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Computational Methods for Precision Oncology

Computational Methods for Precision Oncology
Author: Alessandro Laganà
Publisher: Springer Nature
Total Pages: 341
Release: 2022-03-01
Genre: Medical
ISBN: 303091836X

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Precision medicine holds great promise for the treatment of cancer and represents a unique opportunity for accelerated development and application of novel and repurposed therapeutic approaches. Current studies and clinical trials demonstrate the benefits of genomic profiling for patients whose cancer is driven by specific, targetable alterations. However, precision oncologists continue to be challenged by the widespread heterogeneity of cancer genomes and drug responses in designing personalized treatments. Chapters provide a comprehensive overview of the computational approaches, methods, and tools that enable precision oncology, as well as related biological concepts. Covered topics include genome sequencing, the architecture of a precision oncology workflow, and introduces cutting-edge research topics in the field of precision oncology. This book is intended for computational biologists, bioinformaticians, biostatisticians and computational pathologists working in precision oncology and related fields, including cancer genomics, systems biology, and immuno-oncology.


Improving Cancer Diagnosis and Care

Improving Cancer Diagnosis and Care
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
Total Pages: 93
Release: 2019-08-15
Genre: Medical
ISBN: 0309490812

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A hallmark of high-quality cancer care is the delivery of the right treatment to the right patient at the right time. Precision oncology therapies, which target specific genetic changes in a patient's cancer, are changing the nature of cancer treatment by allowing clinicians to select therapies that are most likely to benefit individual patients. In current clinical practice, oncologists are increasingly formulating cancer treatment plans using results from complex laboratory and imaging tests that characterize the molecular underpinnings of an individual patient's cancer. These molecular fingerprints can be quite complex and heterogeneous, even within a single patient. To enable these molecular tumor characterizations to effectively and safely inform cancer care, the cancer community is working to develop and validate multiparameter omics tests and imaging tests as well as software and computational methods for interpretation of the resulting datasets. To examine opportunities to improve cancer diagnosis and care in the new precision oncology era, the National Cancer Policy Forum developed a two-workshop series. The first workshop focused on patient access to expertise and technologies in oncologic imaging and pathology and was held in February 2018. The second workshop, conducted in collaboration with the Board on Mathematical Sciences and Analytics, was held in October 2018 to examine the use of multidimensional data derived from patients with cancer, and the computational methods that analyze these data to inform cancer treatment decisions. This publication summarizes the presentations and discussions from the second workshop.


'Essentials of Cancer Genomic, Computational Approaches and Precision Medicine

'Essentials of Cancer Genomic, Computational Approaches and Precision Medicine
Author: Nosheen Masood
Publisher: Springer Nature
Total Pages: 499
Release: 2020-03-20
Genre: Medical
ISBN: 9811510679

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This book concisely describes the role of omics in precision medicine for cancer therapies. It outlines our current understanding of cancer genomics, shares insights into the process of oncogenesis, and discusses emerging technologies and clinical applications of cancer genomics in prognosis and precision-medicine treatment strategies. It then elaborates on recent advances concerning transcriptomics and translational genomics in cancer diagnosis, clinical applications, and personalized medicine in oncology. Importantly, it also explains the importance of high-performance analytics, predictive modeling, and system biology in cancer research. Lastly, the book discusses current and potential future applications of pharmacogenomics in clinical cancer therapy and cancer drug development.


Advanced Computational Methods for Oncological Image Analysis

Advanced Computational Methods for Oncological Image Analysis
Author: Leonardo Rundo
Publisher: Mdpi AG
Total Pages: 262
Release: 2021-12-06
Genre: Science
ISBN: 9783036525549

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Cancer is the second most common cause of death worldwide and encompasses highly variable clinical and biological scenarios. Some of the current clinical challenges are (i) early diagnosis of the disease and (ii) precision medicine, which allows for treatments targeted to specific clinical cases. The ultimate goal is to optimize the clinical workflow by combining accurate diagnosis with the most suitable therapies. Toward this, large-scale machine learning research can define associations among clinical, imaging, and multi-omics studies, making it possible to provide reliable diagnostic and prognostic biomarkers for precision oncology. Such reliable computer-assisted methods (i.e., artificial intelligence) together with clinicians' unique knowledge can be used to properly handle typical issues in evaluation/quantification procedures (i.e., operator dependence and time-consuming tasks). These technical advances can significantly improve result repeatability in disease diagnosis and guide toward appropriate cancer care. Indeed, the need to apply machine learning and computational intelligence techniques has steadily increased to effectively perform image processing operations-such as segmentation, co-registration, classification, and dimensionality reduction-and multi-omics data integration.


Computational Methods for Multi-Omics Data Analysis in Cancer Precision Medicine

Computational Methods for Multi-Omics Data Analysis in Cancer Precision Medicine
Author: Ehsan Nazemalhosseini-Mojarad
Publisher: Frontiers Media SA
Total Pages: 433
Release: 2023-08-02
Genre: Science
ISBN: 2832530389

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Cancer is a complex and heterogeneous disease often caused by different alterations. The development of human cancer is due to the accumulation of genetic and epigenetic modifications that could affect the structure and function of the genome. High-throughput methods (e.g., microarray and next-generation sequencing) can investigate a tumor at multiple levels: i) DNA with genome-wide association studies (GWAS), ii) epigenetic modifications such as DNA methylation, histone changes and microRNAs (miRNAs) iii) mRNA. The availability of public datasets from different multi-omics data has been growing rapidly and could facilitate better knowledge of the biological processes of cancer. Computational approaches are essential for the analysis of big data and the identification of potential biomarkers for early and differential diagnosis, and prognosis.


Detection Methods in Precision Medicine

Detection Methods in Precision Medicine
Author: Mengsu Yang
Publisher: Royal Society of Chemistry
Total Pages: 389
Release: 2020-12-14
Genre: Science
ISBN: 1788017617

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This book will be among the first to cover the detection methods for precision medicine that are set to transform health care in the future.


P5 eHealth: An Agenda for the Health Technologies of the Future

P5 eHealth: An Agenda for the Health Technologies of the Future
Author: Gabriella Pravettoni
Publisher: Springer Nature
Total Pages: 191
Release: 2019-11-29
Genre: Psychology
ISBN: 3030279944

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This open access volume focuses on the development of a P5 eHealth, or better, a methodological resource for developing the health technologies of the future, based on patients’ personal characteristics and needs as the fundamental guidelines for design. It provides practical guidelines and evidence based examples on how to design, implement, use and elevate new technologies for healthcare to support the management of incurable, chronic conditions. The volume further discusses the criticalities of eHealth, why it is difficult to employ eHealth from an organizational point of view or why patients do not always accept the technology, and how eHealth interventions can be improved in the future. By dealing with the state-of-the-art in eHealth technologies, this volume is of great interest to researchers in the field of physical and mental healthcare, psychologists, stakeholders and policymakers as well as technology developers working in the healthcare sector.


Progress and Challenges in Precision Medicine

Progress and Challenges in Precision Medicine
Author: Mukesh Verma
Publisher: Academic Press
Total Pages: 344
Release: 2016-12-22
Genre: Medical
ISBN: 0128095024

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Progress and Challenges in Precision Medicine presents an insightful overview to the myriad factors of personalized and precision medicine. The availability of the human genome, large amounts of data on individual genetic variations, environmental interactions, influence of lifestyle, and cutting-edge tools and technologies for big-data analysis have led to the age of personalized and precision medicine. Bringing together a global range of experts on precision medicine, this book collects previously scattered information into one concise volume which covers the most important developments so far in precision medicine and also suggests the most likely avenues for future development. The book includes clinical information, informatics, public policy implications, and information on case studies. It is a useful reference and background work for students, researchers, and clinicians working in the biomedical and medical fields, as well as policymakers in the health sciences. Provides an overview of the growing field of precision medicine Contains chapters from geographically diverse experts in their field Explores important aspects of precision medicine, including applications, ethics, and development


Advanced Computational Methods for Oncological Image Analysis

Advanced Computational Methods for Oncological Image Analysis
Author: Leonardo Rundo
Publisher:
Total Pages: 262
Release: 2021
Genre:
ISBN: 9783036525556

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[Cancer is the second most common cause of death worldwide and encompasses highly variable clinical and biological scenarios. Some of the current clinical challenges are (i) early diagnosis of the disease and (ii) precision medicine, which allows for treatments targeted to specific clinical cases. The ultimate goal is to optimize the clinical workflow by combining accurate diagnosis with the most suitable therapies. Toward this, large-scale machine learning research can define associations among clinical, imaging, and multi-omics studies, making it possible to provide reliable diagnostic and prognostic biomarkers for precision oncology. Such reliable computer-assisted methods (i.e., artificial intelligence) together with clinicians' unique knowledge can be used to properly handle typical issues in evaluation/quantification procedures (i.e., operator dependence and time-consuming tasks). These technical advances can significantly improve result repeatability in disease diagnosis and guide toward appropriate cancer care. Indeed, the need to apply machine learning and computational intelligence techniques has steadily increased to effectively perform image processing operations--such as segmentation, co-registration, classification, and dimensionality reduction--and multi-omics data integration.].