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Conclusion for Next-Generation Bioinformatics for Pulmonary Disease Research
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Author(s): Debasis Mitra (Graphic Era University, India), Devvret Verma (Graphic Era University, India), Bhavya Mudgal (Graphic Era University, India), Suraj Vitthaloo Atram (University of Sheffield, UK)and Rokayya Sami (Taif University, Saudi Arabia)
Copyright: 2026
Pages: 12
Source title:
Next-Generation Bioinformatics for Pulmonary Disease Research
Source Author(s)/Editor(s): Devvret Verma (Graphic Era University, India), Debasis Mitra (Graphic Era University, India), Bhavya Mudgal (Graphic Era University, India), Suraj Vitthaloo Atram (The University of Sheffield, UK)and Rokayya Sami (Taif University, Saudi Arabia)
DOI: 10.4018/979-8-3373-4923-7.ch014
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Abstract
This book explores computational approaches revolutionizing pulmonary disease studies through AI, machine learning, and multi-omics. Chapters cover AI-driven respiratory data analysis, single-cell approaches, and integrative omics for lung disease outcomes. Key areas include tuberculosis, severe asthma, idiopathic pulmonary fibrosis, and non-small cell lung cancer, integrating genomic, proteomic, and epigenomic data. Novel methods like Sequential Attribute Designator for feature selection and deep learning models for lung disease diagnosis via chest X-rays are introduced. The book addresses lung microbiome, metagenomic tools, and environmental exposure effects. By connecting translational bioinformatics with clinical applications, it highlights precision pulmonology's future through advanced omics and machine learning, advancing disease diagnosis, treatment, and research.
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