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Data Driven Science for Clinically Actionable Knowledge in Diseases
Data-driven science has become a major decision-making aid for the diagnosis and treatment of disease. Computational and visual analytics enables effective exploration and sense making of large and complex data through the deployment of appropriate data science methods, meaningful visualisation and human-information interaction. This edited volume covers state-of-the-art theory, method, models, design, evaluation and applications in computational and visual analytics in desktop, mobile and immersive environments for analysing biomedical and health data. The book is focused on data-driven integral analysis, including computational methods and visual analytics practices and solutions for discovering actionable knowledge in support of clinical actions in real environments. By studying how data and visual analytics have been implemented into the healthcare domain, the book demonstrates how analytics influences the domain through improving decision making, specifying diagnostics, selecting the best treatments and generating clinical certainty.
Recent Progresses of Non-Coding RNAs in Biological and Medical Research, 2nd Edition
Publisher’s note: In this 2nd edition, the following article has been updated: Xun Y, Tang Y, Hu L, Xiao H, Long S, Gong M, Wei C, Wei K and Xiang S (2019) Purification and Identification of miRNA Target Sites in Genome Using DNA Affinity Precipitation. Front. Genet. 10:778. doi: 10.3389/fgene.2019.00778
Machine Intelligence and Data Science Applications
This book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications (MIDAS 2022), held on October 28 and 29, 2022, at the University of Versailles—Paris-Saclay, France. The book covers applications in various fields like data science, machine intelligence, image processing, natural language processing, computer vision, sentiment analysis, and speech and gesture analysis. It also includes interdisciplinary applications like legal, healthcare, smart society, cyber-physical system, and smart agriculture. The book is a good reference for computer science engineers, lecturers/researchers in the machine intelligence discipline, and engineering graduates.
Data Driven Science for Clinically Actionable Knowledge in Diseases
Data-driven science has become a major decision-making aid for the diagnosis and treatment of disease. Computational and visual analytics enables effective exploration and sense making of large and complex data through the deployment of appropriate data science methods, meaningful visualisation and human-information interaction. This edited volume covers state-of-the-art theory, method, models, design, evaluation and applications in computational and visual analytics in desktop, mobile and immersive environments for analysing biomedical and health data. The book is focused on data-driven integral analysis, including computational methods and visual analytics practices and solutions for discovering actionable knowledge in support of clinical actions in real environments. By studying how data and visual analytics have been implemented into the healthcare domain, the book demonstrates how analytics influences the domain through improving decision making, specifying diagnostics, selecting the best treatments and generating clinical certainty.
Global Genes, Local Concerns
With interdisciplinary chapters written by lawyers, sociologists, doctors and biobank practitioners, Global Genes, Local Concerns identifies and discusses the most pressing issues in contemporary biobanking. Addressing pressing questions such as how do national biobanks best contribute to translational research and how could academic and industrial exploitation, ownership and IPR issues be addressed and facilitated, this book contributes to the continued development of international biobanking by highlighting and analysing the complexities in this important area of research.
AI 2021: Advances in Artificial Intelligence
This book constitutes the proceedings of the 34th Australasian Joint Conference on Artificial Intelligence, AI 2021, held in Sydney, NSW, Australia, in February 2022.* The 64 full papers presented in this volume were carefully reviewed and selected from 120 submissions. The papers were organized in topical sections named: Ethical AI, Applications, Classical AI, Computer Vision and Machine Learning, Natural Language Processing and Data Mining, and Network Analysis. *The conference was postponed from December 2021 to February 2022 and held virtually due to the COVID-19 pandemic.
Data Mining
This book constitutes the refereed proceedings of the 20th Australasian Conference on Data Mining, AusDM 2022, held in Western Sydney, Australia, during December 12–15, 2022. The 17 full papers included in this book were carefully reviewed and selected from 44 submissions. They were organized in topical sections as research track and application track.
Neural Information Processing
The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually. The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 12534, is organized in topical sections on biomedical information; neural data analysis; neural network models; recommender systems; time series analysis.
Data Mining
This book constitutes the refereed proceedings of the 15th Australasian Conference on Data Mining, AusDM 2017, held in Melbourne, VIC, Australia, in August 2017. The 17 revised full papers presented together with 11 research track papers and 6 application track papers were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on clustering and classification; big data; time series; outlier detection and applications; social media and applications.
Advances in Knowledge Discovery and Data Mining
This book constitutes the refereed proceedings of the 8th Pacific-Asia Conference on Knowledge Discovery and Data mining, PAKDD 2004, held in Sydney, Australia in May 2004. The 50 revised full papers and 31 revised short papers presented were carefully reviewed and selected from a total of 238 submissions. The papers are organized in topical sections on classification; clustering; association rules; novel algorithms; event mining, anomaly detection, and intrusion detection; ensemble learning; Bayesian network and graph mining; text mining; multimedia mining; text mining and Web mining; statistical methods, sequential data mining, and time series mining; and biomedical data mining.
