Telemedicine framework using case-based reasoning with evidences

Abstract

Telemedicine is the medical practice of information exchanged from one location to another through electronic communications to improve the delivery of health care services. This research article describes a telemedicine framework with knowledge engineering using taxonomic reasoning of ontology modeling and semantic similarity. In addition to being a precious support in the procedure of medical decision-making, this framework can be used to strengthen significant collaborations and traceability that are important for the development of official deployment of telemedicine applications. Adequate mechanisms for information management with traceability of the reasoning process are also essential in the fields of epidemiology and public health. In this paper we enrich the case-based reasoning process by taking into account former evidence-based knowledge. We use the regular four steps approach and implement an additional (iii) step: (i) establish diagnosis, (ii) retrieve treatment, (iii) apply evidence, (iv) adaptation, (v) retain. Each step is performed using tools from knowledge engineering and information processing (natural language processing, ontology, indexation, algorithm, etc.). The case representation is done by the taxonomy component of a medical ontology model. The proposed approach is illustrated with an example from the oncology domain. Medical ontology allows a good and efficient modeling of the patient and his treatment. We are pointing up the role of evidences and specialist's opinions in effectiveness and safety of care.

Discovering frequent patterns for in-flight incidents

“…This system will assist the volunteers (doctor on board staff) for medical care and will serve as a telemedicine framework with ground teams. Telemedicine is a remote medical practice using information technologies and telecommunication (Sene, Kamsu-Foguem, & Rumeau, 2015). This is an opportunity for safety of life applications like aviation and maritime transport where medical evacuation can cost too much.…”

Decision support system for in-flight emergency events

“…In the conceptualization processes, the ontologies can be engaged in specifying the semantic meaning of the models within telemedicine systems (Kamsu-Foguem 2014b). It is for this reason that ontology specifications are one of the key elements of the proposed research work (La-Ongsri and Roddick 2015) (Sene et al 2015). A formal ontology specification is described using a language that contains adequate mathematical semantics that provides two main advantages (1) an interpretation of descriptions that guarantees the absence of ambiguity in the models produced and (2) reasoning procedures for the analysis of the specified descriptions utilized to infer new knowledge or to verify the properties of models.…”

“…In a KBS, the available measurements and observations, supported by the knowledge and beliefs, are used to make decisions on how to better serve the target objectives. The decision-making process can be optimized by the use of different types of evidence (coming from meta-analyses, systematic reviews, and randomized controlled trials) (Sene et al 2015). Given the features of the different types of evidence, the information can be weighted differently in order to yield informed decisions with associated recommendations.…”

A viewpoint-based case-based reasoning approach utilising an enterprise architecture ontology for experience management

“…The used ontology "[...] employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians" (Shen et al 2015, p.307). Sene, Kamsu-Foguem, and Rumeau (2015) propose an ontology-based CBR approach based on taxonomic reasoning for telemedicine in the oncology domain with the inclusion of natural language processing (NLP). Delir Haghighi et al (2013) introduce a development and evaluation of an ontology-based CBR system in medical emergency management.…”