HICSS 2023 : Hawaii International Conference on System Science: ITAIHE: Minitrack on IT Architectures and Implementations in Healthcare Environments

We invite papers that promote IT architectures and implementations in healthcare, which range from frameworks of and infrastructure for scalable and clustered software architectures and pervasive healthcare settings and implementations of architectural solutions for instances of Internet of Things in medicine and healthcare deliveries, to translational informatics and biomedical semantics. Papers which focus on the latest rise of serverless computing and intelligent computational edge, and their trade-offs with cloud architectures in healthcare software applications are also welcome. They may address the impact of advances of various technologies, including wearable healthcare robotics, body area networks and Internet of Medical Things (IoMT) on software implementations suitable for healthcare delivery. We would also like to receive papers across disciplines such as personalized and precision medicine, human performance engineering, modeling patient behavioral change, and the development of effective healthcare Apps, which exploit software architectures and their styles. They may focus on human performance improvement, assessment, technologies, and the way we build healthcare systems today.

Specific topics of interest may include:

1. Integrated Solutions in Healthcare:
• Architectures and implementations of personalised and public healthcare software solutions, Software tools for empowering and educating patients, Learning from existing health information repositories; Personalized decision support systems for preventive healthcare.
• Software tools and services in integrated healthcare: Architectures for and applications of healthcare services; Software technologies and application architectures in public health protection, preventive healthcare, and personalized health services.
• Computational Intelligence in Healthcare: software architectures for data sharing, semantic reasoning for building intelligence, data architectures for supporting learning algorithms in healthcare and medicine, architectures for creating predictions and viable statistical inference with applications ranging from medical images, diagnostics and drug discoveries to management of healthcare delivery in pandemics.
• Architectures/frameworks for interoperable healthcare software; Standards, medical vocabularies/ontologies for manipulating semantics in heterogeneous health systems.
• Communicating health-related data: exchange and integration of clinical data, documents and workflows; Dissemination of health related data to healthcare professionals and caregivers; Telemedicine, e-prescribing and medication management.

2. Emerging Healthcare Software Platforms and Implementations in/of:
• Internet of Medical Things (IoMT): Feasibility/security of healthcare delivery with IoMT; Implementations of IoMT in clinical practice, Smart medications with ingestible sensors; IoMT and Cyborgs, Human-machine augmentation in medicine: Human aspects and perspectives of IoMT; Computational materials in IoMT: Applications of IoMT: from smart delivery of healthcare in communities to instant reaction to incidents with interconnected ambulance systems.
• Translational biomedicine: Bridging the gap between biomedical research and clinical practice; Computational and probabilistic models and algorithms for drug repurposing, repositioning and ranking; Computational algorithms for predicting drug-disease association, Data driven predictions of drug behavior; Ontologies for genetics and molecular biology;
• Personalized medicine and predictive analytics with machine learning algorithms: Creating targeted therapies, tailored medical interventions and selection of medicines; Software models for predicting the development of diseases, disease prognosis and their prevention; Predictive modeling and facilitating workflows in healthcare delivery; Simulating hospital configurations and workflows.
• Applications of streamlined and user generated data: healthcare management supported by sentiments analysis available in public and user generated data; Augmented reality for exchange of experiences and healthcare information; Application architectures for implementing collaborative and virtual healthcare environments.

3. Relevant Architectures for Apps in Healthcare
• Software architectures for accommodating Apps in pandemics: feasibility of integrating data gathering mechanisms with algorithms for predictive inference; Location specific Apps and sharing of data and results of computations, such as track-and-trace, Apps with privacy enhancing computations in pandemics, versus publically shared data with an ad-hoc diagnostics.
• Computing at the Edge: Instant access to and manipulation of healthcare data; The role of Apps in the trade-off between cloud architectures and edge/fog computing; Software architectural solutions for healthcare Apps which accommodate Statistics and Learning / Predictive technologies.
• Architectures for Integration: Placing Devices / Apps in existing healthcare systems, and environments, Adding Apps to healthcare software applications dependent on algorithmic computations as prevalent in AI and machine learning.
• Software architectures for accommodating new computational models running on multipurpose healthcare devices, Impact of engineering solutions from hardware manufacturers on healthcare Apps; Modes of patient involvements in computations stored in Apps, particularly at the time of pandemics.

Minitrack Co-Chairs

Dr Radmila Juric (Primary Contact)
Independent Researcher
ALMAIS consultancy, UK
[email protected]

Dr Sang Suh
Department of Computer Science & Information Systems
Texas A&M University-Commerce
Dallas, TX, US
[email protected]

Dr Ying-Chyi Chou (周瑛琪)
Department of Business Administration,
Tunghai University, Taiwan
Email: [email protected]