Jon Urteaga
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View article: A deep learning model for QRS delineation in organized rhythms during in-hospital cardiac arrest
A deep learning model for QRS delineation in organized rhythms during in-hospital cardiac arrest Open
A precise delineator like this could support clinical practice by quantifying QRS features to enhance diagnostic accuracy and optimize treatment strategies.
View article: Invasive arterial blood pressure delineator for cardiopulmonary resuscitation patients during pauses of chest compressions
Invasive arterial blood pressure delineator for cardiopulmonary resuscitation patients during pauses of chest compressions Open
Invasive arterial blood pressure (IBP) monitoring is important to assess patient's cardiovascular competence and guide clinical treatment. Besides, international resuscitation guidelines in force suggest its use during Cardiopulmonary Resu…
View article: Machine learning model to predict evolution of pulseless electrical activity during in-hospital cardiac arrest
Machine learning model to predict evolution of pulseless electrical activity during in-hospital cardiac arrest Open
Information hidden in the waveforms of the ECG and TTI signals, along with QRS complex features, can predict the progression of PEA. Automated methods as the one proposed in this study, could contribute to assist in the targeted treatment …
View article: Monitoring chest compressions using finger photoplethysmography in out-of-hospital cardiac arrest
Monitoring chest compressions using finger photoplethysmography in out-of-hospital cardiac arrest Open
Quality cardiopulmonary resuscitation (CPR) is crucial to increase the probability of survival during out-of-hospital cardiac arrest (OHCA). Continuous chest compressions (CCs) provided with appropriate rate are recommended by the guidelin…
View article: A Machine Learning Model for the Prognosis of Pulseless Electrical Activity during Out-of-Hospital Cardiac Arrest
A Machine Learning Model for the Prognosis of Pulseless Electrical Activity during Out-of-Hospital Cardiac Arrest Open
Pulseless electrical activity (PEA) is characterized by the disassociation of the mechanical and electrical activity of the heart and appears as the initial rhythm in 20–30% of out-of-hospital cardiac arrest (OHCA) cases. Predicting whethe…
View article: Regional Convolutional Neural Network for Cell Detection and Classification in Urinary Bladder Cancer
Regional Convolutional Neural Network for Cell Detection and Classification in Urinary Bladder Cancer Open
Bladder canceristhefourth most common type of cancer in men and the eighth in women. Patient treated for this cancer must be monitored for the rest of their live due to the recurrence of this disease.That need for monitoring makes bladder …
View article: Finger Photoplethysmography to Monitor Chest Compression Rate During Out-of-Hospital Cardiac Arrest
Finger Photoplethysmography to Monitor Chest Compression Rate During Out-of-Hospital Cardiac Arrest Open
Cardiac arrest survival rate is strongly associated with high quality cardiopulmonary resuscitation (CPR), which includes chest compression (CC) rates above 100 min -1 .Currently, defibrillator monitors use external hardware such as CPR as…