0000000000635950

AUTHOR

M Castellano

showing 6 related works from this author

Final Report of the Oceanographic Survey NextData201. Project NEXTDATA WP-1.5 : Paleoclimatic Data from Marine Sediments

2013

The retrieval of series of proxy data on the past climate will serve to acquire a deeper understanding of the climate system and a more accurate prediction of its future development, as a priority task for the scientific community. In particular, the analysis of climate data of the past is an essential tool for studying the dynamics of the earth's climatic system in conditions different from present ones, and irreplaceable for testing the validity of medium- and long-term forecasting models. The determination of the influence of anthropogenic impacts on the planet’s environment is predicated on a clear understanding of the natural ways in which the earth's climate responds to the complex se…

Settore GEO/02 - Geologia Stratigrafica E SedimentologicaSettore GEO/01 - Paleontologia E PaleoecologiaSediment Core Micropaleontology Sedimentology Paleoclimatology Tephra
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Distributed medical images analysis on a Grid infrastructure

2007

In this paper medical applications on a Grid infrastructure, the MAGIC-5 Project, are presented and discussed. MAGIC-5 aims at developing Computer Aided Detection (CADe) software for the analysis of medical images on distributed databases by means of GRID Services. The use of automated systems for analyzing medical images improves radiologists’ performance; in addition, it could be of paramount importance in screening programs, due to the huge amount of data to check and the cost of related manpower. The need for acquiring and analyzing data stored in different locations requires the use of Grid Services for the management of distributed computing resources and data. Grid technologies allow…

GRID; Virtual Organization; Medical ApplicationsComputer Networks and CommunicationsComputer scienceVirtual organizationmammographyComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONcomputer.software_genreGRID; virtual organization; CAD; mammography; medical applicationsSoftwareComputer aided diagnosimedicineMammographyCADComputer visionGridLung tumorDistributed databasemedicine.diagnostic_testmedical applicationsbusiness.industryDigital imagingGridDigital imagingHardware and ArchitectureImage analysiArtificial intelligenceData miningAlzheimer diseasevirtual organizationGRIDbusinesscomputerSoftwareMammography
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Understanding Factors Associated With Psychomotor Subtypes of Delirium in Older Inpatients With Dementia

2020

Objectives Few studies have analyzed factors associated with delirium subtypes. In this study, we investigate factors associated with subtypes of delirium only in patients with dementia to provide insights on the possible prevention and treatments. Design This is a cross-sectional study nested in the "Delirium Day" study, a nationwide Italian point-prevalence study. Setting and participants Older patients admitted to 205 acute and 92 rehabilitation hospital wards. Measures Delirium was evaluated with the 4-AT and the motor subtypes with the Delirium Motor Subtype Scale. Dementia was defined by the presence of a documented diagnosis in the medical records and/or prescription of acetylcholine…

Rehabilitation hospitalmedicine.medical_specialtyUrinary systemSocio-culturaledementia; elderly; Motor subtypes of delirium; Aged; Cross-Sectional Studies; Humans; Inpatients; Italy; Delirium; Dementiaelderly03 medical and health sciences0302 clinical medicineInternal medicinemental disordersmedicineDementiaMotor subtypes of delirium dementia elderlyHumansdementia elderly Motor subtypes of delirium030212 general & internal medicineLS4_4Medical prescriptionGeneral NursingAgedPsychomotor learningInpatientsbusiness.industryHealth PolicyMedical recordMotor subtypes of deliriumMemantineDeliriumGeneral Medicinemedicine.diseasedementia; elderly; Motor subtypes of deliriumSettore MED/26 - NEUROLOGIACross-Sectional StudiesItalyDeliriumDementiaGeriatrics and Gerontologymedicine.symptombusiness030217 neurology & neurosurgerymedicine.drug
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Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: A comparative risk a…

2014

High blood pressure, blood glucose, serum cholesterol, and BMI are risk factors for cardiovascular diseases and some of these factors also increase the risk of chronic kidney disease and diabetes. We estimated mortality from cardiovascular diseases, chronic kidney disease, and diabetes that was attributable to these four cardiometabolic risk factors for all countries and regions from 1980 to 2010.

MaleSettore MED/09 - Medicina Internakidney diseaseEndocrinology Diabetes and Metabolismhumanoscoste de las enfermedadesDiseaseGlobal HealthCohort StudiesEndocrinologyCost of Illnesscardiovascular diseaseHealth TransitionRisk Factorstransición sanitariaestudios prospectivosRenal Insufficiency Chronic -- complications -- epidemiology -- mortalityevaluación de riesgosRenal InsufficiencyProspective StudiesChronicestudios de cohortesMetabolic Syndromeeducation.field_of_studydiabetesMortality rateAge Factors; Cardiovascular Diseases; Cohort Studies; Cost of Illness; Diabetes Complications; Female; Health Surveys; Humans; Male; Metabolic Syndrome X; Prospective Studies; Renal Insufficiency Chronic; Risk Assessment; Risk Factors; Sex Factors; Spatio-Temporal Analysis; Global Health; Health Transition; Internal Medicine; Endocrinology Diabetes and Metabolism; EndocrinologyMetabolic Syndrome XCardiovascular Diseases -- complications -- epidemiology -- mortalityAge FactorsCardiovascular diseaseDiabetes Mellitus chronic kidney diseaseDiabetes Complications -- epidemiology -- mortalitySciences bio-médicales et agricolesDiabetes and MetabolismCardiovascular Diseasesencuestas de saludFemaleanálisis temporoespacialRisk assessmentcomplicaciones de la diabetesinsuficiencia renalmedicine.medical_specialtyCardiovascular disease; kidney disease; diabetes mortalityPopulationenfermedades cardiovascularesMetabolic Syndrome X -- complications -- epidemiology -- mortalityRisk AssessmentArticleDiabetes ComplicationsSex FactorsSpatio-Temporal Analysiscardiovascular disease; chronic kidney disease; diabetes; mortalityInternal medicineEnvironmental healthDiabetes mellitusmedicineAge Factors; Cardiovascular Diseases; Cohort Studies; Cost of Illness; Diabetes Complications; Female; Health Surveys; Humans; Male; Metabolic Syndrome X; Prospective Studies; Renal Insufficiency Chronic; Risk Assessment; Risk Factors; Sex Factors; Spatio-Temporal Analysis; Global Health; Health Transition; Endocrinology Diabetes and Metabolism; Internal Medicine; EndocrinologyInternal Medicinefactores de riesgoHumansRisk factorRenal Insufficiency Chroniceducationbusiness.industrydiabetes mortalitymedicine.diseasemortalityHealth SurveysEndocrinologyRelative riskAge Factors; Cardiovascular Diseases/complications; Cardiovascular Diseases/epidemiology; Cardiovascular Diseases/mortality; Cohort Studies; Cost of Illness; Diabetes Complications/epidemiology; Diabetes Complications/mortality; Female; Global Health; Health Surveys; Health Transition; Humans; Male; Metabolic Syndrome X/complications; Metabolic Syndrome X/epidemiology; Metabolic Syndrome X/mortality; Prospective Studies; Renal Insufficiency Chronic/complications; Renal Insufficiency Chronic/epidemiology; Renal Insufficiency Chronic/mortality; Risk Assessment; Risk Factors; Sex Factors; Spatio-Temporal Analysisbusinesschronic kidney diseaseKidney diseaseThe Lancet Diabetes and Endocrinology
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A completely automated CAD system for mass detection in a large mammographic database.

2006

Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing secon…

Databases FactualInformation Storage and RetrievalReproducibility of ResultsBreast NeoplasmsSensitivity and SpecificityNeural networkPattern Recognition AutomatedRadiographic Image EnhancementBreast cancerTextural featuresRadiology Information SystemsImage processingComputer-aided detection (CAD)Artificial IntelligenceCluster AnalysisDatabase Management SystemsHumansRadiographic Image Interpretation Computer-AssistedFemaleBreast cancer; Computer-aided detection (CAD); Image processing; Mammographic mass detection; Neural network; Textural featuresMammographic mass detectionAlgorithmsMammographyMedical physics
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Core description collected during Oceanographic Survey NextData2013 (12 – 19 September 2013)

2013

Sediment Core Micropaleontology Sedimentology Paleoclimatology Tephra
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