Machine Interaction-Based Computational Tools in Cancer Imaging2022

– Special issue of International Journal of Pattern Recognition and Artificial Intelligence
– Expands upon papers from FLAIRS conference, covers various AI techniques and applications

10.1201/9781003268796-13

A comprehensive review of the various computational tools available to detect different types of cancers, as well as the AI/machine learning algorithms based on which they work is provided in this paper .

– Computational tools in cancer imaging backed by AI and machine learning.
– Review of imaging techniques and algorithms used to detect different cancers.

– AI and computational technology are revolutionizing interior design graphics and modeling.
– These technologies offer benefits such as design iterations, material visualization, and time optimization.

– Computational tools backed by AI are crucial in cancer imaging.
– Various imaging techniques and machine learning algorithms are used.

– The paper explores healthcare staff perceptions on the benefits and challenges of using AI predictive tools in clinical decision-making.
– The study identifies opportunities for the application of AI predictive tools in clinical practice.

The paper discusses the use of computational tools backed by AI algorithms for cancer imaging, including techniques such as temporal subtraction, segmentation, feature extraction, and network training.

– Temporal subtraction method, segmentation techniques, feature extraction methods, and network training.
– Artificial neural networks (ANN) and deep learning algorithms.

– Computational tools backed by AI are revolutionizing cancer imaging.
– AI/machine learning algorithms are used to detect different types of cancers.

– Digital technology and tools are being used in the design industry.
– Artificial Intelligence (AI) is one of the latest computational technologies being utilized.

– The paper provides a comprehensive review of computational tools for cancer imaging.
– It discusses the intersection of AI and machine learning in cancer detection.

– AI-driven computational tools for cancer imaging
– Review of imaging techniques and machine learning algorithms