02855nam 2200397z- 450 991034675010332120210211(CKB)4920000000094213(oapen)https://directory.doabooks.org/handle/20.500.12854/52877(oapen)doab52877(EXLCZ)99492000000009421320202102d2018 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierMathematics for HealthcareFrontiers Media SA20181 online resource (284 p.)Frontiers Research Topics2-88945-577-7 In 1996, and with extraordinary prescience, Panfilov and Holden had highlighted in their seminal book 'Computational Biology of the Heart' that biology was, potentially, the most mathematical of all sciences. Fast-forward 20 years and we have seen an explotion of applications of mathematics in not only biology, but healthcare that has already produced significant breakthroughs not imaginable more than 20 years ago. Great strides have been made in explaining through quantitative methods the underlying mechanisms of human disease, not without considerable ingenuity and effort. Biological mechanisms are bewildering: complex, ever evolving, multi-scale, variable, difficult to fully access and understand. This poses immense challenges to the computational physiology community that, nevertheless, has developed an impressive arsenal of tools and methods in a vertiginous race to combat disease with the tall order of improving human healthcare. Mechanistic models are now contending with the advent of machine learning in healthcare and the hope is that both approaches will be used synergistically since the complexity of human patophysiology and the difficulty of acquiring human datasets will require both, deductive and inductive methods. This Research Topic presents work that is currently at the frontier in computational physiology with a striking range of applications, from diabetes to graft failure and using a multitude of mathematical tools. This collection of articles represents a snapshot in a field that is moving a dizzying speed, bringing understanding of fundamental mechanism and solutions to healthcare problems experienced by healthcare systems all over the world.Physiologybicssccomputational physiologydata-driven modellingmathematics for healthcaremechanistic modellingprecision medicinePhysiologyVanessa Diaz-Zuccariniauth1284069Krasimira Tsaneva-AtanasovaauthBOOK9910346750103321Mathematics for Healthcare3019258UNINA02227nam 2200445z- 450 991055754240332120211118(CKB)5400000000044183(oapen)https://directory.doabooks.org/handle/20.500.12854/74354(oapen)doab74354(EXLCZ)99540000000004418320202111d2020 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierBacterial Vaginosis, a Model of True Polymicrobial Infections: Genetics, Evolution, Clinical and Socio-Clinical ImplicationsFrontiers Media SA20201 online resource (182 p.)2-88966-222-5 This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contactBacterial Vaginosis, a Model of True Polymicrobial InfectionsInfectious & contagious diseasesbicsscScience: general issuesbicsscBacterial VaginosisGardnerellapolymicrobial infectionsInfectious & contagious diseasesScience: general issuesSwidsinski Alexanderedt1327917Vaneechoutte MarioedtCerca NunoedtSwidsinski AlexanderothVaneechoutte MarioothCerca NunoothBOOK9910557542403321Bacterial Vaginosis, a Model of True Polymicrobial Infections: Genetics, Evolution, Clinical and Socio-Clinical Implications3038275UNINA