Data Science in Healthcare

• Autore: Hulsen Tim
• Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
• Descrizione fisica: 1 online resource (212 p.)
• Soggetto topico: Medicine and Nursing; Pharmacology
• Soggetto non controllato: apache spark; Arabic language; arteriovenous fistula; artificial intelligence; big data; breast cancer diagnosis; case fatality rate; chronic kidney disease (CKD); computed tomography; coronavirus; COVID-19; cross-validation; data exploratory techniques; data management; data science; data sharing; depression; dialysis; digital technology; distributed computing; early-warning model; end stage kidney disease; end-stage kidney disease (ESKD); genetic algorithm; hand-foot-and-mouth disease; healthcare; kidney failure; kidney replacement therapy (KRT); machine learning; machine learning models; mental health; metabolic syndrome; metabolically healthy obese phenotype; n/a; naïve Bayes classifiers; neural network; non-specialist health worker; obesity; outbreak prediction; pilot study; pneumonia; precision medicine; primary care; psychological treatment; risk prediction; SARS-CoV-2; sentinel surveillance system; smart cities; smart governance; smart healthcare; smoking; social distancing; social media; task sharing; thoracic pain; training; tree classification; Triple Bottom Line (TBL); tumors classification; Twitter; vascular access surveillance
• Persona (resp. second.): HulsenTim
• Sommario/riassunto: 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.
• Titolo autorizzato: Data Science in Healthcare
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910576885103321
• Lo trovi qui: Univ. Federico II