Fuzzy logic and semiotic methods in modeling of medical concepts

Kwiatkowska, Mila; Kielan, Krzysztof

doi:10.1016/j.fss.2012.03.011

Cited by 21 publications

(10 citation statements)

References 22 publications

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“…The first group of studies is mostly concerned with the problem of diagnosis of depression type and severity, trying to provide different automatic diagnosis tools or classification techniques for these diagnoses [17][18][19][20][21][22]. There are also some studies in this group focused on evaluating and improving the diagnostic and therapeutic reasoning of primary care physicians [23].…”

Section: Computer Methods and Major Depressionmentioning

confidence: 99%

A model for continuous monitoring of patients with major depression in short and long term periods

Mugica

Nebot

Bagherpour

et al. 2017

THC

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The final publication is available at IOS Press through http://dx.doi.org/10.3233/THC-161289BACKGROUND AND OBJECTIVE: Major depressive disorder causes more human suffering than any other disease affecting humankind. It has a high prevalence and it is predicted that it will be among the three leading causes of disease burden by 2030. The prevalence of depression, all of its social and personal costs, and its recurrent characteristics, put heavy constraints on the ability of the public healthcare system to provide sufficient support for patients with depression. In this research, a model for continuous monitoring and tracking of depression in both short-term and long-term periods is presented. This model is based on a new qualitative reasoning approach. METHOD: This paper describes the patient assessment unit of a major depression monitoring system that has three modules: a patient progress module, based on a qualitative reasoning model; an analysis module, based on expert knowledge and a rules-based system; and the communication module. These modules base their reasoning mainly on data of the patient's mood and life events that are obtained from the patient's responses to specific questionnaires (PHQ-9, M.I.N.I. and Brugha). The patient assessment unit provides synthetic and useful information for both patients and physicians, keeps them informed of the progress of patients, and alerts them in the case of necessity. RESULTS: A set of hypothetical patients has been defined based on clinically possible cases in order to perform a complete scenario evaluation. The results that have been verified by psychiatrists suggest the utility of the platform. CONCLUSION: The proposed major depression monitoring system takes advantage of current technologies and facilitates more frequent follow-up of the progress of patients during their home stay after being diagnosed with depression by a psychiatrist.Peer ReviewedPostprint (author's final draft

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Section: Computer Methods and Major Depressionmentioning

confidence: 99%

A model for continuous monitoring of patients with major depression in short and long term periods

Mugica

Nebot

Bagherpour

et al. 2017

THC

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“…However, fuzzy logic theory has limited ability to elicit the variables/elements and reflect their contextual interpretation. Therefore, incorporating the semiotic approach into fuzzy logic is a candidate solution for conceptual and computational modelling, which allows for the explicit representation of the contextual interpretation [3] and ensures the effective implementation of CDSSs.…”

Section: Fuzzy Logic Methodologymentioning

confidence: 99%

“…However, not everyone with a high BMI is obese, especially the one who exercises regularly. Besides, knowledge is usually characterized by a high level of context-dependency [3] and evolvement [4]; therefore, it cannot be defined independently without their pragmatic meanings. Thus, without appropriately handling with these challenges, the CDSSs might not support the clinical practice effectively.…”

Section: Introductionmentioning

confidence: 99%

Incorporating Semiotics into Fuzzy Logic to Enhance Clinical Decision Support Systems

Chen

Gao

Liu

et al. 2014

Service Science and Knowledge Innovation

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Abstract. In order to enhance the quality of care, healthcare organisations are increasingly resorting to clinical decision support systems (CDSSs), which provide physicians with appropriate health care decisions or recommendations. However, how to explicitly represent the diverse vague medical knowledge and effectively reason in the decision-making process are still problems we are confronted. In this paper, we incorporate semiotics into fuzzy logic to enhance CDSSs with the aim of providing both the abilities of describing medical domain concepts contextually and reasoning with vague knowledge. A semiotically inspired fuzzy CDSSs framework is presented, based on which the vague knowledge representation and reasoning process are demonstrated.

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“…Dengan kata lain, tidak terdapat batas yang ketat antara apa yang sehat, apa yang berisiko dan apa yang sakit, sehingga membedakannya tidak pasti dan jelas. [5] Faktor yang dapat menimbulkan stroke dibedakan menjadi faktor risiko yang tidak dapat diubah atau tidak dapat dimodifikasi dan faktor risiko yang dapat diubah atau dapat dimodifikasi. [6] Faktor risiko yang tidak dapat diubah diantaranya peningkatan usia dan jenis kelamin laki-laki.…”

Section: Pendahuluanunclassified

Case Based Reasoning Diagnosis Risiko Penyakit Stroke Menggunakan Metode Hamming Distance

Natassya

Tursina

Sukamto

2019

justin

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Stroke merupakan salah satu penyakit yang dapat menimbulkan tingkat kematian maupun cacat tubuh yang tertinggi. Keadaan ini dapat dicegah dengan mengenali risiko yang dapat terjadi sedini mungkin. Organisasi stroke dunia mencatat bahwa hampir 85% orang yang mempunyai faktor risiko dapat terhindar dari penyakit stroke apabila mereka menyadari dan mengatasi faktor risiko tersebut sejak dini. Untuk itu, sebuah sistem yang dapat mendiagnosis risiko penyakit stroke dirasa perlu. Sistem yang diperlukan adalah sistem yang berbasis pengetahuan untuk memperlajari dan memecahkan masalah berdasarkan pengalaman pada masa lalu yang merupakan ciri dari case based reasoning. Case Based Reasoning adalah penalaran untuk penyelesaian masalah berbasis pengetahuan untuk mempelajari dan memecahkan masalah berdasarkan pengalaman masa lalu. Permasalahan baru dapat diselesaikan dengan memanfaatkan kembali permasalahan lama yang memiliki kesamaan yang telah diselesaikan sebelumnya. Sistem case based reasoning dibuat menggunakan metode Hamming Distance sebagai penghitungan similaritas data biner. Hasil dari sistem ini berupa diagnosis risiko stroke yaitu rendah, sedang dan tinggi. Pengujian sistem dilakukan dengan dua cara, yaitu pengujian tahapan Case Based Reasoning dan kesesuaian hasil. Hasil yang didapat dari pengujian yang dilakukan adalah sistem dapat melakukan empat tahapan Case Based Reasoning yaitu tahap retrieve, tahap reuse, tahap revise dan tahap retain. Hasil yang didapat dari pengujian kesesuaian hasil adalah sistem dapat mendiagnosis 11 kasus yang sesuai dengan diagnosis pakar dari 15 kasus yang diuji. Dapat disimpulkan bahwa sistem dapat mendiagnosis risiko stroke.

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Fuzzy logic and semiotic methods in modeling of medical concepts

Cited by 21 publications

References 22 publications

A model for continuous monitoring of patients with major depression in short and long term periods

A model for continuous monitoring of patients with major depression in short and long term periods

Incorporating Semiotics into Fuzzy Logic to Enhance Clinical Decision Support Systems

Case Based Reasoning Diagnosis Risiko Penyakit Stroke Menggunakan Metode Hamming Distance

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