Search results for: Shaker El-Sappagh

Items from 1 to 13 out of 13 results

article

Benchmarking large-scale data management for Internet of Things

Abdeltawab Hendawi, Jayant Gupta, Jiayi Liu, Ankur Teredesai, more

The Journal of Supercomputing > 2019 > 75 > 12 > 8207-8230

In the current era of the Internet of Things (IoT), massive number of sensors are used in our daily lives. Sensors are everywhere around us. They exist in our homes, work places, streets, cars, and even ourselves. Examples include home appliances, wearable devices, and medical sensors. These sensors generate huge amount of dynamic, heterogeneous, and unstructured data that need special handling beyond...

article

A mobile health monitoring-and-treatment system based on integration of the SSN sensor ontology and the HL7 FHIR standard

Shaker El-Sappagh, Farman Ali, Abdeltawab Hendawi, Jun-Hyeog Jang, more

BMC Medical Informatics and Decision Making > 2019 > 19 > 1 > 1-36

Background Mobile health (MH) technologies including clinical decision support systems (CDSS) provide an efficient method for patient monitoring and treatment. A mobile CDSS is based on real-time sensor data and historical electronic health record (EHR) data. Raw sensor data have no semantics of their own; therefore, a computer system cannot interpret these data automatically. In addition, the interoperability...

article

A Fibrosis Diagnosis Clinical Decision Support System Using Fuzzy Knowledge

Sara Sweidan, Shaker El-Sappagh, Hazem El-Bakry, Sahar Sabbeh, more

Arabian Journal for Science and Engineering > 2019 > 44 > 4 > 3781-3800

Liver cirrhosis, the end stage of chronic liver disease, is one of the major risk factors for the development of liver cancer, and may result in premature death. This research proposes a fuzzy fibrosis decision support (F2DS) system. It is a fuzzy knowledge-based expert system for liver fibrosis stage prediction. F2DS is carefully based on a set of knowledge acquisition and machine learning techniques...

article

SNOMED CT standard ontology based on the ontology for general medical science

Shaker El-Sappagh, Francesco Franda, Farman Ali, Kyung-Sup Kwak

BMC Medical Informatics and Decision Making > 2018 > 18 > 1 > 1-19

Background Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT, hereafter abbreviated SCT) is a comprehensive medical terminology used for standardizing the storage, retrieval, and exchange of electronic health data. Some efforts have been made to capture the contents of SCT as Web Ontology Language (OWL), but these efforts have been hampered by the size and complexity of SCT. Method...

article

A case-base fuzzification process: diabetes diagnosis case study

Shaker El-Sappagh, Mohammed Elmogy, Farman Ali, Kyung-Sup Kwak

Soft Computing > 2019 > 23 > 14 > 5815-5834

Medical case-based reasoning (CBR) systems require the handling of vague or imprecise data. The fuzzy set theory is particularly suitable for this purpose. This paper proposes a case-base preparation framework for CBR systems, which converts the electronic health record medical data into fuzzy CBR knowledge. It generates fuzzy case-base knowledge by suggesting a standard crisp entity–relationship...

article

DMTO: a realistic ontology for standard diabetes mellitus treatment

Shaker El-Sappagh, Daehan Kwak, Farman Ali, Kyung-Sup Kwak

Journal of Biomedical Semantics > 2018 > 9 > 1 > 1-30

Background Treatment of type 2 diabetes mellitus (T2DM) is a complex problem. A clinical decision support system (CDSS) based on massive and distributed electronic health record data can facilitate the automation of this process and enhance its accuracy. The most important component of any CDSS is its knowledge base. This knowledge base can be formulated using ontologies. The formal description logic...

article

A fuzzy ontology modeling for case base knowledge in diabetes mellitus domain

Shaker El-Sappagh, Mohammed Elmogy

Engineering Science and Technology, an International Journal > 2017 > 20 > 3 > 1025-1040

Knowledge-Intensive Case-Based Reasoning Systems (KI-CBR) mainly depend on ontologies. Ontology can play the role of case-base knowledge. The combination of ontology and fuzzy logic reasoning is critical in the medical domain. Case-base representation based on fuzzy ontology is expected to enhance the semantic and storage of CBR knowledge-base. This paper provides an advancement to the research of...

article

An encoding methodology for medical knowledge using SNOMED CT ontology

Shaker El-Sappagh, Mohammed Elmogy

Journal of King Saud University - Computer and Information Sciences > 2016 > 28 > 3 > 311-329

Knowledge-Intensive Case Based Reasoning (KI-CBR) systems mainly depend on ontology. Using ontology as domain knowledge supports the implementation of semantically-intelligent case retrieval algorithms. The case-based knowledge must be encoded with the same concepts of the domain ontology. Standard medical ontologies, such as SNOMED CT (SCT), can play the role of domain ontology to enhance case representation...

article

DDO: a diabetes mellitus diagnosis ontology

Shaker El-Sappagh, Farman Ali

Applied Informatics > 2016 > 3 > 1 > 1-28

Diabetes mellitus is a major cause of morbidity and mortality in humans. Early diagnosis is the first step toward the management of this condition. However, a diagnosis involves several variables, which makes it difficult to arrive at an accurate and timely diagnosis and to construct accurate personalized treatment plans. An electronic health record system requires an integrated decision support capability,...

article

A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis

Shaker El-Sappagh, Mohammed Elmogy, A.M. Riad

Artificial Intelligence In Medicine > 2015 > 65 > 3 > 179-208

Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones.Knowledge-intensive CBR using formal ontologies is an evolvement of this paradigm. Ontologies can be...

chapter

A standard fragment of EHR relational data model for diabetes mellitus diagnosis

Shaker El-Sappagh, Mohammed El Mogy, Alaa M. Riad

2014 9th International Conference on Informatics and Systems > DEKM-1 - DEKM-9

2014 9th International Conference on Informatics and Systems (INFOS)

Clinical Decision Support System (CDSS) helps in early detection and diagnosis of diabetes. Case Based Reasoning (CBR)-based CDSS is the applicable technique for these ill formed problems. Building CBR case-base is the most critical challenge. Electronic health record (EHR) is the complete source of cases for CBR. However, mapping EHR into case-base is challenge. This paper proposes a standard relational...

chapter

A proposed SNOMED CT ontology-based encoding methodology for diabetes diagnosis case-base

Shaker El-Sappagh, Mohammed Elmogy, A. M. Riad, Hosam Zaghloul, more

2014 9th International Conference on Computer Engineering & Systems (ICCES) > 184 - 191

2014 9th International Conference on Computer Engineering & Systems (ICCES)

Domain knowledge ontology supports the implementation of intelligent Case Based Reasoning (CBR) systems. Standardized terminologies support efficient indexing and processing of patient data. It is an essential element for the implementation of knowledge-based clinical decision support by exploiting pre-defined semantic relationships, both hierarchical and non-hierarchical in nature. Systemized Nomenclature...

chapter

A diabetes diagnostic domain ontology for CBR system from the conceptual model of SNOMED CT

Shaker El-Sappagh, Samir El-Masri, Mohammed Elmogy, Alaa M. Riad

2014 International Conference on Engineering and Technology (ICET) > 1 - 7

2014 International Conference on Engineering and Technology (ICET)

Domain ontology or background knowledge facilitates the implementation of knowledge intensive case based reasoning systems. Based on the conceptual model of SNOMED CT, this research will propose a methodology for building ontology for diabetes concepts based on most recent diabetes clinical guidelines. All concepts, descriptions and relationships related to diabetes mellitus diagnosis including laboratory...

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