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...
সংরক্ষণ করুন:
| বিন্যাস: | Online |
|---|---|
| ভাষা: | ইংরেজি |
| প্রকাশিত: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | ONIX_20220621_9783036539836_64 |
| ট্যাগগুলো: |
কোনো ট্যাগ নেই, প্রথমজন হিসাবে ট্যাগ করুন!
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| _version_ | 1869526202783367168 |
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| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-84486 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-844862024-03-31T13:08:13Z Data Science in Healthcare Hulsen, Tim data sharing data management data science big data healthcare depression psychological treatment task sharing primary care pilot study non-specialist health worker training digital technology mental health COVID-19 SARS-CoV-2 pneumonia computed tomography case fatality rate social distancing smoking metabolically healthy obese phenotype metabolic syndrome obesity coronavirus machine learning social media apache spark Twitter Arabic language distributed computing smart cities smart healthcare smart governance Triple Bottom Line (TBL) thoracic pain tree classification cross-validation hand-foot-and-mouth disease early-warning model neural network genetic algorithm sentinel surveillance system outbreak prediction artificial intelligence vascular access surveillance arteriovenous fistula end stage kidney disease dialysis kidney failure chronic kidney disease (CKD) end-stage kidney disease (ESKD) kidney replacement therapy (KRT) risk prediction naïve Bayes classifiers precision medicine machine learning models data exploratory techniques breast cancer diagnosis tumors classification n/a thema EDItEUR::M Medicine and Nursing thema EDItEUR::M Medicine and Nursing::MK Medical specialties, branches of medicine::MKG Pharmacology 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. 2022-06-21T08:38:11Z 2022-06-21T08:38:11Z 2022 book ONIX_20220621_9783036539836_64 9783036539836 9783036539843 https://directory.doabooks.org/handle/20.500.12854/84486 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/5469 https://mdpi.com/books/pdfview/book/5469 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-3984-3 10.3390/books978-3-0365-3984-3 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036539836 9783036539843 212 Basel open access |
| spellingShingle | data sharing data management data science big data healthcare depression psychological treatment task sharing primary care pilot study non-specialist health worker training digital technology mental health COVID-19 SARS-CoV-2 pneumonia computed tomography case fatality rate social distancing smoking metabolically healthy obese phenotype metabolic syndrome obesity coronavirus machine learning social media apache spark Arabic language distributed computing smart cities smart healthcare smart governance Triple Bottom Line (TBL) thoracic pain tree classification cross-validation hand-foot-and-mouth disease early-warning model neural network genetic algorithm sentinel surveillance system outbreak prediction artificial intelligence vascular access surveillance arteriovenous fistula end stage kidney disease dialysis kidney failure chronic kidney disease (CKD) end-stage kidney disease (ESKD) kidney replacement therapy (KRT) risk prediction naïve Bayes classifiers precision medicine machine learning models data exploratory techniques breast cancer diagnosis tumors classification n/a thema EDItEUR::M Medicine and Nursing thema EDItEUR::M Medicine and Nursing::MK Medical specialties, branches of medicine::MKG Pharmacology Data Science in Healthcare |
| title | Data Science in Healthcare |
| title_full | Data Science in Healthcare |
| title_fullStr | Data Science in Healthcare |
| title_full_unstemmed | Data Science in Healthcare |
| title_short | Data Science in Healthcare |
| title_sort | data science in healthcare |
| topic | data sharing data management data science big data healthcare depression psychological treatment task sharing primary care pilot study non-specialist health worker training digital technology mental health COVID-19 SARS-CoV-2 pneumonia computed tomography case fatality rate social distancing smoking metabolically healthy obese phenotype metabolic syndrome obesity coronavirus machine learning social media apache spark Arabic language distributed computing smart cities smart healthcare smart governance Triple Bottom Line (TBL) thoracic pain tree classification cross-validation hand-foot-and-mouth disease early-warning model neural network genetic algorithm sentinel surveillance system outbreak prediction artificial intelligence vascular access surveillance arteriovenous fistula end stage kidney disease dialysis kidney failure chronic kidney disease (CKD) end-stage kidney disease (ESKD) kidney replacement therapy (KRT) risk prediction naïve Bayes classifiers precision medicine machine learning models data exploratory techniques breast cancer diagnosis tumors classification n/a thema EDItEUR::M Medicine and Nursing thema EDItEUR::M Medicine and Nursing::MK Medical specialties, branches of medicine::MKG Pharmacology |
| topic_facet | data sharing data management data science big data healthcare depression psychological treatment task sharing primary care pilot study non-specialist health worker training digital technology mental health COVID-19 SARS-CoV-2 pneumonia computed tomography case fatality rate social distancing smoking metabolically healthy obese phenotype metabolic syndrome obesity coronavirus machine learning social media apache spark Arabic language distributed computing smart cities smart healthcare smart governance Triple Bottom Line (TBL) thoracic pain tree classification cross-validation hand-foot-and-mouth disease early-warning model neural network genetic algorithm sentinel surveillance system outbreak prediction artificial intelligence vascular access surveillance arteriovenous fistula end stage kidney disease dialysis kidney failure chronic kidney disease (CKD) end-stage kidney disease (ESKD) kidney replacement therapy (KRT) risk prediction naïve Bayes classifiers precision medicine machine learning models data exploratory techniques breast cancer diagnosis tumors classification n/a thema EDItEUR::M Medicine and Nursing thema EDItEUR::M Medicine and Nursing::MK Medical specialties, branches of medicine::MKG Pharmacology |
| url | ONIX_20220621_9783036539836_64 |