Information Technology

Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies.

BACKGROUND: Ontologies are widely used throughout the biomedical domain. These ontologies formally represent the classes and relations assumed to exist within a domain. As scientific domains are deeply interlinked, so too are their representations. While individual ontologies can be tested for consistency and coherency using automated reasoning methods, systematically combining ontologies of multi...

Cyberattacks Detection in IoT-Based Smart City Applications Using Machine Learning Techniques.

In recent years, the widespread deployment of the Internet of Things (IoT) applications has contributed to the development of smart cities. A smart city utilizes IoT-enabled technologies, communications and applications to maximize operational efficiency and enhance both the service providers' quality of services and people's wellbeing and quality of life. With the growth of smart city networks, h...

Data augmentation-based conditional Wasserstein generative adversarial network-gradient penalty for XSS attack detection system.

The rapid growth of the worldwide web and accompanied opportunities of web applications in various aspects of life have attracted the attention of org...

De-Identification of Facial Features in Magnetic Resonance Images: Software Development Using Deep Learning Technology.

BACKGROUND: High-resolution medical images that include facial regions can be used to recognize the subject's face when reconstructing 3-dimensional (...

The Use of Synthetic Electronic Health Record Data and Deep Learning to Improve Timing of High-Risk Heart Failure Surgical Intervention by Predicting Proximity to Catastrophic Decompensation.

Although many clinical metrics are associated with proximity to decompensation in heart failure (HF), none are individually accurate enough to risk-s...

Generalized Radiographic View Identification with Deep Learning.

To explore the feasibility of an automatic machine-learning algorithm-based quality control system for the practice of diagnostic radiography, perform...

Artificial intelligence and multi agent based distributed ledger system for better privacy and security of electronic healthcare records.

BACKGROUND: Application of Artificial Intelligence (AI) and the use of agent-based systems in the healthcare system have attracted various researchers...

A Method to Improve Availability and Quality of Patient Race Data in an Electronic Health Record System.

BACKGROUND: Although federal regulations mandate documentation of structured race data according to Office of Management and Budget (OMB) categories i...

From electronic health records to terminology base: A novel knowledge base enrichment approach.

Enriching terminology base (TB) is an important and continuous process, since formal term can be renamed and new term alias emerges all the time. As a...

The ImageJ ecosystem: Open-source software for image visualization, processing, and analysis.

For decades, biologists have relied on software to visualize and interpret imaging data. As techniques for acquiring images increase in complexity, re...

Analytics with artificial intelligence to advance the treatment of acute respiratory distress syndrome.

Artificial intelligence (AI) has found its way into clinical studies in the era of big data. Acute respiratory distress syndrome (ARDS) or acute lung ...

Closing the Digital Health Evidence Gap: Development of a Predictive Score to Maximize Patient Outcomes.

Clinical studies of telemedicine (TM) programs for chronic illness have demonstrated mixed results across settings and populations. With recent uptak...

Facilitating the Development of Deep Learning Models with Visual Analytics for Electronic Health Records.

Electronic health record (EHR) data are widely used to perform early diagnoses and create treatment plans, which are key areas of research. We aimed t...

TAPER: Time-Aware Patient EHR Representation.

Effective representation learning of electronic health records is a challenging task and is becoming more important as the availability of such data i...

Prediction of severe chest injury using natural language processing from the electronic health record.

INTRODUCTION: Trauma injury severity scores are currently calculated retrospectively from the electronic health record (EHR) using manual annotation b...

Assessment of User Needs for Telemedicine Robots in a Developing Nation Hospital Setting.

This study aimed to investigate the needs of medical users of telemedicine robots to encourage international cooperation and development. As the use...

A Randomized Study Using Telepresence Robots for Behavioral Health in Interprofessional Practice and Education.

The events of the coronavirus disease 2019 (COVID-19) pandemic forced the world to adopt telemedicine frameworks to comply with isolation and stay-at...

Graphical Presentations of Clinical Data in a Learning Electronic Medical Record.

BACKGROUND: Complex electronic medical records (EMRs) presenting large amounts of data create risks of cognitive overload. We are designing a Learning...

Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management.

Ambulatory monitoring is increasingly important for cardiovascular care but is often limited by the unpredictability of cardiovascular events, the int...

Integrating Genomics and Clinical Data for Statistical Analysis by Using GEnome MINIng (GEMINI) and Fast Healthcare Interoperability Resources (FHIR): System Design and Implementation.

BACKGROUND: The introduction of next-generation sequencing (NGS) into molecular cancer diagnostics has led to an increase in the data available for th...