Electronics, Biomedical Engineering, and Health Informatics (3rd edition)

<ul><li>Preface</li><li>Chapter 1: 3D Technologies in Biomedical Application</li><li>3D Printing of PolyLactic Acid (PLA) Scaffold Combined with Injectable Bone Substitute (IBS) for Tuberculosis Drug Delivery</li><li>3D Printing of Heart Model as Medical Education Tools</li><li>Chapter 2: Modelling and Experimental Research in Biomedical Engineering</li><li>Forecasting Approach to Investigate Dynamic Growth of Organoid within 3D Matrix for Distinct Perspective</li><li>Evaluation of the Malalignment Varus - Valgus in Total Knee Arthroplasty Designed for Deep Knee Flexion Using Knee Kinematic Motion Simulator</li><li>Chapter 3: Medical Devices and Equipment</li><li>Performance Comparison for Hearth Rate Signal Detection for Different Location in Fingertip and Wrist Using Sensor MAX30102</li><li>The Evaluation of Complementary Metal-Oxide Semiconductor (CMOS) in Smartphone to Test X-Ray Tube Radiation Leakage</li><li>Chapter 4: Biomedical Image and Signal Processing</li><li>An Innovation of Black Tea as a Substitute for the Use of Positive Contrast Media in CT Urography in Hydronephrosis Cases: Case Study</li><li>Kalman Filter for Artifact Reduction in MRI Imaging: A Literature Review</li><li>Image Quality Improvement of SENSE Parallel Imaging MRI Post-Acquisition Using Denoising Non-Local Mean Filter Technique</li><li>Determination Image Quality on Thorax COVID-19 and Tuberculosis Using Optical Density Image Analysis</li><li>Falling Estimation Based on PoseNet Using Camera with Difference Absolute Standard Deviation Value and Average Amplitude Change on Key-Joint</li><li>The Influence of X-Ray Tube Current-Time Variations Toward Signal to Noise Ratio (SNR) in Digital Radiography: A Phantom Study</li><li>Literature Review: Impact of Noise on Cognitive Performance Using Electroencephalography</li><li>Chapter 5: Health Informatics</li><li>A Novel Epitope Dataset: Performance of the MCL-Based Algorithms to Generate Dataset for Graph Learning Model</li><li>A Novel Ensemble of Support Vector Machines for Improving Medical Data Classification</li></ul>