Mathematics for Healthcare
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 o...
-д хадгалсан:
| Үндсэн зохиолчид: | , |
|---|---|
| Формат: | Online |
| Хэл сонгох: | англи |
| Хэвлэсэн: |
Frontiers Media SA
2021
|
| Нөхцлүүд: | |
| Онлайн хандалт: | 31986 |
| Шошгууд: |
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
|
| _version_ | 1869531563730927616 |
|---|---|
| author | Vanessa Diaz-Zuccarini Krasimira Tsaneva-Atanasova |
| author_browse | Krasimira Tsaneva-Atanasova Vanessa Diaz-Zuccarini |
| author_facet | Vanessa Diaz-Zuccarini Krasimira Tsaneva-Atanasova |
| author_sort | Vanessa Diaz-Zuccarini |
| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-52877 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Frontiers Media SA |
| publisherStr | Frontiers Media SA |
| record_format | ojs |
| spelling | doab-20.500.12854ir-528772024-03-31T22:45:17Z Mathematics for Healthcare Vanessa Diaz-Zuccarini Krasimira Tsaneva-Atanasova QP1-981 Q1-390 mechanistic modelling computational physiology data-driven modelling mathematics for healthcare precision medicine thema EDItEUR::M Medicine and Nursing::MF Pre-clinical medicine: basic sciences::MFG Physiology 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. 2021-02-11T18:55:29Z 2021-02-11T18:55:29Z 2019-01-23 14:53:43 2018 book 31986 16648714 9782889455775 https://directory.doabooks.org/handle/20.500.12854/52877 eng Frontiers Research Topics image/jpeg Attribution 4.0 International https://www.frontiersin.org/research-topics/4555/mathematics-for-healthcare-as-part-of-computational-medicine Frontiers Media SA 10.3389/978-2-88945-577-5 10.3389/978-2-88945-577-5 bf5ce210-e72e-4860-ba9b-c305640ff3ae 9782889455775 284 open access |
| spellingShingle | QP1-981 Q1-390 mechanistic modelling computational physiology data-driven modelling mathematics for healthcare precision medicine thema EDItEUR::M Medicine and Nursing::MF Pre-clinical medicine: basic sciences::MFG Physiology Vanessa Diaz-Zuccarini Krasimira Tsaneva-Atanasova Mathematics for Healthcare |
| title | Mathematics for Healthcare |
| title_full | Mathematics for Healthcare |
| title_fullStr | Mathematics for Healthcare |
| title_full_unstemmed | Mathematics for Healthcare |
| title_short | Mathematics for Healthcare |
| title_sort | mathematics for healthcare |
| topic | QP1-981 Q1-390 mechanistic modelling computational physiology data-driven modelling mathematics for healthcare precision medicine thema EDItEUR::M Medicine and Nursing::MF Pre-clinical medicine: basic sciences::MFG Physiology |
| topic_facet | QP1-981 Q1-390 mechanistic modelling computational physiology data-driven modelling mathematics for healthcare precision medicine thema EDItEUR::M Medicine and Nursing::MF Pre-clinical medicine: basic sciences::MFG Physiology |
| url | 31986 |
| work_keys_str_mv | AT vanessadiazzuccarini mathematicsforhealthcare AT krasimiratsanevaatanasova mathematicsforhealthcare |