Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Electrical and Computer Engineering (4)
- Other Computer Engineering (3)
- Library and Information Science (2)
- Medicine and Health Sciences (2)
- Social and Behavioral Sciences (2)
-
- Business (1)
- Computer Sciences (1)
- Computer and Systems Architecture (1)
- Data Storage Systems (1)
- Digital Communications and Networking (1)
- Graphics and Human Computer Interfaces (1)
- Health Information Technology (1)
- Health and Medical Administration (1)
- Information Security (1)
- Management Information Systems (1)
- Physical Sciences and Mathematics (1)
- Institution
Articles 1 - 12 of 12
Full-Text Articles in Computer Engineering
Ontolog Summit 2024 Talk Report: Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy
Ontolog Summit 2024 Talk Report: Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy
Publications
Although Artificial Intelligence technology has proven effective in providing healthcare assistance by analyzing health data, it still falls short in supporting decision-making. This deficiency largely stems from the predominance of opaque neural networks, particularly in mental health care AI applications, which raise concerns about their unpredictable and unverifiable nature. This skepticism hinders the transition from information support to decision support. This presentation will explore neurosymbolic approaches that combine neural networks with symbolic control and verification mechanisms. These approaches aim to unlock AI’s full potential by enhancing information analysis and decision-making support for healthcare assistance1.
Iot Health Devices: Exploring Security Risks In The Connected Landscape, Abasi-Amefon Obot Affia, Hilary Finch, Woosub Jung, Issah Abubakari Samori, Lucas Potter, Xavier-Lewis Palmer
Iot Health Devices: Exploring Security Risks In The Connected Landscape, Abasi-Amefon Obot Affia, Hilary Finch, Woosub Jung, Issah Abubakari Samori, Lucas Potter, Xavier-Lewis Palmer
School of Cybersecurity Faculty Publications
The concept of the Internet of Things (IoT) spans decades, and the same can be said for its inclusion in healthcare. The IoT is an attractive target in medicine; it offers considerable potential in expanding care. However, the application of the IoT in healthcare is fraught with an array of challenges, and also, through it, numerous vulnerabilities that translate to wider attack surfaces and deeper degrees of damage possible to both consumers and their confidence within health systems, as a result of patient-specific data being available to access. Further, when IoT health devices (IoTHDs) are developed, a diverse range of …
The Use Of Data Balancing Algorithms To Correct For The Under-Representation Of Female Patients In A Cardiovascular Dataset, Sian Miller
Dissertations
Given that women are under-represented in medical datasets, and that machine learning classification algorithms are known to exhibit bias towards the majority class, the growing application of machine learning in the medical field risks resulting in worse medical outcomes for female patients. The Heart Failure Prediction (HFP) dataset is a historical dataset used for the training of models for the prediction of heart disease. This dataset contains significantly fewer female patients than male patients, and as such it is expected that models trained using this data will inherit a gender bias to favour male patients. This dissertation explores the use …
Acm Web Conference 2023, Usha Lokala, Kaushik Roy, Utkarshani Jaimini, Amit Sheth
Acm Web Conference 2023, Usha Lokala, Kaushik Roy, Utkarshani Jaimini, Amit Sheth
Publications
Improving the performance and explanations of ML algorithms is a priority for adoption by humans in the real world. In critical domains such as healthcare, such technology has significant potential to reduce the burden on humans and considerably reduce manual assessments by providing quality assistance at scale. In today’s data-driven world, artificial intelligence (AI) systems are still experiencing issues with bias, explainability, and human-like reasoning and interpretability. Causal AI is the technique that can reason and make human-like choices making it possible to go beyond narrow Machine learning-based techniques and can be integrated into human decision-making. It also offers intrinsic …
Blockchain-Based Healthcare Portal – A Bibliometric Analysis, Aditi Goyal, Aditya Banerjee, Aniket Mulik, Yashika Chhabaria, Sonali Kothari Tidke Dr, Vijayshri Khedkar
Blockchain-Based Healthcare Portal – A Bibliometric Analysis, Aditi Goyal, Aditya Banerjee, Aniket Mulik, Yashika Chhabaria, Sonali Kothari Tidke Dr, Vijayshri Khedkar
Library Philosophy and Practice (e-journal)
User privacy has been a topmost priority and one such domain where this is neglected is the area of healthcare. Our solution focuses on the idea of using blockchain to provide a platform for healthcare experts and patients, giving patients full control over the data that will be shared. This paper focuses on identifying current research that has been conducted in this area in the form of a bibliometric analysis. A bibliometric study on a research area involves a detailed analysis of citations and papers across a domain of study. The purpose of this study is a statistical analysis of …
Bibliometric Of Feature Selection Using Optimization Techniques In Healthcare Using Scopus And Web Of Science Databases, Rahul Joshi, Harita Gadikta, Saneeka Kharat, Soumi Mandal, Kalyani Kadam, Anupkumar M. Bongale Dr., Siddhant Pandit
Bibliometric Of Feature Selection Using Optimization Techniques In Healthcare Using Scopus And Web Of Science Databases, Rahul Joshi, Harita Gadikta, Saneeka Kharat, Soumi Mandal, Kalyani Kadam, Anupkumar M. Bongale Dr., Siddhant Pandit
Library Philosophy and Practice (e-journal)
Feature selection technique is an important step in the prediction and classification process, primarily in data mining related aspects or related to medical field. Feature selection is immersive with the errand of choosing a subset of applicable features that could be utilized in developing a prototype. Medical datasets are huge in size; hence some effective optimization techniques are required to produce accurate results. Optimization algorithms are a critical function in medical data mining particularly in identifying diseases since it offers excellent effectiveness in minimum computational expense and time. The classification algorithms also produce superior outcomes when an objective function is …
A Bibliometric Survey Of Smart Wearable In The Health Insurance Industry, Apeksha Shah, Swati Ahirrao, Shraddha Phansalkar, Ketan Kotecha
A Bibliometric Survey Of Smart Wearable In The Health Insurance Industry, Apeksha Shah, Swati Ahirrao, Shraddha Phansalkar, Ketan Kotecha
Library Philosophy and Practice (e-journal)
Smart wearables help real-time and remote monitoring of health data for effective diagnostic and preventive health care services. Wearable devices have the ability to track and monitor healthcare vitals such as heart rate, physical activities, BMI (Body Mass Index), blood pressure, and keeps an individual notified about the health status. Artificial Intelligence-enabled wearables show an ability to transform the health insurance sector. This would not only enable self-management of individual health but also help them focus from treatments to the preventions of health hazards. With this customer-centric approach to health care, it will enable the insurance companies to track the …
Towards Better Remote Healthcare Experiences: An Mhealth Video Conferencing System For Improving Healthcare Outcomes, El Sayed Mahmoud, Edward Sykes, Blake Eram, Sandy Schwenger, Jimmy Poulin, Mark Cheers
Towards Better Remote Healthcare Experiences: An Mhealth Video Conferencing System For Improving Healthcare Outcomes, El Sayed Mahmoud, Edward Sykes, Blake Eram, Sandy Schwenger, Jimmy Poulin, Mark Cheers
Publications and Scholarship
This work investigated how to combine mobile cloud computing, video conferencing and user interface design principles to promote the effectiveness and the ease of using online healthcare appointment platforms. The Jitsi Meet video conference technology was selected from amongst 27 competing systems based on efficiency and security criteria. This platform was used as the foundation on which we designed, developed and evaluated of our video conferencing system specially designed for improving doctor-patient interaction and experiences. Nine doctor- patient functions were developed in order to facilitate efficient and effective online healthcare appointments, such as providing the doctor with the ability to …
Personalized Health Knowledge Graph, Amelie Gyrard, Manas Gaur, Saeedeh Shekarpour, Krishnaprasad Thirunarayan, Amit Sheth
Personalized Health Knowledge Graph, Amelie Gyrard, Manas Gaur, Saeedeh Shekarpour, Krishnaprasad Thirunarayan, Amit Sheth
Publications
Our current health applications do not adequately take into account contextual and personalized knowledge about patients. In order to design “Personalized Coach for Healthcare” applications to manage chronic diseases, there is a need to create a Personalized Healthcare Knowledge Graph (PHKG) that takes into consideration a patient’s health condition (personalized knowledge) and enriches that with contextualized knowledge from environmental sensors and Web of Data (e.g., symptoms and treatments for diseases). To develop PHKG, aggregating knowledge from various heterogeneous sources such as the Internet of Things (IoT) devices, clinical notes, and Electronic Medical Records (EMRs) is necessary. In this paper, we …
Multi-Task Learning Framework For Mining Crowd Intelligence Towards Clinical Treatment, Shweta Yadav, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya, Amit Sheth
Multi-Task Learning Framework For Mining Crowd Intelligence Towards Clinical Treatment, Shweta Yadav, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya, Amit Sheth
Publications
In recent past, social media has emerged as an active platform in the context of healthcare and medicine. In this paper, we present a study where medical user’s opinions on health-related issues are analyzed to capture the medical sentiment at a blog level. The medical sentiments can be studied in various facets such as medical condition, treatment, and medication that characterize the overall health status of the user. Considering these facets, we treat analysis of this information as a multi-task classification problem. In this paper, we adopt a novel adversarial learning approach for our multi-task learning framework to learn the …
Ransomware In Healthcare Facilities: The Future Is Now, Nikki Spence, David P. Paul Iii, Alberto Coustasse
Ransomware In Healthcare Facilities: The Future Is Now, Nikki Spence, David P. Paul Iii, Alberto Coustasse
Management Faculty Research
Cybercriminals have begun to target the healthcare industry with a type of malware called ransomware, malware that encrypts an infected device and any attached devices or network drives. After encryption, cybercriminals demand a sum of money, also known as a “ransom,” to release the devices from encryption. Without adequate disaster recovery and backup plans, many businesses are forced to pay the ransom. The purpose of this study was to determine the extent of recent ransomware infections in healthcare settings, the risk liabilities and cost associated with such infections, and to determine possible risk mitigation tactics. Financial costs associated with business …
A Security Analysis Of Cyber-Physical Systems Architecture For Healthcare, Darren Seifert, Hassan Reza
A Security Analysis Of Cyber-Physical Systems Architecture For Healthcare, Darren Seifert, Hassan Reza
Computer Science Faculty Publications
This paper surveys the available system architectures for cyber-physical systems. Several candidate architectures are examined using a series of essential qualities for cyber-physical systems for healthcare. Next, diagrams detailing the expected functionality of infusion pumps in two of the architectures are analyzed. The STRIDE Threat Model is then used to decompose each to determine possible security issues and how they can be addressed. Finally, a comparison of the major security issues in each architecture is presented to help determine which is most adaptable to meet the security needs of cyber-physical systems in healthcare.