UID:
almahu_9949747858102882
Format:
1 online resource (564 pages)
Edition:
1st ed.
ISBN:
9783031590917
Series Statement:
Communications in Computer and Information Science Series ; v.2084
Note:
Intro -- Foreword -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Clinical Decision Support and Medical AI 1 -- Using Machine Learning Methods to Predict the Lactate Trend of Sepsis Patients in the ICU -- 1 Introduction -- 2 Methods -- 2.1 Data Sources -- 2.2 Study Design -- 2.3 Definition of Outcomes -- 2.4 Variable Selection -- 2.5 Proposed Machine Learning Framework -- 2.6 Selected Classifiers for Proposed Framework -- 2.7 Evaluation Criteria -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Computed Tomography Artefact Detection Using Deep Learning-Towards Automated Quality Assurance -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Assessment of Parkinson's Disease Severity Using Gait Data: A Deep Learning-Based Multimodal Approach -- 1 Introduction -- 1.1 Parkinson's Disease (PD) -- 1.2 Gait Analysis -- 1.3 Multimodal in Decision Support -- 1.4 Goal of the Study -- 2 Related Work -- 2.1 PD Severity Estimation -- 2.2 PD Diagnosis -- 2.3 Multimodal Data Analysis Using Perceiver -- 3 Materials and Methods -- 3.1 Dataset Description -- 3.2 Pre-processing and Feature Extraction -- 3.3 Perceiver Architecture -- 3.4 Proposed Framework -- 3.5 Experimental Setup -- 3.6 Evaluation -- 3.7 Hyperparameter Optimization Using GA -- 4 Results -- 4.1 Empirical Results -- 5 Discussion -- 6 Conclusion -- References -- Digital Care Pathways II -- Dual-Perspective Modeling of Patient Pathways: A Case Study on Kidney Cancer -- 1 Introduction -- 2 Methods -- 2.1 Recruitment -- 2.2 Mapping and Modeling of Patient Pathways with Healthcare Personnel -- 2.3 Mapping and Modeling of Patient Journeys -- 2.4 Feasibility Evaluation -- 3 Results -- 3.1 Modeling of the Kidney Cancer Pathway (Healthcare Perspective).
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3.2 Modeling the Kidney Cancer Patient Journey (The Patient Perspective) -- 3.3 The Dual Perspective -- 3.4 Feasibility Evaluation -- 4 Discussion -- 5 Conclusion -- References -- Digital Services in the Welfare, Social and Health Sector Organizations of the South Ostrobothnia Region -- 1 Introduction -- 2 Methods -- 2.1 Study Design -- 2.2 Sample -- 2.3 Data Collection and Ethical Considerations -- 2.4 Quantitative Cross-Sectional Survey -- 2.5 Analyses -- 3 Results -- 3.1 Current State and the Role of Digital Services -- 3.2 Perceived Barriers for Development of Digital Services -- 3.3 Development Plans -- 3.4 Support Needs -- 4 Discussion -- References -- A Persuasive mHealth Application for Postoperative Cardiac Procedures: Prototype Design and Usability Study -- 1 Introduction -- 2 Background -- 2.1 Cardiovascular Diseases -- 2.2 mHealth Applications for Cardiovascular Procedures -- 2.3 Persuasive Technology and Persuasive Systems Design -- 3 Methods -- 3.1 Study Design -- 3.2 User Interface Design -- 3.3 Population and Sample -- 3.4 Data Collection and Organization -- 3.5 Data Collection Instruments -- 3.6 Statistical Procedures -- 3.7 Ethical Considerations -- 3.8 Data Security -- 4 Results -- 4.1 Application Prototype -- 4.2 SUS Score -- 4.3 Non-mandatory Open-Ended Questions -- 5 Discussion -- 6 Conclusion -- References -- Effectiveness of Robot-Assisted Lower Limb Rehabilitation on Balance in People with Stroke: A Systematic Review, Meta-analysis, and Meta-regression -- 1 Introduction -- 2 Methods -- 2.1 Data Sources and Searches -- 2.2 Study Selection -- 2.3 Data Extraction and Quality Assessment -- 2.4 Data Synthesis and Analysis -- 3 Results -- 3.1 Study Selection -- 3.2 Study Characteristics -- 3.3 Methodological Quality -- 3.4 Effectiveness of Robot-Assisted Lower-Limb Rehabilitation on Balance -- 3.5 Meta-regression.
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3.6 Adverse Events -- 4 Discussion -- 4.1 Study Limitations -- 4.2 Conclusions -- References -- Virtual Reality in Rehabilitation of Executive Functions in Children (VREALFUN) - Study Protocols for Randomized Control Trials -- 1 Introduction -- 2 Subjects and Methods -- 2.1 Participants -- 2.2 Procedure -- 2.3 Intervention -- 2.4 Research Ethical Considerations -- 3 Results -- 4 Discussion -- References -- Novel Sensors and Bioinformatics -- A Distributed Framework for Remote Multimodal Biosignal Acquisition and Analysis -- 1 Introduction -- 2 Related Work -- 3 Key Elements in Physiological Signal Devices -- 4 Key Challenges of rPPG Acquisition Systems -- 5 Proposed Architecture for rPPG and rBSG Acquisition -- 5.1 Overview of the Proposed Architecture -- 5.2 Interoperability -- 5.3 Sensing and On-Device Computing -- 5.4 Aggregation, Storage, and Standardization -- 5.5 Data Analysis and AI Computation -- 5.6 Interactive User Interface -- 6 Evaluation of the Camera-Based rPPG Component -- 6.1 Experimental Setup and Configurations -- 6.2 Benchmark Datasets, Protocol and Metrics -- 6.3 Speed Performance -- 6.4 Accuracy Performance in Vital Signs Measurement -- 7 Conclusion -- References -- Passively Reconfigurable Antenna Using Gravitational Method -- 1 Introduction -- 2 Antenna Design -- 2.1 Antenna Structure -- 2.2 Directors -- 3 Results and Discussions -- 3.1 Without Directors -- 3.2 Effect of Directors -- 4 Conclusions -- References -- A Skewness-Based Harmonic Filter for Harmonic Attenuation of Wearable Functional Near-Infrared Spectroscopy Signals -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Collection -- 2.2 Wearable Device -- 2.3 HA Attenuation Algorithm -- 3 Results -- 4 Discussions and Conclusions -- References -- Wearable Motion Sensors in the Detection of ADHD: A Critical Review -- 1 Introduction.
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1.1 What is ADHD and How is It Currently Diagnosed? -- 1.2 Movement Sensors in ADHD Assessment -- 1.3 The Present Study -- 2 Methods -- 2.1 Study Selection -- 2.2 Study Participants -- 2.3 Sensor Data Collection -- 2.4 Experimental Designs -- 2.5 Analysis Methods -- 3 Results -- 4 Discussion -- 4.1 Critical Analysis of the Research Quality in Sensor-Based ADHD Studies -- 4.2 Evaluation of the Clinical Utility of the Sensor-Based Diagnostics -- 4.3 Conclusions -- References -- Influence of Arterial Vessel Diameter and Blood Viscosity on PTT in Pulsatile Flow Model -- 1 Introduction -- 1.1 Mechanical Properties of Blood Vessels, Flow, and Pressure -- 1.2 Mathematical Models to Estimate BP Based on PTT -- 2 Methodology -- 2.1 Pulsatile Flow Simulation -- 2.2 Data Acquisition -- 2.3 Statistical Analysis -- 3 Results -- 3.1 System Stability Testing -- 3.2 Influence of Liquid Viscosity and Tube Dimensions on PTT Levels -- 3.3 Regression Model Based on Moens-Korteweg Equation -- 4 Discussion -- 5 Conclusion -- References -- Clinical Decision Support and Medical AI 2 -- A Hybrid Images Deep Trained Feature Extraction and Ensemble Learning Models for Classification of Multi Disease in Fundus Images -- 1 Introduction -- 2 Related Work -- 2.1 Ensemble Learning-Based Identification of Eye Diseases -- 2.2 Deep Learning-Based Identification of Eye Diseases -- 3 Hybrid Images Deep-Trained Feature Extraction and Ensemble Learning Algorithm for Categorizing Multiple Diseases in Fundus Images -- 3.1 Data Characterization and Preparation -- 3.2 Feature Selection -- 3.3 Classification -- 3.4 Deep Learning Models for Classification -- 4 Result and Discussion -- 5 Conclusion -- References -- Drug Recommendation System for Healthcare Professionals' Decision-Making Using Opinion Mining and Machine Learning -- 1 Introduction -- 2 Methodology -- 2.1 System Architecture.
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2.2 Development Methodology -- 2.3 Overall System Flowchart -- 2.4 Sentiment Analysis -- 2.5 Recommendation Algorithm -- 2.6 Description of Data Source -- 3 Results and Analysis -- 3.1 Sentiment Analysis Model -- 3.2 Content-Based Filtering Model -- 3.3 Collaborative Filtering Model -- 4 Discussion and Conclusion -- References -- Enhancing Arrhythmia Diagnosis with Data-Driven Methods: A 12-Lead ECG-Based Explainable AI Model -- 1 Introduction -- 2 Material and Methods -- 2.1 Dataset Description -- 2.2 HRV Features Extraction -- 2.3 Deep Learning Algorithms -- 2.4 Training, Testing and Performance Metrics -- 2.5 Explainability AI Techniques -- 3 Results -- 3.1 Deep Learning Classification with ECG Raw Signal -- 3.2 Hybrid Approach: Optimal Classifier with ECG Raw Signal and HRV Features -- 3.3 Explainability Analysis of the Optimal Model -- 4 Discussion -- 5 Conclusions -- References -- Real-Time Gait Anomaly Detection Using 1D-CNN and LSTM -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Proposed Neural Networks -- 2.3 Anomaly Detection -- 3 Baseline and Evaluation -- 3.1 Real-time tsSVM Anomaly Detection Algorithm -- 3.2 Evaluation Metrics -- 3.3 Score and Alarm -- 4 Experimental Setup -- 5 Experimental Results and Discussion -- 5.1 Optimization of 1D-CNN-AD and LSTM-AD Algorithms Hyperparameters -- 6 Conclusion -- References -- Research for JYU: An AI-Driven, Fully Remote Mobile Application for Functional Exercise Testing -- 1 Introduction -- 2 Methods -- 2.1 Approach -- 2.2 Technical Details -- 2.3 Use Case - Functional Testing of Patients After Knee Surgery -- 3 Results and Interpretation -- 4 Discussion and Future Perspectives -- References -- Exploring and Extending Human-Centered Design to Develop AI-Enabled Wellbeing Technology in Healthcare -- 1 Introduction -- 2 Methods of HCD in Developing AI-Enabled Technical Solutions.
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2.1 Human-Centered Design (HCD) and Service Design.
Additional Edition:
Print version: Särestöniemi, Mariella Digital Health and Wireless Solutions Cham : Springer,c2024 ISBN 9783031590900
Language:
English
Keywords:
Electronic books.