Real-Time Diagnosis Algorithms in Biomedical Applications and Decision Support Tools

doi:10.3390/books978-3-7258-1300-1

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Hardback

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Keywords

gas sensors; exhaled acetone detection; diabetes; portable breath analyzer; object detection; standard line for brain; faster R-CNN; medical image analysis; magnetic resonance imaging; neurodegenerative diseases; handwriting analysis; survey; balance; center of pressure (COP); segmentalized principal component analysis (sPCA); equilibrium score (EQs); empirical mode decomposition (EMD); linear regression; decision support; accelerometer; activity classification; activity trackers; machine learning; wearable systems; electroencephalogram; epileptic EEG signal classification; epilepsy; epileptogenic focus; real-time implementation; FPGA; BIS-instrumentation; biological-tissue; gain-phase detector; Bode plot; Nyquist plot; breast surface reconstruction; 3D scanning system; turntable calibration; breast cancer diagnosis; microwave imaging; medical radar; breast phantoms; Scheimpflug; 3D cornea model; early keratoconus; Corrected Distance Visual Acuity (CDVA); electrocardiography analysis; ventricular arrhythmia detection; ventricular fibrillation detection; ventricular tachycardia detection; ECG signal classification; Topological Data Analysis; representation of point cloud; persistent diagram representation; landscape representation; silhouette representation

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Real-Time Diagnosis Algorithms in Biomedical Applications and Decision Support Tools

Edited by

June 2024

218 pages

ISBN 978-3-7258-1299-8 (Hardback)
ISBN 978-3-7258-1300-1 (PDF)

https://doi.org/10.3390/books978-3-7258-1300-1

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This is a Reprint of the Special Issue Real-Time Diagnosis Algorithms in Biomedical Applications and Decision Support Tools that was published in

Engineering

Summary

Daily clinical practice is introducing new devices and tools that support doctors in achieving a better diagnosis. This Special Issue shows ten application cases where an algorithm or device is proposed to provide better information to doctors and help them to get more data, leading to better diagnosis and treatment prescription. The cases described here show both hardware and software, including the use of recent artificial intelligence and deep learning techniques.