Medical Data Sharing Harmonization and Analytics

Medical Data Sharing  Harmonization and Analytics
Author: Dimitrios I. Fotiadis,Vasileios Pezoulas,Themis Exarchos
Publsiher: Academic Press
Total Pages: 382
Release: 2020-01-17
ISBN 10: 9780128165072
ISBN 13: 0128165073
Language: EN, FR, DE, ES & NL

Medical Data Sharing Harmonization and Analytics Book Review:

Medical Data Sharing, Harmonization and Analytics serves as the basis for understanding the rapidly evolving field of medical data harmonization combined with the latest cloud infrastructures for storing the harmonized (shared) data. Chapters cover the latest research and applications on data sharing and protection in the medical domain, cohort integration through the recent advancements in data harmonization, cloud computing for storing and securing the patient data, and data analytics for effectively processing the harmonized data. Examines the unmet needs in chronic diseases as a part of medical data sharing Discusses ethical, legal and privacy issues as part of data protection Combines data harmonization and big data analytics strategies in shared medical data, along with relevant case studies in chronic diseases

Medical Data Sharing Harmonization and Analytics

Medical Data Sharing  Harmonization and Analytics
Author: Vasileios Pezoulas,Themis Exarchos,Dimitrios I Fotiadis
Publsiher: Academic Press
Total Pages: 382
Release: 2020-01-05
ISBN 10: 0128165596
ISBN 13: 9780128165591
Language: EN, FR, DE, ES & NL

Medical Data Sharing Harmonization and Analytics Book Review:

Medical Data Sharing, Harmonization and Analytics serves as the basis for understanding the rapidly evolving field of medical data harmonization combined with the latest cloud infrastructures for storing the harmonized (shared) data. Chapters cover the latest research and applications on data sharing and protection in the medical domain, cohort integration through the recent advancements in data harmonization, cloud computing for storing and securing the patient data, and data analytics for effectively processing the harmonized data. Examines the unmet needs in chronic diseases as a part of medical data sharing Discusses ethical, legal and privacy issues as part of data protection Combines data harmonization and big data analytics strategies in shared medical data, along with relevant case studies in chronic diseases

8th European Medical and Biological Engineering Conference

8th European Medical and Biological Engineering Conference
Author: Tomaz Jarm,Aleksandra Cvetkoska,Samo Mahnič-Kalamiza,Damijan Miklavcic
Publsiher: Springer Nature
Total Pages: 1172
Release: 2020-11-29
ISBN 10: 3030646106
ISBN 13: 9783030646103
Language: EN, FR, DE, ES & NL

8th European Medical and Biological Engineering Conference Book Review:

This book aims at informing on new trends, challenges and solutions, in the multidisciplinary field of biomedical engineering. It covers traditional biomedical engineering topics, as well as innovative applications such as artificial intelligence in health care, tissue engineering , neurotechnology and wearable devices. Further topics include mobile health and electroporation-based technologies, as well as new treatments in medicine. Gathering the proceedings of the 8th European Medical and Biological Engineering Conference (EMBEC 2020), held on November 29 - December 3, 2020, in Portorož, Slovenia, this book bridges fundamental and clinically-oriented research, emphasizing the role of education, translational research and commercialization of new ideas in biomedical engineering. It aims at inspiring and fostering communication and collaboration between engineers, physicists, biologists, physicians and other professionals dealing with cutting-edge themes in and advanced technologies serving the broad field of biomedical engineering.

Data Science for COVID 19

Data Science for COVID 19
Author: Utku Kose,Deepak Gupta,Victor Hugo Costa de Albuquerque,Ashish Khanna
Publsiher: Academic Press
Total Pages: 812
Release: 2021-10-22
ISBN 10: 0323907709
ISBN 13: 9780323907705
Language: EN, FR, DE, ES & NL

Data Science for COVID 19 Book Review:

Data Science for COVID-19, Volume 2: Societal and Medical Perspectives presents the most current and leading-edge research into the applications of a variety of data science techniques for the detection, mitigation, treatment and elimination of the COVID-19 virus. At this point, Cognitive Data Science is the most powerful tool for researchers to fight COVID-19. Thanks to instant data-analysis and predictive techniques, including Artificial Intelligence, Machine Learning, Deep Learning, Data Mining, and computational modeling for processing large amounts of data, recognizing patterns, modeling new techniques, and improving both research and treatment outcomes is now possible. Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and the treatment of the COVID-19 virus Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including the wide variety of impacts the virus is having on societies and medical practice Presents insights into innovative, data-oriented modeling and predictive techniques from COVID-19 researchers around the world, including geoprocessing and tracking, lab data analysis, and theoretical views on a variety of technical applications Includes real-world feedback and user experiences from physicians and medical staff from around the world for medical treatment perspectives, public safety policies and impacts, sociological and psychological perspectives, the effects of COVID-19 in agriculture, economies, and education, and insights on future pandemics

Fundamentals of Clinical Data Science

Fundamentals of Clinical Data Science
Author: Pieter Kubben,Michel Dumontier,Andre Dekker
Publsiher: Springer
Total Pages: 219
Release: 2018-12-21
ISBN 10: 3319997130
ISBN 13: 9783319997131
Language: EN, FR, DE, ES & NL

Fundamentals of Clinical Data Science Book Review:

This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.

Advances in Assistive Technologies

Advances in Assistive Technologies
Author: George A. Tsihrintzis
Publsiher: Springer Nature
Total Pages: 135
Release: 2022
ISBN 10: 3030871320
ISBN 13: 9783030871321
Language: EN, FR, DE, ES & NL

Advances in Assistive Technologies Book Review:

Sharing Research Data to Improve Public Health in Africa

Sharing Research Data to Improve Public Health in Africa
Author: National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Committee on Population
Publsiher: National Academies Press
Total Pages: 102
Release: 2015-09-18
ISBN 10: 0309378125
ISBN 13: 9780309378123
Language: EN, FR, DE, ES & NL

Sharing Research Data to Improve Public Health in Africa Book Review:

Sharing research data on public health issues can promote expanded scientific inquiry and has the potential to advance improvements in public health. Although sharing data is the norm in some research fields, sharing of data in public health is not as firmly established. In March 2015, the National Research Council organized an international conference in Stellenbosch, South Africa, to explore the benefits of and barriers to sharing research data within the African context. The workshop brought together public health researchers and epidemiologists primarily from the African continent, along with selected international experts, to talk about the benefits and challenges of sharing data to improve public health, and to discuss potential actions to guide future work related to public health research data sharing. Sharing Research Data to Improve Public Health in Africa summarizes the presentations and discussions from this workshop.

Sharing Clinical Research Data

Sharing Clinical Research Data
Author: Institute of Medicine,Board on Health Care Services,Board on Health Sciences Policy,Roundtable on Translating Genomic-Based Research for Health,National Cancer Policy Forum,Forum on Neuroscience and Nervous System Disorders,Forum on Drug Discovery, Development, and Translation
Publsiher: National Academies Press
Total Pages: 156
Release: 2013-06-07
ISBN 10: 0309268745
ISBN 13: 9780309268745
Language: EN, FR, DE, ES & NL

Sharing Clinical Research Data Book Review:

Pharmaceutical companies, academic researchers, and government agencies such as the Food and Drug Administration and the National Institutes of Health all possess large quantities of clinical research data. If these data were shared more widely within and across sectors, the resulting research advances derived from data pooling and analysis could improve public health, enhance patient safety, and spur drug development. Data sharing can also increase public trust in clinical trials and conclusions derived from them by lending transparency to the clinical research process. Much of this information, however, is never shared. Retention of clinical research data by investigators and within organizations may represent lost opportunities in biomedical research. Despite the potential benefits that could be accrued from pooling and analysis of shared data, barriers to data sharing faced by researchers in industry include concerns about data mining, erroneous secondary analyses of data, and unwarranted litigation, as well as a desire to protect confidential commercial information. Academic partners face significant cultural barriers to sharing data and participating in longer term collaborative efforts that stem from a desire to protect intellectual autonomy and a career advancement system built on priority of publication and citation requirements. Some barriers, like the need to protect patient privacy, pre- sent challenges for both sectors. Looking ahead, there are also a number of technical challenges to be faced in analyzing potentially large and heterogeneous datasets. This public workshop focused on strategies to facilitate sharing of clinical research data in order to advance scientific knowledge and public health. While the workshop focused on sharing of data from preplanned interventional studies of human subjects, models and projects involving sharing of other clinical data types were considered to the extent that they provided lessons learned and best practices. The workshop objectives were to examine the benefits of sharing of clinical research data from all sectors and among these sectors, including, for example: benefits to the research and development enterprise and benefits to the analysis of safety and efficacy. Sharing Clinical Research Data: Workshop Summary identifies barriers and challenges to sharing clinical research data, explores strategies to address these barriers and challenges, including identifying priority actions and "low-hanging fruit" opportunities, and discusses strategies for using these potentially large datasets to facilitate scientific and public health advances.

Registries for Evaluating Patient Outcomes

Registries for Evaluating Patient Outcomes
Author: Agency for Healthcare Research and Quality/AHRQ
Publsiher: Government Printing Office
Total Pages: 356
Release: 2014-04-01
ISBN 10: 1587634333
ISBN 13: 9781587634338
Language: EN, FR, DE, ES & NL

Registries for Evaluating Patient Outcomes Book Review:

This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.

Joint Imaging Platform for Federated Clinical Data Analytics

Joint Imaging Platform for Federated Clinical Data Analytics
Author: Jonas Scherer,Jakob Neubauer,Marco Reisert,Michael Bock,Fabian Bamberg,Jürgen Hennig,Philipp Tobias Meyer,Juri Ruf,Klaus H. Maier-Hein
Publsiher: Unknown
Total Pages: 135
Release: 2020
ISBN 10: 1928374650XXX
ISBN 13: OCLC:1235807920
Language: EN, FR, DE, ES & NL

Joint Imaging Platform for Federated Clinical Data Analytics Book Review:

Abstract: PURPOSE Image analysis is one of the most promising applications of artificial intelligence (AI) in health care, potentially improving prediction, diagnosis, and treatment of diseases. Although scientific advances in this area critically depend on the accessibility of large-volume and high-quality data, sharing data between institutions faces various ethical and legal constraints as well as organizational and technical obstacles. METHODS The Joint Imaging Platform (JIP) of the German Cancer Consortium (DKTK) addresses these issues by providing federated data analysis technology in a secure and compliant way. Using the JIP, medical image data remain in the originator institutions, but analysis and AI algorithms are shared and jointly used. Common standards and interfaces to local systems ensure permanent data sovereignty of participating institutions. RESULTS The JIP is established in the radiology and nuclear medicine departments of 10 university hospitals in Germany (DKTK partner sites). In multiple complementary use cases, we show that the platform fulfills all relevant requirements to serve as a foundation for multicenter medical imaging trials and research on large cohorts, including the harmonization and integration of data, interactive analysis, automatic analysis, federated machine learning, and extensibility and maintenance processes, which are elementary for the sustainability of such a platform. CONCLUSION The results demonstrate the feasibility of using the JIP as a federated data analytics platform in heterogeneous clinical information technology and software landscapes, solving an important bottleneck for the application of AI to large-scale clinical imaging data

Global Health Informatics

Global Health Informatics
Author: Heimar Marin,Eduardo Massad,Marco Antonio Gutierrez,Roberto Jaime Rodrigues,Daniel Sigulem
Publsiher: Academic Press
Total Pages: 312
Release: 2016-12-08
ISBN 10: 0128046171
ISBN 13: 9780128046173
Language: EN, FR, DE, ES & NL

Global Health Informatics Book Review:

Global Health Informatics: How Information Technology Can Change Our Lives in a Globalized World discusses the critical role of information and communication technologies in health practice, health systems management and research in increasingly interconnected societies. In a global interconnected world the old standalone institutional information systems have proved to be inadequate for patient-centered care provided by multiple providers, for the early detection and response to emerging and re-emerging diseases, and to guide population-oriented public health interventions. The book reviews pertinent aspects and successful current experiences related to standards for health information systems; digital systems as a support for decision making, diagnosis and therapy; professional and client education and training; health systems operation; and intergovernmental collaboration. Discusses how standalone systems can compromise health care in globalized world Provides information on how information and communication technologies (ICT) can support diagnose, treatment, and prevention of emerging and re-emerging diseases Presents case studies about integrated information and how and why to share data can facilitate governance and strategies to improve life conditions

Genomic Epidemiology Data Infrastructure Needs for SARS CoV 2

Genomic Epidemiology Data Infrastructure Needs for SARS CoV 2
Author: National Academies of Sciences, Engineering, and Medicine,Division on Earth and Life Studies,Board on Life Sciences,Health and Medicine Division,Board on Health Sciences Policy,Committee on Data Needs to Monitor the Evolution of SARS-CoV-2
Publsiher: National Academies Press
Total Pages: 110
Release: 2020-10-29
ISBN 10: 0309680913
ISBN 13: 9780309680912
Language: EN, FR, DE, ES & NL

Genomic Epidemiology Data Infrastructure Needs for SARS CoV 2 Book Review:

In December 2019, new cases of severe pneumonia were first detected in Wuhan, China, and the cause was determined to be a novel beta coronavirus related to the severe acute respiratory syndrome (SARS) coronavirus that emerged from a bat reservoir in 2002. Within six months, this new virusâ€"SARS coronavirus 2 (SARS-CoV-2)â€"has spread worldwide, infecting at least 10 million people with an estimated 500,000 deaths. COVID-19, the disease caused by SARS-CoV-2, was declared a public health emergency of international concern on January 30, 2020 by the World Health Organization (WHO) and a pandemic on March 11, 2020. To date, there is no approved effective treatment or vaccine for COVID-19, and it continues to spread in many countries. Genomic Epidemiology Data Infrastructure Needs for SARS-CoV-2: Modernizing Pandemic Response Strategies lays out a framework to define and describe the data needs for a system to track and correlate viral genome sequences with clinical and epidemiological data. Such a system would help ensure the integration of data on viral evolution with detection, diagnostic, and countermeasure efforts. This report also explores data collection mechanisms to ensure a representative global sample set of all relevant extant sequences and considers challenges and opportunities for coordination across existing domestic, global, and regional data sources.

Future of Patient Data

Future of Patient Data
Author: Tim Jones,Caroline Dewing
Publsiher: Createspace Independent Publishing Platform
Total Pages: 134
Release: 2018-05-07
ISBN 10: 9781718864580
ISBN 13: 1718864582
Language: EN, FR, DE, ES & NL

Future of Patient Data Book Review:

We are witnessing a growing revolution around the provision of healthcare. Much is being driven by the proliferation of medical data and the technology that supports this. As the pressures on healthcare providers continue to escalate, the better collection, management and use of more patient-specific information provides a significant opportunity for innovation and change. The Future Agenda team made this, the Future of Patient Data, the focus of our major Open Foresight project for 2017/18 - 12 discussions across 11 countries, gathering views from over 300 experts. This report shares the findings from the Future of Patient Data research project. It highlights several important emerging issues that are the source of major differences of opinion around the world. These include how to best accommodate rising data sovereignty concerns, the privatisation of health information and the growing value of health data. Some of the challenges and opportunities are technical in nature, but many are concerned with different ethical, philosophical and cultural approaches to health and how we treat the sick in society.

Data Management Analytics and Innovation

Data Management  Analytics and Innovation
Author: Neha Sharma,Amlan Chakrabarti,Valentina Emilia Balas
Publsiher: Springer Nature
Total Pages: 740
Release: 2019-10-24
ISBN 10: 9813299495
ISBN 13: 9789813299498
Language: EN, FR, DE, ES & NL

Data Management Analytics and Innovation Book Review:

This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.

Sharing Clinical Trial Data

Sharing Clinical Trial Data
Author: Institute of Medicine,Board on Health Sciences Policy,Committee on Strategies for Responsible Sharing of Clinical Trial Data
Publsiher: National Academies Press
Total Pages: 304
Release: 2015-04-20
ISBN 10: 0309316324
ISBN 13: 9780309316323
Language: EN, FR, DE, ES & NL

Sharing Clinical Trial Data Book Review:

Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research--from funders, to researchers, to journals, to physicians, and ultimately, to patients.

Understanding Population Health Analytics

Understanding Population Health Analytics
Author: Martha Sylvia,Ines Vigil
Publsiher: Jones & Bartlett Learning
Total Pages: 400
Release: 2021-03
ISBN 10: 1284182479
ISBN 13: 9781284182477
Language: EN, FR, DE, ES & NL

Understanding Population Health Analytics Book Review:

"Binding: PB"--

Smart Health

Smart Health
Author: Andreas Holzinger,Carsten Röcker,Martina Ziefle
Publsiher: Springer
Total Pages: 275
Release: 2015-02-24
ISBN 10: 3319162268
ISBN 13: 9783319162263
Language: EN, FR, DE, ES & NL

Smart Health Book Review:

Prolonged life expectancy along with the increasing complexity of medicine and health services raises health costs worldwide dramatically. Whilst the smart health concept has much potential to support the concept of the emerging P4-medicine (preventive, participatory, predictive, and personalized), such high-tech medicine produces large amounts of high-dimensional, weakly-structured data sets and massive amounts of unstructured information. All these technological approaches along with “big data” are turning the medical sciences into a data-intensive science. To keep pace with the growing amounts of complex data, smart hospital approaches are a commandment of the future, necessitating context aware computing along with advanced interaction paradigms in new physical-digital ecosystems. The very successful synergistic combination of methodologies and approaches from Human-Computer Interaction (HCI) and Knowledge Discovery and Data Mining (KDD) offers ideal conditions for the vision to support human intelligence with machine learning. The papers selected for this volume focus on hot topics in smart health; they discuss open problems and future challenges in order to provide a research agenda to stimulate further research and progress.

Machine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine
Author: Subhi J. Al'Aref,Gurpreet Singh,Lohendran Baskaran,Dimitri Metaxas
Publsiher: Academic Press
Total Pages: 454
Release: 2020-11-20
ISBN 10: 0128202742
ISBN 13: 9780128202746
Language: EN, FR, DE, ES & NL

Machine Learning in Cardiovascular Medicine Book Review:

Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Advances in Molecular Pathology 2018

Advances in Molecular Pathology 2018
Author: Anonim
Publsiher: Elsevier Health Sciences
Total Pages: 264
Release: 2018-10-09
ISBN 10: 0323639666
ISBN 13: 9780323639668
Language: EN, FR, DE, ES & NL

Advances in Molecular Pathology 2018 Book Review:

This inaugural issue of Advances in Molecular Pathology will provide a comprehensive review of the most current practices, trends, and developments in the field of Molecular Pathology. Publishing on an annual basis, the volume will be divided into 7 sections: Genetics, Hematopathology, Infectious Disease, Pharmacogenomics, Informatics, Solid tumors, and Identity/HLA. Led by Dr. Gregory Tsongalis of Dartmouth University, a team of experienced pathologists from institutions across the country oversee annual topic and expert author selection. Topics discussed in this volume include, but are not limited to: whole genome sequencing in critically ill children, bioinformatics in clinical genomic sequencing, comprehensive monitoring of patients with chronic myeloid leukemia, genetic biomarkers in the biology and clinical workup of chronic lymphocytic leukemia, metagenomics in infectious disease, point of care molecular testing, pharmacogenomics in oncology, clinical uses of panel testing vs. single gene testing, large scale data sharing initiatives in genomic oncology, clinical NGS assays for solid tumors emerging concepts in liquid biopsy the cell line and tissue misidentification problem, and cell line detective work.

Data Science and Medical Informatics in Healthcare Technologies

Data Science and Medical Informatics in Healthcare Technologies
Author: Nguyen Thi Dieu Linh,Zhongyu (Joan) Lu
Publsiher: Springer Nature
Total Pages: 86
Release: 2021-06-19
ISBN 10: 9811630291
ISBN 13: 9789811630293
Language: EN, FR, DE, ES & NL

Data Science and Medical Informatics in Healthcare Technologies Book Review:

This book highlights a timely and accurate insight at the endeavour of the bioinformatics and genomics clinicians from industry and academia to address the societal needs. The contents of the book unearth the lacuna between the medication and treatment in the current preventive medicinal and pharmaceutical system. It contains chapters prepared by experts in life sciences along with data scientists for examining the circumstances of health care system for the next decade. It also highlights the automated processes for analyzing data in clinical trial research, specifically for drug development. Additionally, the data science solutions provided in this book help pharmaceutical companies to improve on what had historically been manual, costly and laborious process for cross-referencing research in clinical trials on drug development, while laying the groundwork for use with a full range of other drugs for the conditions ranging from tuberculosis, to diabetes, to heart attacks and many others.