Wireless Mobile Communication and Healthcare: 12th EAI International Conference, MobiHealth 2023, Vila Real, Portugal, November 29-30, 2023 Proceedings

by António Cunha (Editor), Anselmo Paiva (Editor), Sandra Pereira (Editor)

Overview

This book constitutes the refereed post-conference proceedings of the 12th International Conference on Mobile Communication and Healthcare, MobiHealth 2023, held in November 29-30, 2023 in Vila Real, Portugal.

The 35 full papers of MobiHealth 2023 were carefully selected from 111 submissions and present science and technology aspects in the field of wireless communication, mobile computing and healthcare applications.
The conference papers are organized in topical sections on: Medical, communications and networking; Digital imaging and communications in medicine (DICOM). Biomedical, and health informatics; Multimedia e-Health data exchange services. Signal/Data processing and computing for health systems.

Product Details

ISBN-13:	9783031606656
Publisher:	Springer-Verlag New York, LLC
Publication date:	06/27/2024
Series:	Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , #578
Sold by:	Barnes & Noble
Format:	eBook
File size:	81 MB
Note:	This product may take a few minutes to download.

Table of Contents

.- Medical, Communications and Networking.

.- Geometric Perception of the Brain: a Classical Approach using Image Segmentation.

.- Determination of Effective Connectivity of Brain Activity in the Resting Brain.

.- Evanescent Wave Filtering for Ultrasound RF-Data Compression.

.- SpinalTracking: An Application to Help Track Spinal Deformities.

.- Optimising Wheelchair Path Planning.

.- eDEM-CONNECT: An ontology-based chatbot for family caregivers of people with dementia.

.- Digital Imaging and Communications in Medicine (DICOM). Biomedical, and Health Informatics.

.- A Cascade Approach for Automatic Segmentation of Coronary Arteries Calcification in Computed Tomography Images using Deep Learning.

.- Evaluation of Transfer Learning with a U-Net Architectures for Kidney Segmentation.

.- Training U-Net with Proportional Image Division for Retinal Structure Segmentation.

.- Eff-Unet For Automated Trachea Segmentation On CT Images.

.- A Vision Transformer Approach to Fundus Image Classification.

.- Glaucoma Grading Using Fundus Images.

.- Automatic Detection of Pathologies in Medical Images Using Deep Features and Machine Learning.

.- Segmentation in Capsule Endoscopy Images Using TransUNet.

.- Automating the Annotation of Medical Images in Capsule Endoscopy through Convolutional Neural Networks and CBIR.

.- Similarity-Based Explanations for Deep Interpretation of Capsule Endoscopy Images.

.- Deep Learning Applications in Histopathological Images.

.- Tooth Detection and Numbering in Panoramic Radiographs using YOLOv8-Based Approach.

.- Automatic Detection of Polyps Using Deep Learning.

.- Detection of Landmarks in X-Ray Images through Deep Learning.

.- Performance analysis of CNN models in the detection and classification of diabetic retinopathy.

.- Deep Learning Model Evaluation and Insights in Inherited Retinal Disease Detection.

.- Indoor air quality in a residential building – a health issue.

.- Identification and detection in building images of biological growths – prevent a health issue.

.- Informative classification of Capsule Endoscopy videos using Active Learning.

.- Multimedia e-health data exchange services. Signal/Data Processing and Computing For Health Systems.

.- Develop method to efficiently apply image-based facial emotion classification models to video data.

.- DeepSquitoes: A mobile system framework for the surveillance of disease-carrying mosquitoes.

.- BrainGain: a technological approach for increasing consciousness in coma patients.

.- PHPlace: A New Perspective on Managing Pelvic Organ Prolapse Through Mobile Applications.

.- Behavioural Changes using mHealth: An Experimental Case Study.

.- Gym at Home - A Proof-of-Concept.

.- Automatic Food Labels Reading System.

.- Transfer Learning to Detect COVID-19 Coughs with Incremental Addition of Patient Coughs to Healthy People’s Cough Detection Models.

.- EEG monitoring in driving using embedded systems.

.- Complex systems and optimal pandemic control.

.- Automated Classification of Prostate Cancer Severity using Pre-trained Models.