Mathematics for Healthcare

Dublin Core

Title

Mathematics for Healthcare

Subject

Mathematics for Healthcare

Description

Appropriate mathematical tools and methodologies are critical for ensuring robust and reliable computational model predictions based on medical and healthcare data in the era of the digital health revolution (Duggal et al., 2018). Patient-specific approaches are being increasingly pursued, with
simulations benchmarked by clinical data (e.g., brain activity recordings; Breakspear, 2017) obtained in non-invasive manner on individual level (e.g., resting state; Spetsieris et al., 2015). Precision Medicine, although not a new concept, is gaining momentum (Hodson, 2016) powered by the ever increasing volume of patients data (Colijn et al.). Quantifying patient similarity is an important challenge that is critical in predicting patients’ disease trajectories (Sharafoddini et al., 2017). In an opinion article (Brown) patient similarity concept has been introduced as a paradigm
shift in optimizing personalisation of patient care.

Creator

Krasimira Tsaneva-Atanasova, Vanessa Diaz-Zuccarini

Source

https://www.frontiersin.org/research-topics/4555/mathematics-for-healthcare-as-part-of-computational-medicine

Publisher

Frontiers Media SA

Date

2018

Contributor

Baihaqi

Rights

Creative Commons

Format

PDF

Language

English

Type

Textbooks

Files

Citation

Krasimira Tsaneva-Atanasova, Vanessa Diaz-Zuccarini , “Mathematics for Healthcare,” Open Educational Resource (OER) - USK Library, accessed July 23, 2024, http://uilis.usk.ac.id/oer/items/show/2937.

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