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King Saud University, Saudi Arabia

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16 Papers

The Impact of Class Weight Optimization on Improving Machine Learning Outcomes in Identifying COVID-19 Specific ECG Patterns

Topics: Pattern Recognition and Machine Learning; Application of Health Informatics in Clinical Cases; Data Mining and Data Analysis

Authors: Sara Khan ¹ , Walaa Ismail ² , Shada Alsalamah ³ , Ebtesam Mohamed ⁴ and Hessah A. Alsalamah ^{5

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Affiliations: ¹ Department of Information Systems and Technology Management, George Washington University, Washington, DC, U.S.A. , ² Management Information Systems Department, College of Business, Al Yamamah University, Riyadh, K.S.A. , ³ Information Systems Department, King Saud University, Riyadh, K.S.A. , ⁴ Faculty of Computer Science, Minia University, Minia, Egypt , ⁵ Computer Engineering Department, College of Engineering and Architecture, Al Yamamah University, Riyadh, K.S.A.

Digital Object Identifier: 10.5220/0012413100003657

Proceedings of HEALTHINF 2024, ISBN: 978-989-758-688-0

Quick Abstract

The Covid-19 pandemic has resulted in 550 million cases and 6.3 million fatalities, with the virus severely affecting the lungs and cardiovascular system. A study utilizes a VGG16 model adapted for a 12-Lead ECG Image database to assess the disease’s impact on cardiovascular health. The research addresses the challenge of data imbalance by experimenting with different training approaches: using balanced datasets, imbalanced datasets, and class weight adjustments for imbalanced datasets. These models are designed for a three-class multiclass classification of ECG images: Abnormal, Covid-19, and Normal categories. Performance evaluations, including accuracy scores, confusion matrices, and classification reports, show promising results. The model trained on a balanced dataset achieved a 90% accuracy rate. When trained on an imbalanced dataset, the accuracy dropped to 82%. However, with class weight adjustments, the accuracy rebounded to 87%. The study proves that the adapted VGG16 model can effectively handle both balanced and imbalanced datasets. Further testing and enhancements can be carried out using additional datasets, making it a valuable tool for understanding the cardiovascular implications of Covid-19.

Achieving Patient-Centered Fine-Grained Access Control in Hospital Information Systems - Using Business Process Management Systems

Topics: Decision Support Systems; Medical and Nursing Informatics; Confidentiality and Data Security; Healthcare Management Systems; Electronic Health Records and Standards

Authors: Nahid AlThqafi , Hessah AlSalamah and Ahmad Daraiseh

Affiliation: King Saud University, Saudi Arabia

Digital Object Identifier: 10.5220/0005630200390048

Proceedings of HEALTHINF 2016/BIOSTEC, ISBN: 978-989-758-170-0

Quick Abstract

Access Control to patients’ medical information in Hospital Information Systems (HIS) is a challenge in modern Patient-Centered (PC) healthcare. Fine–Grained Access Control (FGAC) in particular has been identified as one of the security requirements in these systems. In FGAC, only parts of medical information that are relevant and required by healthcare providers are accessed at the point of care. This cannot be achieved without a holistic view of a medical condition through a Patient-Centered Fine-Grained Access Control (PCFGAC), in which patient-centricity is considered. This research proposes using Business Process Management (BPM) to achieve PCFGAC in order to provide a real-time access control based on a “need-to-know” principle. Through a prototype that uses BPM, security requirements of PCFGAC were met. These include: authority control, informed decision support, fine-grained access control, and dynamic policies support. Thus, a contribution to the knowledge and practice has been introduced.

Related Ontology Subjects/Areas/Topics (16)

Artificial Intelligence	Data Engineering	Health Information Systems
Biomedical Engineering	Decision Support Systems	Healthcare Management Systems
Business Analytics	Decision Support Systems, Remote Data Analysis	Knowledge-Based Systems
Cardiovascular Technologies	Electronic Health Records and Standards	Medical and Nursing Informatics
Computing and Telecommunications in Cardiology	Health Engineering and Technology Applications	Symbolic Systems
Confidentiality and Data Security

Direct Measurement of TV Viewing Time and Physical Activity in Children - A Pilot Study

Topic: Health and Fitness

Author: Mohammad Ali Alahmadi

Affiliation: College of Sport Science and Physical Activity and King Saud University, Saudi Arabia

Digital Object Identifier: 10.5220/0005611401450149

Proceedings of icSPORTS 2015, ISBN: 978-989-758-159-5

Quick Abstract

The main aim of this study was to design an electronic device to objectively monitor Television (TV) viewing time in children. The second aim was to examine the relationship between TV viewing time and physical activate activity (PA). Seven children (mean ± SD, age, 10.7 ± 2.1 years; body mass, 35.7 ± 17 kg; height, 137.4 ± 12.3 cm) participated in this study. TV viewing time was directly measured for two consecutive days by a novel wireless electronic device, using Radio-frequency identification (RFID) technology which was connected to a main electronic board that is designed to measure TV viewing time in minutes. PA was also measured, concurrently with TV viewing time measurement, by pedometers (Yamax Digiwalker SW-700) for 3 consecutive days. The preliminary results show that the average TV viewing time of children was 248 ± 188 min/day. Participants also recorded a mean of 10731 ± 3399 steps per day. The average TV viewing time was positively associated with the average steps in children, but not statistically significant (r= 0.74, p= 0.056). It is concluded that the current study produces a novel wireless electronic tool that can monitor TV viewing time in children. It is also concluded that high association between TV viewing time and PA was observed among children, although not statistically significant.

Related Ontology Subjects/Areas/Topics (3)

Health and Fitness

Health, Sports Performance and Support Technology

Sport Science Research and Technology

Describing Functionalities and Reactions of Cars and Managing Their Feature Interactions

Topics: Vehicle Control Applications; Software Agents for Intelligent Control Systems; Intelligent Transportation Technologies and Systems

Authors: Ahmed Khoumsi ¹ and Zohair Chentouf ²

Affiliations: ¹ University of Sherbrooke, Canada , ² King Saud University, Saudi Arabia

Digital Object Identifier: 10.5220/0005010501470155

Proceedings of ICINCO 2014, ISBN: 978-989-758-039-0

Quick Abstract

We develop an Automotive Reaction System (ARS) framework to support cars by capabilities to react to various situations. With ARS, the states and actions of a car are designed as objects of a high level objectoriented language, called ARS-language. ARS permits also to design the reactions of a car to various situations by an ARS-specification consisting of rules “condition->action”. The ARS-objects and ARSspecification are implemented in a car to provide her with capabilities to function and react online. ARS permits also to model certain actions of a car at a high abstraction level by an ARS-model consisting of rules “condition->operation”. With ARS, we are confronted to conflicts (or feature interactions) which denote situations where an ARS-specification implies simultaneous executions of incompatible actions. We propose an approach to detect and resolve feature interactions.

Related Ontology Subjects/Areas/Topics (6)

Informatics in Control, Automation and Robotics		Intelligent Transportation Technologies and Systems		Software Agents for Intelligent Control Systems
Intelligent Control Systems and Optimization		Robotics and Automation		Vehicle Control Applications

Finding the Frequent Pattern in a Database - A Study on the Apriori Algorithm

Topics: Web Mining; Foundations of Knowledge Discovery in Databases; Data Analytics; Data Mining in Electronic Commerce

Authors: Najlaa AlHuwaishel ¹ , Maram AlAlwan ² and Ghada Badr ¹

Affiliations: ¹ King Saud University, Saudi Arabia , ² King Abdulaziz City for Science and Technology, Saudi Arabia

Digital Object Identifier: 10.5220/0005147703880396

Proceedings of KDIR 2014/IC3K, ISBN: 978-989-758-048-2

Quick Abstract

This paper is a study on the frequent pattern mining using the Apriori algorithm. We will present the concept of data mining in a high level and explain how the frequent pattern is mined. We will talk about the Apriori algorithm and the problem with this algorithm followed by exploration of some algorithms that considered as an update on the Apriori algorithm in order to enhance the efficiency problem that we explained. We will also compare the selected algorithms taking under consideration: 1.Number of database scan. 2.Number of generated candidate lists. 3.Memory usage.

Related Ontology Subjects/Areas/Topics (11)

Artificial Intelligence	Data Mining in Electronic Commerce	Soft Computing
Business Analytics	Foundations of Knowledge Discovery in Databases	Symbolic Systems
Data Analytics	Knowledge Discovery and Information Retrieval	Web Mining
Data Engineering	Knowledge-Based Systems

Q-Routing in Cognitive Packet Network Routing Protocol for MANETs

Topics: Computational Neuroscience; Learning Paradigms and Algorithms; Adaptive Architectures and Mechanisms

Authors: Amal Alharbi , Abdullah Al-Dhalaan and Miznah Al-Rodhaan

Affiliation: King Saud University, Saudi Arabia

Digital Object Identifier: 10.5220/0005082902340243

Proceedings of NCTA 2014/IJCCI, ISBN: 978-989-758-054-3

Quick Abstract

Mobile Ad hoc Networks (MANET) are self-organized networks which are characterized by dynamic topologies in time and space. This creates an instable environment, where classical routing approaches cannot achieve high performance. Thus, adaptive routing is necessary to handle the random changing network topology. This research uses Reinforcement Learning approach with Q-Routing to introduce our MANET routing algorithm: Stability-Aware Cognitive Packet Network (CPN). This new algorithm extends the work on CPN to adapt it to the MANET environment with focus on path stability metric. CPN is a distributed adaptive routing protocol that uses three types of packets: Smart Packets for route discovery, Data Packets for carrying data payload, and Acknowledgments to bring back feedback information for the Reinforcement Learning reward function. The research defines a reward function as a combination of high stability and low delay path criteria to discover long-lived routes without disrupting the overall delay. The algorithm uses Acknowledgment-based Q-routing to make routing decisions which adapt on line to network changes allowing nodes to learn efficient routing policies.

Related Ontology Subjects/Areas/Topics (19)

Adaptive Architectures and Mechanisms	Human-Computer Interaction	Pattern Recognition
Artificial Intelligence	Learning Paradigms and Algorithms	Physiological Computing Systems
Biomedical Engineering	Methodologies and Methods	Sensor Networks
Biomedical Signal Processing	Neural Networks	Signal Processing
Computational Intelligence	Neurocomputing	Soft Computing
Computational Neuroscience	Neurotechnology, Electronics and Informatics	Theory and Methods
Health Engineering and Technology Applications

Using a Hopfield Iterative Neural Network to Explain Diffusion in the Brain’s Extracellular Space Structure

Topics: Industrial, Financial and Medical Applications; Computational Neuroscience

Author: Abir Alharbi

Affiliation: King Saud University, Saudi Arabia

Digital Object Identifier: 10.5220/0005029300970104

Proceedings of NCTA 2014/IJCCI, ISBN: 978-989-758-054-3

Quick Abstract

Many therapies for drug delivery to the brain are based on diffusion, and diffusion in this extracellular space is based on micro-techniques that can be modelled with classical differential equations such as the point source diffusion equation. In this paper an energy function is constructed using a finite-difference approximation to the governing diffusion equation and then minimized by a Hopfield neural network. The synergy of Hopfield neural networks with finite difference approximation is promising. The neural network approach is capable of giving insight to the complex brain activity better than any other classical numerical method and the parallelism nature of the Hopfield neural networks approach is easier to implement on fast parallel computers and this will make them faster than the traditional methods for modelling this complex problem. Moreover, the effect of the involved parameters on the diffusion distribution and drug delivery in the ECS is investigated.

Related Ontology Subjects/Areas/Topics (21)

Artificial Intelligence	Fuzzy Systems	Neurotechnology, Electronics and Informatics
Biomedical Engineering	Health Engineering and Technology Applications	Pattern Recognition
Biomedical Signal Processing	Human-Computer Interaction	Physiological Computing Systems
Computational Intelligence	Industrial, Financial and Medical Applications	Sensor Networks
Computational Neuroscience	Methodologies and Methods	Signal Processing
Computer-Supported Education	Neural Networks	Soft Computing
Domain Applications and Case Studies	Neurocomputing	Theory and Methods

Electronic Monitor for Monitoring TV Viewing Time - Description and Significance

Topic: Applied Physiology and Exercise

Author: Mohammad Ali Alahmadi

Affiliation: King Saud University, Saudi Arabia

Digital Object Identifier: 10.5220/0004636600910094

Proceedings of icSPORTS 2013, ISBN: 978-989-8565-79-2

Quick Abstract

Sedentary behaviour is related to adverse cardiometabolic risk profiles and premature mortality. Television (TV) viewing time is the most predominant sedentary behaviour. There are also adverse associations between TV viewing time and a number of cardiovascular risk factors such as the metabolic syndrome, obesity, and abnormal glucose metabolism. Few measurement tools, such as direct observation and videotaping, have been utilized to objectively monitor TV watching. Unfortunately, these measurements have shortcomings as they invade the personal privacy and are impractical in large-scale research studies. Therefore, there is a need for alternative objective measures. Therefore, the main aim of this paper is to design an electronic device to objectively monitor TV viewing. This device uses Radio-frequency identification (RFID) technology that transfers data using tracking tag that is attached to a child's wrist like a watch. This data will be collected by the RFID Reader which is connected to a main electronic board that is designed to measure TV viewing time in minutes. The current research is expected to produce a novel wireless electronic tool that can monitor TV viewing without intrusion to the person privacy and can be widely used as an objective method of assessing TV viewing time.

Related Ontology Subjects/Areas/Topics (3)

Applied Physiology and Exercise

Health, Sports Performance and Support Technology

Sport Science Research and Technology

ERP Implementation Success through Effective Management of Roles and Responsibilities among StakeholdersA Holistic Framework Adopted from Two Case Studies

Authors: Waiel Al-Rashid ¹ , Mustafa Alshawi ¹ and Majed Al-Mashari ²

Affiliations: ¹ University of Salford, United Kingdom , ² King Saud University, Saudi Arabia

Digital Object Identifier: 10.5220/0004775001570165

Proceedings of BMSD 2013, ISBN: 978-989-8565-56-3

Quick Abstract

This paper describes a case study of Enterprise Resource Planning (ERP) implementation in a public-private partnership organisation. The primary focus of the study is to explore, from a holistic view, how Return On Investment (ROI) can be achieved through effective management of roles and responsibilities in an ERP implementation context. The paper starts with an introduction, which includes highlights from the literature indicating the significance of roles and responsibilities management among various ERP stakeholders. The introduction is followed by a brief description of the research methodology used, and then followed by a description of the chosen case study for this paper. The case is then analysed with more focus on how roles and responsibilities among ERP stakeholders interrelate with the implementation outcomes. A separate section is dedicated to extracting appropriate lessons that improve ROI from ERP investment. The findings from the case are assessed through the literature and a published case study that is addressed to ERP stakeholders. The result of discussing the case findings will be presented in a new version of the management framework for the stakeholder’s roles and responsibilities in the context of ERP.

Stability-aware Cognitive Packet Network Routing Protocol for MANET

Authors: A. Alharbi ¹ , A. Aldhalaan ² and M. Alrodhaan ²

Affiliations: ¹ Princess Nora University, Saudi Arabia , ² King Saud University, Saudi Arabia

Proceedings of Doctoral Consortium 2013/IJCCI, ISBN: Not Available

Quick Abstract

The research introduces a new Stability-Aware Cognitive Packet Routing Algorithm to provide Quality Of Service (QoS) to packets in Mobile Ad hoc networks (MANET) through long-lived, short delay routes. It extends the work on Ad-hoc Cognitive Packet Network (AHCPN) to adapt it to the MANET environment. It uses Smart Packets (SP) to find and maintain paths that provide specific QoS goals to each packet. Smart Packets move through the network collecting information to be able to make decisions by “learning” from the experience of previous SP’s of the same QoS goals. The routing algorithm constructs Random Neural Networks (RNN) at each node with a neuron for each output link in order to make a routing decision. The algorithm uses Computational Intelligence to make routing decisions with high probability to stable nodes in th e network. A feedback system is subsequently used based on Reinforcement Learning through Acknowledgments to update network information in RNN’s. The proposed algorithm defines a combined routing goal function that considers both the associativity of the node for stability and path delay to result in short, long-lived paths. The degree of associativity of a node is determined via low frequency periodic beacons to identify itself to its neighbors.