Intelligent Computing In Carcinogenic Disease Detection
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Intelligent Computing in Carcinogenic Disease Detection
Author: Kaushik Das Sharma
language: en
Publisher: Springer Nature
Release Date: 2024-05-16
This book draws on a range of intelligent computing methodologies to effectively detect and classify various carcinogenic diseases. These methodologies, which have been developed on a sound foundation of gene-level, cell-level and tissue-level carcinogenic datasets, are discussed in Chapters 1 and 2. Chapters 3, 4 and 5 elaborate on several intelligent gene selection methodologies such as filter methodologies and wrapper methodologies. In addition, various gene selection philosophies for identifying relevant carcinogenic genes are described in detail. In turn, Chapters 6 and 7 tackle the issues of using cell-level and tissue-level datasets to effectively detect carcinogenic diseases. The performance of different intelligent feature selection techniques is evaluated on cell-level and tissue-level datasets to validate their effectiveness in the context of carcinogenic disease detection. In closing, the book presents illustrative case studies that demonstrate the value of intelligent computing strategies.
Intelligent Computing Theories and Application
This two-volume set of LNCS 11643 and LNCS 11644 constitutes - in conjunction with the volume LNAI 11645 - the refereed proceedings of the 15th International Conference on Intelligent Computing, ICIC 2019, held in Nanchang, China, in August 2019. The 217 full papers of the three proceedings volumes were carefully reviewed and selected from 609 submissions. The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is “Advanced Intelligent Computing Methodologies and Applications.” Papers related to this theme are especially solicited, including theories, methodologies, and applications in science and technology.
Revolutionizing Healthcare: Impact of Artificial Intelligence on Diagnosis, Treatment, and Patient Care
Author: Thipendra P. Singh
language: en
Publisher: Springer Nature
Release Date: 2025-03-21
This book explores the transformative role of artificial intelligence (AI) in healthcare, emphasizing its shift from a futuristic concept to an essential part of modern medical systems. The articles cover a range of AI applications, from disease diagnosis and drug design to patient engagement and mental health treatment. Advances in machine learning (ML) and deep learning (DL) technologies have opened new possibilities for diagnosing complex conditions, with examples like predictive analysis for health risks and early diagnosis of diseases such as breast cancer and diabetic retinopathy. Additionally, AI's role in treating mental health disorders is highlighted. While AI offers vast benefits, the book stresses the importance of ethical considerations, such as patient privacy and equitable access. It also addresses challenges in integrating AI within existing healthcare systems, underscoring collaboration among stakeholders as crucial. This book ultimately provides a comprehensive look at AI’s potential to reshape healthcare.