01174cam0 2200265 450 E60020005845720161128100434.020100118d2002 |||||ita|0103 baitaITImportazioni ceramiche corinzie e imitazioni locali dall'area archeologica di S. Restituta (Lacco Ameno d'Ischia) VIII sec. a. C.Vincenzo Franciosicon la collaborazione di Simona SperanzaNapoliJovene2002103 p.ill.21 cm(ac)Franciosi, VincenzoAF00012851070323973SPERANZA, SimonaAF00023022070ITUNISOB20161128RICAUNISOBUNISOBFondo|Craveri147335E600200058457M 102 Monografia moderna SBNMFondo|Craveri000234Si147335CraveridonocatenacciUNISOBUNISOB20100118084236.020161128100434.0catenacciModalità di consultazione vedi home page Biblioteca link FondiImportazioni ceramiche corinzie e imitazioni locali dall'area archeologica di S. Restituta (Lacco Ameno d'Ischia) VIII sec. a. C1706672UNISOB04286nam 2201105z- 450 991057688510332120220621(CKB)5720000000008323(oapen)https://directory.doabooks.org/handle/20.500.12854/84486(oapen)doab84486(oapen)84486(EXLCZ)99572000000000832320202206d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierData Science in HealthcareBaselMDPI - Multidisciplinary Digital Publishing Institute20221 online resource (212 p.)3-0365-3983-2 3-0365-3984-0 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.Medicine and NursingbicsscPharmacologybicsscapache sparkArabic languagearteriovenous fistulaartificial intelligencebig databreast cancer diagnosiscase fatality ratechronic kidney disease (CKD)computed tomographycoronavirusCOVID-19cross-validationdata exploratory techniquesdata managementdata sciencedata sharingdepressiondialysisdigital technologydistributed computingearly-warning modelend stage kidney diseaseend-stage kidney disease (ESKD)genetic algorithmhand-foot-and-mouth diseasehealthcarekidney failurekidney replacement therapy (KRT)machine learningmachine learning modelsmental healthmetabolic syndromemetabolically healthy obese phenotypen/anaïve Bayes classifiersneural networknon-specialist health workerobesityoutbreak predictionpilot studypneumoniaprecision medicineprimary carepsychological treatmentrisk predictionSARS-CoV-2sentinel surveillance systemsmart citiessmart governancesmart healthcaresmokingsocial distancingsocial mediatask sharingthoracic paintrainingtree classificationTriple Bottom Line (TBL)tumors classificationTwittervascular access surveillanceMedicine and NursingPharmacologyHulsen Timedt1302275Hulsen TimothBOOK9910576885103321Data Science in Healthcare3026328UNINA