Data Science in Healthcare
Data science is an interdisciplinary field that applies numerous techniques, such as machine learning, neural networks, and deep learning, to create value based on extracting knowledge and insights from available data. Advances in data science have a significant impact on healthcare. While advances...
Saved in:
Other Authors: | |
---|---|
Format: | Electronic Book Chapter |
Language: | English |
Published: |
Basel
MDPI - Multidisciplinary Digital Publishing Institute
2022
|
Subjects: | |
Online Access: | DOAB: download the publication DOAB: description of the publication |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
MARC
LEADER | 00000naaaa2200000uu 4500 | ||
---|---|---|---|
001 | doab_20_500_12854_84486 | ||
005 | 20220621 | ||
003 | oapen | ||
006 | m o d | ||
007 | cr|mn|---annan | ||
008 | 20220621s2022 xx |||||o ||| 0|eng d | ||
020 | |a books978-3-0365-3984-3 | ||
020 | |a 9783036539836 | ||
020 | |a 9783036539843 | ||
040 | |a oapen |c oapen | ||
024 | 7 | |a 10.3390/books978-3-0365-3984-3 |c doi | |
041 | 0 | |a eng | |
042 | |a dc | ||
072 | 7 | |a M |2 bicssc | |
072 | 7 | |a MMG |2 bicssc | |
100 | 1 | |a Hulsen, Tim |4 edt | |
700 | 1 | |a Hulsen, Tim |4 oth | |
245 | 1 | 0 | |a Data Science in Healthcare |
260 | |a Basel |b MDPI - Multidisciplinary Digital Publishing Institute |c 2022 | ||
300 | |a 1 electronic resource (212 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a Data science is an interdisciplinary field that applies numerous techniques, such as machine learning, neural networks, and deep learning, to create value based on extracting knowledge and insights from available data. Advances in data science have a significant impact on healthcare. While advances in the sharing of medical information result in better and earlier diagnoses as well as more patient-tailored treatments, information management is also affected by trends such as increased patient centricity (with shared decision making), self-care (e.g., using wearables), and integrated care delivery. The delivery of health services is being revolutionized through the sharing and integration of health data across organizational boundaries. Via data science, researchers can deliver new approaches to merge, analyze, and process complex data and gain more actionable insights, understanding, and knowledge at the individual and population levels. This Special Issue focuses on how data science is used in healthcare (e.g., through predictive modeling) and on related topics, such as data sharing and data management. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Medicine |2 bicssc | |
650 | 7 | |a Pharmacology |2 bicssc | |
653 | |a data sharing | ||
653 | |a data management | ||
653 | |a data science | ||
653 | |a big data | ||
653 | |a healthcare | ||
653 | |a depression | ||
653 | |a psychological treatment | ||
653 | |a task sharing | ||
653 | |a primary care | ||
653 | |a pilot study | ||
653 | |a non-specialist health worker | ||
653 | |a training | ||
653 | |a digital technology | ||
653 | |a mental health | ||
653 | |a COVID-19 | ||
653 | |a SARS-CoV-2 | ||
653 | |a pneumonia | ||
653 | |a computed tomography | ||
653 | |a case fatality rate | ||
653 | |a social distancing | ||
653 | |a smoking | ||
653 | |a metabolically healthy obese phenotype | ||
653 | |a metabolic syndrome | ||
653 | |a obesity | ||
653 | |a coronavirus | ||
653 | |a machine learning | ||
653 | |a social media | ||
653 | |a apache spark | ||
653 | |a Twitter | ||
653 | |a Arabic language | ||
653 | |a distributed computing | ||
653 | |a smart cities | ||
653 | |a smart healthcare | ||
653 | |a smart governance | ||
653 | |a Triple Bottom Line (TBL) | ||
653 | |a thoracic pain | ||
653 | |a tree classification | ||
653 | |a cross-validation | ||
653 | |a hand-foot-and-mouth disease | ||
653 | |a early-warning model | ||
653 | |a neural network | ||
653 | |a genetic algorithm | ||
653 | |a sentinel surveillance system | ||
653 | |a outbreak prediction | ||
653 | |a artificial intelligence | ||
653 | |a vascular access surveillance | ||
653 | |a arteriovenous fistula | ||
653 | |a end stage kidney disease | ||
653 | |a dialysis | ||
653 | |a kidney failure | ||
653 | |a chronic kidney disease (CKD) | ||
653 | |a end-stage kidney disease (ESKD) | ||
653 | |a kidney replacement therapy (KRT) | ||
653 | |a risk prediction | ||
653 | |a naïve Bayes classifiers | ||
653 | |a precision medicine | ||
653 | |a machine learning models | ||
653 | |a data exploratory techniques | ||
653 | |a breast cancer diagnosis | ||
653 | |a tumors classification | ||
653 | |a n/a | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/5469 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/84486 |7 0 |z DOAB: description of the publication |