0000000000309781

AUTHOR

Claudia Amato

showing 4 related works from this author

Prediction of the hemoglobin level in hemodialysis patients using machine learning techniques

2013

HighlightsDifferent prediction algorithms were used to predict Hb levels in CRF patients.Prediction errors in the validation cohorts of patients were around 0.6g/dl.Difficulty to obtain lower errors due to the measuring machine precision (0.2g/dl).Relevance analysis of features have been applied for each predictor. Patients who suffer from chronic renal failure (CRF) tend to suffer from an associated anemia as well. Therefore, it is essential to know the hemoglobin (Hb) levels in these patients. The aim of this paper is to predict the hemoglobin (Hb) value using a database of European hemodialysis patients provided by Fresenius Medical Care (FMC) for improving the treatment of this kind of …

AdultMaleAdolescentmedicine.medical_treatmentHealth InformaticsMachine learningcomputer.software_genreDisease clusterSensitivity and SpecificityHemoglobinsYoung AdultArtificial IntelligenceRenal DialysismedicineHumansComputer SimulationCluster analysisErythropoietinAgedAged 80 and overDose-Response Relationship DrugArtificial neural networkbusiness.industryModels CardiovascularLinear modelReproducibility of ResultsAnemiaMiddle AgedRegressionDrug Therapy Computer-AssistedComputer Science ApplicationsSupport vector machineTreatment OutcomeAdaptive resonance theoryFemaleHemodialysisArtificial intelligenceDrug MonitoringbusinesscomputerAlgorithmsBiomarkersSoftwareComputer Methods and Programs in Biomedicine
researchProduct

Preface to Data Mining in Biomedical Informatics and Healthcare

2013

EngineeringHealth Administration Informaticsbusiness.industryHealth careTranslational research informaticsData miningbusinesscomputer.software_genreHealth informaticsData sciencecomputer2013 IEEE 13th International Conference on Data Mining Workshops
researchProduct

Performance of a Predictive Model for Long-Term Hemoglobin Response to Darbepoetin and Iron Administration in a Large Cohort of Hemodialysis Patients

2016

International audience; Anemia management, based on erythropoiesis stimulating agents (ESA) and iron supplementation, has become an increasingly challenging problem in hemodialysis patients. Maintaining hemodialysis patients within narrow hemoglobin targets, preventing cycling outside target, and reducing ESA dosing to prevent adverse outcomes requires considerable attention from caregivers. Anticipation of the long-term response (i.e. at 3 months) to the ESA/iron therapy would be of fundamental importance for planning a successful treatment strategy. To this end, we developed a predictive model designed to support decision-making regarding anemia management in hemodialysis (HD) patients tr…

MalePediatricsBlood transfusionDarbepoetin alfaPhysiologymedicine.medical_treatment030232 urology & nephrologylcsh:Medicine030204 cardiovascular system & hematologyFerric CompoundsBiochemistryGlucaric AcidHemoglobinsMathematical and Statistical Techniques0302 clinical medicineMedicine and Health SciencesDarbepoetin alfaErythropoiesislcsh:ScienceFerric Oxide SaccharatedMultidisciplinaryPharmaceuticsDisease ManagementAnemia[SDV.MHEP.HEM]Life Sciences [q-bio]/Human health and pathology/HematologyHematologyMiddle Aged3. Good healthNephrologyInjections IntravenousPhysical SciencesFemaleHemodialysisStatistics (Mathematics)Research Articlemedicine.drugComputer and Information Sciencesmedicine.medical_specialtyAnemiaResearch and Analysis Methods03 medical and health sciencesDose Prediction MethodsRenal DialysisArtificial IntelligenceMedical DialysismedicineHumansHemoglobinDosingStatistical MethodsIron Deficiency AnemiaIntensive care medicineArtificial Neural NetworksAgedRetrospective StudiesComputational NeuroscienceModels Statisticalbusiness.industrylcsh:RBiology and Life SciencesComputational BiologyProteinsRetrospective cohort studymedicine.diseaseIron-deficiency anemiaHematinicsKidney Failure ChronicCognitive Sciencelcsh:QNeural Networks ComputerHemoglobinPhysiological ProcessesbusinessMathematicsNeuroscienceForecasting
researchProduct

Role of  1-Adrenoceptor Subtypes in Pupil Dilation Studied With Gene-Targeted Mice

2014

PURPOSE The α₁A-adrenoceptor (α₁A-AR) subtype was suggested to mediate contraction and trophic effects in the iris dilator muscle, and thus its pharmacological blockade may be involved in intraoperative floppy iris syndrome. We tested the hypothesis that the α₁A-AR mediates pupil dilation and trophic effects in the mouse iris. METHODS The α₁-AR subtype mRNA expression was quantified in iris tissue by real-time PCR. To assess the role of individual α₁-ARs for mediating pupil dilation, the α₁-AR agonist phenylephrine was topically applied to the ocular surface of mice deficient in one of the three α₁-AR subtypes (α₁A-AR(-/-), α₁B-AR(-/-), α₁D-AR(-/-), respectively) and wild-type controls. Cha…

medicine.medical_specialtyurogenital systemIntraoperative floppy iris syndromeAnatomyBiologymedicine.diseaseSensory SystemsPupilCellular and Molecular NeuroscienceOphthalmologyIris dilator muscleEndocrinologyAtrophyInternal medicinemedicinePupillary responseMydriasismedicine.symptomReceptorPhenylephrinemedicine.drugInvestigative Ophthalmology & Visual Science
researchProduct