图书简介
The automated learning of machines characterizes machine learning (ML). It focuses on making data-driven predictions using programmed algorithms. ML has several applications, including bioinformatics, which is a discipline of study and practice that deals with applying computational derivations to obtain biological data. It involves the collection, retrieval, storage, manipulation, and modeling of data for analysis or prediction made using customized software. Previously, comprehensive programming of;bioinformatical algorithms was an extremely laborious task for such applications as predicting protein structures. Now, algorithms using ML and deep learning (DL) have increased the speed and efficacy of programming such algorithms. Applications of Machine Learning and Deep Learning on Biological Data is an examination of applying ML and DL to such areas as proteomics, genomics, microarrays, text mining, and systems biology. The key objective is to cover ML applications to biological science problems, focusing on problems related to bioinformatics. The book looks at cutting-edge research topics and methodologies in ML applied to the rapidly advancing discipline of bioinformatics. ML and DL applied to biological and neuroimaging data can open new frontiers for biomedical engineering, such as refining the understanding of complex diseases, including cancer and neurodegenerative and psychiatric disorders. Advances in this field could eventually lead to the development of precision medicine and automated diagnostic tools capable of tailoring medical treatments to individual lifestyles, variability, and the environment.Highlights include:Artificial Intelligence in treating and diagnosing schizophreniaAn analysis of ML’s and DL’s financial effect on healthcareAn XGBoost-based classification method for breast cancer classificationUsing ML to predict squamous diseasesML and DL
1. Deep Learning Approaches, Algorithms, and Applications in BioinformaticsSaahira Banu Ahamed, Shermin Shamsudheen, and Awatef Salem Balobaid
2. Role of Artificial Intelligence and Machine Learning in Schizophrenia—A SurveyBhawana Paliwal and Khandakar Faridar Rahman.
3. Understanding Financial Impact of Machine and Deep Learning in Healthcare: An AnalysisKhurshid Ali Ganai and Bilal Ahmad Pandow
4. Face Mask Detection Alert System for COVID Prevention Using Deep LearningParth Agarwal , Dhruv Rastogi and Aman Sharma
5. An XGBoost-Based Classification Method to Classify Breast CancerKishwar Sadaf, Jabeen Sultana, and Nazia Ahmad
6. Prediction of Erythemato-Squamous Diseases Using Machine LearningSyed Nisar Hussain Bukhari, Faheem Masoodi, Muneer Ahmad Dar, Nisar IqbalWani, Adfar Sajad and Gousiya Hussain
7. Grouping of Mushroom 5.8s rRNA Sequences by Implementing Hierarchical Clustering AlgorithmP. Sudhasini and B. Ashadevi
8. Applications of Machine Learning and Deep Learning in Genomics and ProteomicsQurat-ul-ain and Uzma Hameed
9. Artificial Intelligence: For Biological DataIfra Altaf, Muheet Ahmed Butt, Majid Zaman
10. Application of;ML and DL;on Biological DataTawseef Ahmed Teli, Faheem Syed Masoodi and Zubair Masoodi
11. Deep Learning for BioinformaticsTawseef Ahmed Teli and Rameez Yousuf
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