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A prototype of a real-time solution on mobile devices for heart tele-auscultation.

, , and . PETRA, page 30:1-30:8. ACM, (2015)

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On Evaluating Blood Pressure Through Photoplethysmography., , and . IoT 360 (1), volume 169 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 523-529. (2015)A Real-time m-Health Monitoring System: An Integrated Solution Combining the Use of Several Wearable Sensors and Mobile Devices., , , , and . HEALTHINF, page 545-552. SciTePress, (2017)Voice Disorder Identification by Using Machine Learning Techniques., , and . IEEE Access, (2018)A prototype of a real-time solution on mobile devices for heart tele-auscultation., , and . PETRA, page 30:1-30:8. ACM, (2015)A Wellness Mobile Application for Smart Health: Pilot Study Design and Results., , and . Sensors, 17 (3): 611 (2017)Multi-purpose mobile monitoring system based on automatic extraction of rule-sets., , and . BHI, page 630-634. IEEE, (2014)Non-Invasive Risk Stratification of Hypertension: A Systematic Comparison of Machine Learning Algorithms., , and . J. Sens. Actuator Networks, 9 (3): 34 (2020)To What Extent It Is Possible to Predict Falls due to Standing Hypotension by Using HRV and Wearable Devices? Study Design and Preliminary Results from a Proof-of-Concept Study., , , , and . IWAAL, volume 8868 of Lecture Notes in Computer Science, page 167-170. Springer, (2014)A Novel Deep Learning Approach for Colon and Lung Cancer Classification Using Histopathological Images., , and . e-Science, page 1-10. IEEE, (2023)On Finding Explicit Rules for Personalized Forecasting of Obstructive Sleep Apnea Episodes., , and . IRI, page 326-333. IEEE Computer Society, (2015)