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Computer Aided Diagnosis Sensors

Sensors used to diagnose, monitor or treat diseases in the medical domain are known as medical sensors. There are several types of medical sensors that can be utilized for various applications, such as temperature probes, force sensors, pressure sensors, oximeters, electrocardiogram sensors that mea...

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Bibliographic Details
Main Author:	El-Baz, Ayman
Other Authors:	Giridharan, Guruprasad A., Shalaby, Ahmed, Mahmoud, Ali H.
Format:	eBook
Language:	English
Published:	Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:	Ppg Machine Learning Physiological Perfusion Radiomics Diabetic Retinopathy Smartphones Lung Sound Detection Multiple Object Tracking Brain Imaging Icc Human Papillomavirus (hpv) Suction Index Nosema Disease Feature Selection Ecg Big Healthcare Data Diabetic Retinopathy (dr) Deep Learning Suction Prevention Respiration Signal Cad System Computational Pathology Optical Imaging System Bland–altman Method Optical Coherence Tomography Angiography (octa) Rbd Motion Correction Uveitis Grading Texture Analysis Channel Data Machine Learning (ml) Vggnet Image Encryption Sars-cov-2 Skin Cancer Computer-aided Diagnosis Grade Groups Dwi Left Ventricular Assist Devices Prostate Cancer Artificial Intelligence Regression Shape Features Non-contact Spirometry Fundus Images U-net Discrete Wavelet Decomposition Cancer Convolutional Neural Networks Adc Maps Machine-learning Support Vector Machine (svm) Cardiovascular Disease Segmentation Conjunctival Microvessel Thermal Camera Melanoma Electrocardiogram (ecg) Renal Cell Carcinoma Pocus Smart Devices Model Fusion Digital Image Analysis Rc-cad Chest Emotion Recognition System Autism Low Pass Filter Healthcare Bone Mass Image Classification Cwt Personalized Diagnosis Texture Affective Computing Nc Protein Imt Respiration Rate Mobile Application Psa Alexnet Oct Segmentation Strength Training Immune System Autism Spectrum Disorder (asd) Computed Tomography (ct) Histopathology Images Functional Features Osteoporosis Security Analysis Data Association Ce-ct Carotid Intima-media Thickness Biomedical Informatics Alzheimer’s Disease Pour Brainamp Heart Rate Variability Protein–protein Interactions Naive Bayes Image Processing Mild Cognitive Impairment N/a Asd Vessel Segmentation Smri Multichannel System Diagnosis Mri Image Medicine / Bicssc Skin Lesions Chest X-ray Cca Decision-making Smart Wearables Osteopenia Number Of Chews Thyroid Diabetic Retinopathy Classification Abide-ii Yolo Sensor-based Control Covid-19 Transfer Learning Neuroimaging Gradient Boosting Disease Detection Chewing Dti Macrophages Dexa Multi-features Optical Detection Dataset Lung Pump Independent Intraclass Correlation Coefficient Lesions Detection Morphology Dendritic Cells Whale Optimization Cervical Cancer Cnn Diabetic Retinopathy Lesions Localization Bladder Monitoring Blood Flow Velocity Quantification Artificial Intelligence Classification Convolutional Neural Network (cnn) Functionality Encoder-decoder Model Semantic Attribute Convolutional Neural Network Bitalino Electrical Characterization Heart Sound Detection Convolutional Neural Networks (cnn)
Online Access:	https://directory.doabooks.org/handle/20.500.12854... https://www.mdpi.com/books/book/8310
Collection:	Directory of Open Access Books - Collection details see MPG.ReNa

Description
Summary:	Sensors used to diagnose, monitor or treat diseases in the medical domain are known as medical sensors. There are several types of medical sensors that can be utilized for various applications, such as temperature probes, force sensors, pressure sensors, oximeters, electrocardiogram sensors that measure the electrical activity of the heart, heart rate sensors, electroencephalogram sensors that measure the electrical activity of the brain, electromyogram sensors that record electrical activity produced by skeletal muscles, and respiration rate sensors that count how many times the chest rises in a minute. The output of these sensors used to be interpreted by humans, which was time consuming and tedious; however, such interpretations became easy with advances in artificial intelligence (AI) techniques and the integration of the sensor outputs into computer-aided diagnostic (CAD) systems. This reprint presents some of the state-of-the-art AI approaches that are used to diagnose different diseases and disorders based on the data collected from different medical sensors. The ultimate goal is to develop comprehensive and automated computer-aided diagnosis by focusing on the different machine learning algorithms that can be used for this purpose as well as novel applications in the medical field.
Item Description:	Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:	1 electronic resource (670 p.)
ISBN:	9783036595320 books978-3-0365-9533-7 9783036595337

Computer Aided Diagnosis Sensors

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