An Information Technology Framework For Predictive Preventive And Personalised Medicine

This book explores how PPPM, clinical practice, and basic research could be best served by information technology (IT). A use-case was developed for hepatocellular carcinoma (HCC). The subject was approached with four interrelated tasks: (1) review of clinical practices relating to HCC; (2) propose an IT system relating to HCC, including clinical decision support and research needs; (3) determine how a clinical liver cancer center can contribute; and, (4) examine the enhancements and impact that the first three tasks will have on the management of HCC. An IT System for Personalized Medicine (ITS-PM) for HCC will provide the means to identify and determine the relative value of the wide number of variables, including clinical assessment of the patient -- functional status, liver function, degree of cirrhosis, and comorbidities; tumor biology, at a molecular, genetic and anatomic level; tumor burden and individual patient response; medical and operative treatments and their outcomes.

The edition will cover proceedings of the second International conference on digital health Technologies (ICDHT 2019). The conference will address the topic of P4 medicine from the information technology point of view, and will be focused on the following topics: - Artificial Intelligence for health • Knowledge extraction • Decision-aid systems • Data analysis and risk prediction • Machine learning, deep learning - Health data processing • Data preprocessing, cleaning, management and mining • Computer-aided detection • Big data analysis, prediction and prevention • Cognitive algorithms for healthcare handling dynamic context management • Augmented reality, Motion detection and activity recognition - Devices, infrastructure and communication • Wearable & connected devices • Communication infrastructures, architectures and standards Blockchain for e-Health • Computing/storage infrastructures for e-Health • IoT devices & architectures for Smart Healthcare - Health information systems • Telemedicine, Teleservices • Computing/storage infrastructures for e-Health • Clinical Data Visualisation Standards - Security and privacy for e-health • Health data Analytics for Security and Privacy • E-health Software and Hardware Security • Embedded Security for e-health - Applications in P4 medicine

In this book, practicing physicians and experts in anticipation present arguments for a new understanding of medicine. Their contributions make it clear that medicine is the decisive test for anticipation. The reader is presented with a provocative hypothesis: If medicine will align itself with the anticipatory condition of life, it can prompt the most important revolution in our time. To this end, all stakeholders—medical practitioners, patients, scientists, and technology developers—will have to engage in the conversation. The book makes the case for the transition from expensive, and only marginally effective, reactive treatment through “spare parts” (joint replacements, organ transplants) and reliance on pharmaceuticals (antibiotics, opiates) to anticipation-informed healthcare. Readers will understand why the current premise of treating various behavioral conditions (attention deficit disorder, hyperactivity, schizophrenia) through drugs has to be re-evaluated from the perspective of anticipation. In the manner practiced today, medicine generates dependence and long-lasting damage to those it is paid to help. As we better understand the nature of the living, the proactive view of healthcare, within which the science and art of healing fuse, becomes a social and political mandate.

This volume presents advanced bio/medical sciences with a particular value for translating research achievements into daily medical practice in the framework of Predictive, Preventive and Personalised Medicine (3PM/PPPM). First two decades of the 21st century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The paradigm change from reactive to predictive preventive and personalised medicine is essential to promote population health by application of individualised patient profiling, multi-parametric analysis leading to cost-effective targeted prevention. To this end, inadequate data for risk assessment on speed and urgency of COVID-19, combined with increased globalization of human society, led to the rapid spread of COVID-19. Despite an abundance of digital methods that could be used in slowing or stopping this virus and future pandemics, the world remains unprepared, and lessons have not been learned from previous cases of pandemics. The book presents PPPM strategies which might be of great clinical utility for future pandemics. In a long-term way, a significantly improved healthcare economy is one of the clear benefits of the proposed paradigm shift; a tight collaboration between all stakeholders including scientific community, healthcare providers, patient organisations, policy-makers and educators is analysed for the smooth implementation of the 3PM concepts. Further issues linked to big data management and medical ethics have to be carefully treated in the context of application of artificial intelligence in medicine.

This collection, entitled Digital Health for Predictive, Preventive, Personalized and Participatory Medicine contains the proceedings of the first International conference on digital healthtechnologies (ICDHT 2018). Ten recent contributions in the fields of Artificial Intelligence (AI) and machine learning, Internet of Things (IoT) and data analysis, all applied to digital health. This collection enables researchers to learn about recent advances in the above mentioned fields. It brings a technological viewpoint of P4 medicine. Readers will discover how advanced Information Technology (IT) tools can be used for healthcare. For instance, the use of connected objects to monitor physiological parameters is discussed. Moreover, even if compressed sensing is nowadays a common acquisition technique, its use for IoT is presented in this collection through one of the pioneer works in the field. In addition, the use of AI for epileptic seizure detection is also discussed as being one of the major concerns of predictive medicine both in industrialized and low-income countries. This work is edited by Prof. Lotfi Chaari, professor at the University of Sfax, and previously at the University of Toulouse. This work comes after more than ten years of expertise in the biomedical signal and image processing field.

Pharmacogenomics supports personalized medicine by translating genome-based knowledge into clinical practice, offering enhanced benefit for patients and health-care systems at large. Current routine practice for diagnosing and treating patients is conducted by correlating parameters such as age, gender and weight with risks and expected treatment outcomes. In the new era of personalized medicine the healthcare provider is equipped with improved ability to prevent, diagnose, treat and predict outcomes on the basis of complex information sources, including genetic and genomic data. Targeted therapy and reliable prediction of expected outcomes offer patients access to better healthcare management, by way of identifying the therapies effective for the relevant patient group, avoiding prescription of unnecessary treatment and reducing the likelihood of developing adverse drug reactions.

This collection, entitled #x1B;(S0#x1B;(B Digital Health for Predictive, Preventive, Personalized and Participatory Medicine#x1B;(S1#x1B;(B contains the proceedings of the first International conference on digital health technologies (ICDHT 2018). Ten recent contributions in the fields of Artificial Intelligence (AI) and machine learning, Internet of Things (IoT) and data analysis, all applied to digital health. This collection enables researchers to learn about recent advances in the above mentioned fields. It brings a technological viewpoint of P4 medicine. Readers will discover how advanced Information Technology (IT) tools can be used for healthcare. For instance, the use of connected objects to monitor physiological parameters is discussed. Moreover, even if compressed sensing is nowadays a common acquisition technique, its use for IoT is presented in this collection through one of the pioneer works in the field. In addition, the use of AI for epileptic seizure detection is also discussed as being one of the major concerns of predictive medicine both in industrialized and low-income countries. This work is edited by Prof. Lotfi Chaari, professor at the University of Sfax, and previously at the University of Toulouse. This work comes after more than ten years of expertise in the biomedical signal and image processing field.

Practitioners are increasingly adopting a personalised medicine approach to individually tailored patient care, especially disease diagnosis and treatment with the use of biomarkers. However, development and implementation of such approaches to chronic disease prevention need further investigation and concerted efforts for proper use in healthcare systems. This book provides high-quality, multidisciplinary knowledge from research in personalised medicine, specifically personalised prevention of chronic disease. It addresses different perspectives of prevention in the field, and is the outcome of a four-year work of the Personalized prevention of Chronic Disease (PRECeDI) Consortium, a multi-disciplinary and multi-professional team of experts. The Consortium jointly agreed to document and address the five aspects or domains of personalised medicine and prevention as individual chapters: Identification of biomarkers for the prevention of chronic disease Evaluation of predictive genomic applications Ethico-legal and policy issues surrounding personalised medicine Roles and responsibilities of stakeholders in informing healthy individuals on their genome: a sociotechnical analysis Identification of organisational models for the provision of predictive genomic applications The book focuses on the Consortium's recommendations that are derived from each of these domains based on up-to-date evidence and research that the authors write, follow, and systematically organise and report. Personalisation of health care is, eventually, a driver of innovation in research and healthcare systems. With this SpringerBrief on Personalised Health Care: Fostering Precision Medicine Advancements for Gaining Population Health Impact, the Consortium provides further evidence of the clinical validity and utility of personalised medicine with special emphasis on the prevention of chronic diseases. The book is a useful resource for policy makers, industry and healthcare professionals, scientists, technology-sector professionals, investors, citizens, and private companies that need proper advice to realise the potential of personalised medicine.