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Author

Ramona Popa

Bio: Ramona Popa is an academic researcher from Politehnica University of Bucharest. The author has contributed to research in topics: Ontology (information science) & Ontology learning. The author has an hindex of 1, co-authored 9 publications receiving 5 citations.

Papers
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Proceedings ArticleDOI
22 Jun 2017
TL;DR: The objective of this work is to extend the work from PrEmISES for raising the medical literacy of empowered patients by creating a digital library that contains relevant articles from different medical domain by using automatic tool generation algorithms for the creation of ontologies.
Abstract: The work of this p aper is done within the context of European Project E! 8949 PrEmISES 1. One of the central pieces of PrEmISES[16] is the use of automatic tool generation algorithms for the creation of ontologies. The objective of this work is to extend the work from PrEmISES for raising the medical literacy of empowered patients by creating a digital library that contains relevant articles from different medical domain. It should be noted that a large number of persons are interested in finding relevant information about their condition. We have chosen to discuss in this research the automated generation of ontologies for the medical domain. By the use of ontologies that gives key terms from a domain, the creation of the digital library can be done by crawling from the Internet articles which are related to the profile of the user and that are based on the key terms of the ontologies. The articles from the digital library can be used by a patient to raise his / her knowledge and literacy related to his/her diseases.

7 citations

Proceedings ArticleDOI
01 Jul 2021
TL;DR: In this paper, the authors review the existing research and results for healthcare robotic telepresence and insist on the functionalities, characteristics and interfaces of these devices, with the intention to start developing similar solutions.
Abstract: The healthcare system is a decided target for new technologies because the results are affecting directly human life and quality of life. Robotic telepresence is a robotics domain with an expanding interest and part of it is dedicated to the support of hospital patients and of elders. Because of the continuous functioning, they are fit to persons which require permanent assistance, increasing their care and their quality of life and to persons which are isolated because of communicable infectious diseases, increasing their healthcare in conditions of safety for the others. The concentration on the study of robotic telepresence for healthcare was vastly influenced by the COVID-19 pandemic and solutions using this approach were proposed all around the world. We will review in this paper the existing research and results for healthcare robotic telepresence and we will insist on the functionalities, characteristics and interfaces of these devices, with the intention to start developing similar solutions.

2 citations

Proceedings ArticleDOI
24 May 2021
TL;DR: In this paper, a software application based on the Health Level 7 Fast Healthcare Interoperability Resources standard (HL7 FHIR Questionnaire format) is proposed. But the authors focus on the creation of questionnaires that are used to gather medical data, as well as for quantitative research purposes.
Abstract: Information technology evolved as the years passed by, while interoperability of healthcare information systems remains a challenge. The current paper proposes the conceptualization of a software application based on the Health Level 7 Fast Healthcare Interoperability Resources standard. The intelligent solution named Formisio incorporates the creation of questionnaires that are used to gather medical data, as well as for quantitative research purposes. The paper outlines the system architecture components and the focus was put on components which are related to front end question editor, web based and mobile questionnaire version, back-end editor logic and questions results analyzers. The questionnaires are created and stored in the HL7 FHIR Questionnaire format. The obtained results are saved as HL7 FHIR QuestionnaireResponse resources. Furthermore, medical questionnaires are generated for various types of HL7 FHIR resources.

2 citations

Proceedings ArticleDOI
01 Apr 2019
TL;DR: A comparison between the Old Testament and the New Testament in terms of knowledge extraction and ontology learning is presented, using the Bible as source for the text and using Text2Onto as the main tool in order to obtain the most relevant concepts.
Abstract: The objective of this work is to present a comparison between the Old Testament and the New Testament in terms of knowledge extraction and ontology learning. It is a knows fact that these two books have many differences in term of size, practice of worship, prophecy and there is also a difference in the time period when they were written. By applying the ontology learning and knowledge extraction methods we were interested do see if these differences are revealed and what are the similarities among them. Ontology learning can be applied for the semantic analysis of text, in order to extract concepts, relations, which can be further used for automated summaries or critical comparison. Such activities are important in education as they can allow dynamic creation of content or analyses that can be further used in the educational process. Since ontology-learning methods require large corpus of unstructured data, we have chosen the Bible as source for the text. In this way, the new developed methods are validated, and they can be used successfully in other educational domains. The Bible is the religious text of Christians and Jews. The Bible contains a collection of scriptures that was written by many authors, at different time and locations. Computationally, the Bible contains semi-structured information due to its organized structure of scriptures and numbered chapters. We have used Text2Onto as the main tool in order to obtain the most relevant concepts from the New Testament and then from The Old Testament. After that we analyze the most relevant concepts and the range of similarity for each domain identified in the New Testament and in The Old Testament. We can mention that there are no studies reported in the literature using ontology extraction for this religious domain. Those methods can be employed for automatic generation of content that can be further used in the educational process.

2 citations

Proceedings ArticleDOI
24 May 2021
TL;DR: In this article, the authors present a different perspective on how the documents can be archived and transmitted and expose the architecture of a system that has more features than common document management systems.
Abstract: Working in the coronavirus COVID-19 pandemic context, the entire world has started to perform their activities in online medium. This current situation has affected multiple industries and made companies realize the need of digitalization of a number vital but time-consuming processes. They are presently found in all activity domains when talking about paperwork and communication between governments and educational institutions. The article is based on the idea that as automation is gaining more and more access into our everyday lives, the old school methods of storing information will soon be replaced by databases of enormous dimensions which can be managed by people. Also, the technology available now, has the methods of helping the bureaucratic processes having as an effect a better communication between citizens and government. The paper presents a different perspective on how the documents can be archived and transmitted. It exposes the architecture of a system that has more features than common document management systems.

2 citations


Cited by
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Proceedings ArticleDOI
01 Sep 2018
TL;DR: A substantial overhaul of methodology is required to address the real complexity of health, and this can be achieved through the FHIR Ontology Mapper (FOM) technique, which aims at constructing healthcare ontologies from any data source, and then identifying both the structural and semantic similarities between the latter and the HL7 FHir resources ontologies.
Abstract: The healthcare sector faces multiple challenges in implementing, maintaining and upgrading its systems, including technical, security and interoperability difficulties. Ontologies are the key to achieve and improve healthcare interoperability, in the form of a permanent artefact of the specification of each of the medical concepts. However, since different ontologies may have contradicting or overlapping parts, the need for the creation of ontology matching techniques for identifying similarities between them is rising. In the meantime, a large number of ontologies, vocabularies and taxonomies, as well as medical standards are constructed and globally adopted (e.g. HL7 FHIR), without promising the existence of a single global ontology, any time soon. Thus, a substantial overhaul of methodology is required to address the real complexity of health. This can be achieved through the FHIR Ontology Mapper (FOM) technique that is presented in this paper, which aims at constructing healthcare ontologies from any data source, and then identifying both the structural and semantic similarities between the latter and the HL7 FHIR resources ontologies. The final matchings derive from the mean of the latter, aiming at translating healthcare data of any type, into the widely adopted HL7 FHIR standard, thus enabling interoperability and improving the quality of patient care and research.

19 citations

Journal ArticleDOI
TL;DR: In this paper , the authors discuss how novel therapeutic interventions involving social robots can potentially offer meaningful opportunities for overcoming some of the present challenges in post-traumatic stress disorder (PTSD).
Abstract: Post-Traumatic Stress Disorder (PTSD) is a severe psychiatric disorder with profound public health impact due to its high prevalence, chronic nature, accompanying functional impairment, and frequently occurring comorbidities. Early PTSD symptoms, often observed shortly after trauma exposure, abate with time in the majority of those who initially express them, yet leave a significant minority with chronic PTSD. While the past several decades of PTSD research have produced substantial knowledge regarding the mechanisms and consequences of this debilitating disorder, the diagnosis of and available treatments for PTSD still face significant challenges. Here, we discuss how novel therapeutic interventions involving social robots can potentially offer meaningful opportunities for overcoming some of the present challenges. As the application of social robotics-based interventions in the treatment of mental disorders is only in its infancy, it is vital that careful, well-controlled research is conducted to evaluate their efficacy, safety, and ethics. Nevertheless, we are hopeful that robotics-based solutions could advance the quality, availability, specificity and scalability of care for PTSD.

6 citations

Book ChapterDOI
11 Apr 2018
TL;DR: The findings underline that the new citation analysis and service system framework based on ontology and linked data are feasible, which can integrate information requirements and knowledge services, and provide users with more personalized and comprehensive services.
Abstract: Research focus: The aim of this chapter is to introduce a new citation analysis and service framework based on the semantic web technologies (e.g., ontology and linked data). Research methods: This research project is based on a review of relevant literature and a series of experimental results based on ontology and linked data. Motivation: Traditional citation analysis methods and tools are overly dependent on citation databases, and traditional citation information service may ignore the semantics of knowledge resources and lack ability to store and query data in a machine-readable mode. Findings: The findings underline that the new citation analysis and service system framework based on ontology and linked data are feasible, which can integrate information requirements and knowledge services, and provide users with more personalized and comprehensive services.

3 citations

Proceedings ArticleDOI
01 Apr 2019
TL;DR: A comparison between the Old Testament and the New Testament in terms of knowledge extraction and ontology learning is presented, using the Bible as source for the text and using Text2Onto as the main tool in order to obtain the most relevant concepts.
Abstract: The objective of this work is to present a comparison between the Old Testament and the New Testament in terms of knowledge extraction and ontology learning. It is a knows fact that these two books have many differences in term of size, practice of worship, prophecy and there is also a difference in the time period when they were written. By applying the ontology learning and knowledge extraction methods we were interested do see if these differences are revealed and what are the similarities among them. Ontology learning can be applied for the semantic analysis of text, in order to extract concepts, relations, which can be further used for automated summaries or critical comparison. Such activities are important in education as they can allow dynamic creation of content or analyses that can be further used in the educational process. Since ontology-learning methods require large corpus of unstructured data, we have chosen the Bible as source for the text. In this way, the new developed methods are validated, and they can be used successfully in other educational domains. The Bible is the religious text of Christians and Jews. The Bible contains a collection of scriptures that was written by many authors, at different time and locations. Computationally, the Bible contains semi-structured information due to its organized structure of scriptures and numbered chapters. We have used Text2Onto as the main tool in order to obtain the most relevant concepts from the New Testament and then from The Old Testament. After that we analyze the most relevant concepts and the range of similarity for each domain identified in the New Testament and in The Old Testament. We can mention that there are no studies reported in the literature using ontology extraction for this religious domain. Those methods can be employed for automatic generation of content that can be further used in the educational process.

2 citations