about
Aid decision algorithms to estimate the risk in congenital heart surgery.Monitoring-Based Model for Personalizing the Clinical Process of Crohn's Disease.Using machine learning methods for predicting inhospital mortality in patients undergoing open repair of abdominal aortic aneurysm.Electrooculogram filtering using wavelet and wavelet packet transforms.Power line interference filtering on surface electromyography based on the stationary wavelet packet transform.Empowerment of Patients with Hypertension through BPM, IoT and Remote Sensing.Swarm intelligence applied to the risk evaluation for congenital heart surgery.Influence of the surrounded tissue in the detection of microcalcifications using wavelets.Growing Neural Gas approach for obtaining homogeneous maps by restricting the insertion of new nodes.A Distributed Model for Stressors Monitoring Based on Environmental Smart Sensors.eFisioTrack: a telerehabilitation environment based on motion recognition using accelerometryTowards the optimisation of ceramic-based microbial fuel cells: A three-factor three-level response surface analysis designMonitoring 3D movements for the rehabilitation of joints in physiotherapySupport System for Early Diagnosis of Chronic Obstructive Pulmonary Disease Based on the Service-Oriented Architecture Paradigm and Business Process Management Strategy: Development and Usability Survey Among Patients and Health Care ProvidersBusiness Process Management for optimizing clinical processes: A systematic literature reviewModelling the energy harvesting from ceramic-based microbial fuel cells by using a fuzzy logic approachLumbatex: A Wearable Monitoring System Based on Inertial Sensors to Measure and Control the Lumbar Spine MotionChess Practice as a Protective Factor in DementiaA decision support system for predicting the treatment of ectopic pregnancies
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Q38920016-20C1AB92-3138-4B80-AA1A-7FCD50334806Q39415211-BE78771D-A7EA-42E3-916A-50B80A99BF77Q39617948-746E3266-FE41-4397-B7D6-60DC1CFF3717Q40142536-C0A0482D-9AC8-493E-8316-4BA03268F65AQ43851407-75F15EE4-4A5B-4F1C-8661-6E608C1594C2Q47108624-A801B243-87BF-4DE4-8996-3C1C75F0C272Q50743009-72948950-23ED-4A46-8A4F-AFE13A317C3DQ50743024-9514FB9A-D9B7-4ACD-9ACC-402ADB38C46BQ51099167-AE79597A-E41C-43C8-880D-945545613551Q55393789-F4B31AC8-F101-49B2-9796-A9A04576B9D4Q57730359-D8783210-9F70-4CAD-95CC-09410D68F9F2Q64111779-A9AD7336-D53D-4F81-8962-9C9E402BF28DQ83225733-7698108B-8125-49BF-9A47-F569A3DD041FQ90387427-D6A4B687-6302-4500-B039-5A1C7349A246Q90462953-485BAE6B-93F2-41BC-BA16-740C80D34102Q91582804-3D92B7F2-D74E-4826-88EB-AAE636F7EB42Q91707405-67FA2EDA-F554-4EA1-B906-7A152E42CE65Q92815173-4E93B970-C7A2-4D38-A370-D3506AE7F64EQ92840293-A2578936-6B3A-43EE-9F6B-1D6BE05B659E
P50
description
investigador
@es
researcher
@en
wetenschapper
@nl
name
Daniel Ruiz-Fernandez
@en
Daniel Ruiz-Fernandez
@nl
type
label
Daniel Ruiz-Fernandez
@en
Daniel Ruiz-Fernandez
@nl
prefLabel
Daniel Ruiz-Fernandez
@en
Daniel Ruiz-Fernandez
@nl
P31
P496
0000-0002-8919-8863