neural networks [30]. Similarly, the combination of antecedents and consequents can be seen as an argument in the discipline of argumentation, and a set of...
In this review, we provide an overview of the current field, including studies between 2018 and February 2021, describing AI algorithms for (1) lesion classification and (2) lesion detection for PCa. Our evaluation of 59 included studies showed that most research has been conducted for the ...
Learn about classification in machine learning, looking at what it is, how it's used, and some examples of classification algorithms.
They discuss the two main applications of AI in art: the automated analysis of existing artworks and the generation of new ones. AI-based art classification involves using machine learning algorithms to categorize artworks by attributes such as genre, style, and artist. This automated classification...
t until the 2010s that AIGC underwent rapid development, transitioning from experimental stages to practical applications, accompanied by the emergence of various deep learning algorithms. Especially by 2022, the advent of pre-trained large-scale AI models significantly bolstered AIGC capabilities, ...
We have also seen algorithms exhibit and amplify gender, racial, ethnic, and classbiasesthat are already baked into society. Also:Want to work in AI? How to pivot your career in 5 steps These kinds of issues arise because much of the data that powers AI models is scraped from content...
Every group of files should be diverse so that the machine learning algorithms will have better accuracy. Machine learning models predict labels for documents and determine the accuracy of their predictions. A “confidence level” is shown to a reviewer to reassess model data for another round of...
based on the Kolmogorov-Smirnov (K-S) test [31], which is a non-parametric statistical method to measure the goodness of fit. AI-based AMC Two algorithms for analog and digital modulation classification are presented in [32], the first of which utilizes the decision-theoretic approach, and ...