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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 personalisedmedicine 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 implementationof 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. |
