A5061462416- Data Quality and Management
- Big Data and Business Intelligence
- Semantic Web and Ontologies
- Artificial Intelligence in Healthcare
- AI in cancer detection
- Pancreatic and Hepatic Oncology Research
- Big Data Technologies and Applications
- Artificial Intelligence in Healthcare and Education
- Advanced Database Systems and Queries
- Radiomics and Machine Learning in Medical Imaging
- Scientific Computing and Data Management
- Electronic Health Records Systems
- Machine Learning in Healthcare
University of Piraeus
2022-2024
University of Puerto Rico at Carolina
2021-2022
The modern healthcare landscape is overwhelmed by data derived from heterogeneous IoT sources and Electronic Health Record (EHR) systems. Based on the advancements in science Machine Learning (ML), an improved ability to integrate process so-called primary secondary fosters provision of real-time personalized decisions. In that direction, innovative mechanism for processing integrating health-related introduced this article. It describes details its internal subcomponents workflows, together...
Given the challenge that healthcare related data are being obtained from various sources and in divergent formats there is an emerging need for providing improved automated techniques technologies perform qualification standardization of these data. The approach presented this paper introduces a novel mechanism cleaning, qualification, collected primary secondary types. latter realized through design implementation three (3) integrated subcomponents, Data Cleaner, Qualifier, Harmonizer...
In recent years, vast amounts of data are generated from a plethora devices, systems, and platforms, covering wide range domains. This increase generates the necessity to access technical technological resources enabling efficient ready-to-use analysis solutions, including for training learning in addition infrastructure elements, as well Artificial Intelligence (AI)/Machine Learning (ML) techniques. Current solutions siloed, instead being structured, integrated, openly accessible...
The healthcare domain is increasingly adopting IoT and Electronic Health Record (EHR) systems, generating vast volumes of data. This shift driven by the growing need delivering right information to individuals, at time. latter underscores importance a comprehensive strategy for efficiently collecting, utilizing, analyzing health-related data not only enhance overall management but also provision timely personalized prevention strategies. highest especially in scenarios where lack effective...
This study proposes an optimized machine learning (ML) methodology and workflow to examine pancreatic cancer factors, taking advantage of real-world data collected from three different hospitals. The overall proposed processing analysis pipeline incorporates transformation, cleaning, mapping techniques such as translating specific values into a common language calculating average blood result tests per patient. ML models utilized under the scope this research work are supervised techniques,...