Data Science in Healthcare

• Muut tekijät: Hulsen, Tim (Toimittaja)
• Aineistotyyppi: Elektroninen Kirjan osa
• Kieli: englanti
• Julkaistu: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Aiheet: Medicine; Pharmacology; 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
• Linkit: DOAB: download the publication; DOAB: description of the publication

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...