Fuzzy logic in medicine

Ozsahin, Dilber Uzun; Uzun, Berna; Ozsahin, Ilker; Mustapha, Mubarak Taiwo; Musa, Musa Sani

doi:10.1016/b978-0-12-818946-7.00006-8

Cited by 28 publications

(16 citation statements)

References 41 publications

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“…Situations in real-life do not fall in the crisp 'true' or 'false' state, vagueness and ambiguity in the natural language is always present (De Silva, 2018). A variable with values represented in words in natural language is called linguistic variable (Uzun Ozsahin et al, 2020). After the introduction of Fuzzy logic by Lotfi Zadeh (Zadeh, 1965)., the linguistic vagueness can be described crisply.…”

Section: Fuzzy Methodsmentioning

confidence: 99%

“…Recently, fuzzy sets have been used extensively in healthcare MCDM for material and technique selection of best alternative (Mishra et al, 2020;Chakraborty & Saha, 2022b;Chaurasiya & Jain, 2022;Krishankumar et al, 2022;Salimian & Mousavi, 2022;Liu et al, 2022;Chakraborty & Saha, 2023;Quasim et al, 2023;Ghorbani et al, 2023). In the field of medicine, diagnosis of the disease is always accompanied by uncertainties and ambiguities (De Silva, 2018;Uzun Ozsahin et al, 2020). Behavior and symptoms of a disease vary from patient to patient.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, the same symptoms can be seen due to different diseases thus presenting a difficult treatment regime. Such uncertainties resulted in inclusion of fuzzy logic into the field of medicine (Uzun Ozsahin et al, 2020). Fuzzy logic has been used in disease diagnosis, medical treatment selection, and monitoring of data of patients in real-time (Uzun Ozsahin et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Application of fuzzy TOPSIS for prioritization of patients on elective surgeries waiting list - A novel multi-criteria decision-making approach

Hassan¹,

Umer²,

Hassan³

et al. 2023

Decis. Mak. Appl. Manag. Eng.

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Prioritizing patients is a growing concern in healthcare. Once resources are limited, prioritization is considered an effective and viable solution in provision of healthcare treatment to awaiting patients. Prioritization is a preferred approach that helps clinicians to apportion scarce resources fairly and transparently. In this study, a novel methodology of prioritizing the patient is formulated using fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The objective is based on actual hospital conditions in Pakistan. The proposed methodology has two contributions: objective scoring mechanism that translates the patient’s condition given in human linguistic terms; and second methodology to prioritize patients according to corresponding scores. To validate the proposed methodology, simulation was carried out on actual data collected in real-time by surgeons, while providing consultations to their patients. The proposed methodology outperforms the traditional methodology by reducing average waiting time by 34% (from 4.246 to 2.810 days), minimize wait time and delays by 46.7% (from 15 to 8 days), and number of surgery days by 18%. The majority of the previously presented researched methodologies prioritize the patients subjectively. This study presents an objective methodology to prioritize the patients and decrease wait-times while ensuring transparency and equity.

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Section: Fuzzy Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Application of fuzzy TOPSIS for prioritization of patients on elective surgeries waiting list - A novel multi-criteria decision-making approach

Hassan¹,

Umer²,

Hassan³

et al. 2023

Decis. Mak. Appl. Manag. Eng.

View full text Add to dashboard Cite

show abstract

“…Therefore, it is necessary to capture these terms in the course of a knowledge acquisition and to represent their meaning. Fuzzy logic is already used to describe medical contexts (Ozsahin, 2020). Downstream neural networks can be used to realize classifiers that are capable of learning (Gayathri, 2018).…”

Section: Knowledge Modelingmentioning

confidence: 99%

The European Conference on Aging & Gerontology 2022: Official Conference Proceedings

2022

EGen Official Conference Proceedings

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When aiming for built environments and systems that foster resiliency and resources, one of the most crucial aspects of design is to properly address the users' needs. While comprehensive research and an empathetic mindset are important prerequisites of this process, the inclusion of all relevant stakeholders cannot be compensated by any methodology. With regards to co-creation with people with dementia, this can pose additional challenges as participants might have difficulties to articulate their feelings and thoughts or design teams might struggle to come up with interactive formats that fit the current mental and physical abilities of the participants. Therefore, understanding key requirements and principles that are particular for the field of neurodiversity can be of great help in order to successfully engage users in the design process. In this paper we outline a transdisciplinary research process conducted by scholars from UCL in cooperation with other stakeholders from academia and practise. This multi-stage process aimed at creating a framework for developing co-creation workshops and approaches for people living with dementia and other forms of neurodiversity.

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“…Tumor research is one significant field where modeling techniques are used [3]. When the system is unclear, fuzzy mathematics provides an outlet for bio-mathematical issues such as cancer to reach a realistic solution and a better and more exciting knowledge of a particular phenomenon [4,5]. Zadeh introduced fuzzy sets in 1965 to deal with data having non-statistical uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty-based Gompertz growth model for tumor population and its numerical analysis

Sheergojri

Iqbal

Agarwal

et al. 2022

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

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For treating cancer, tumor growth models have shown to be a valuable resource, whether they are used to develop therapeutic methods paired with process control or to simulate and evaluate treatment processes. In addition, a fuzzy mathematical model is a tool for monitoring the influences of various elements and creating behavioral assessments. It has been designed to decrease the ambiguity of model parameters to obtain a reliable mathematical tumor development model by employing fuzzy logic.The tumor Gompertz equation is shown in an imprecise environment in this study. It considers the whole cancer cell population to be vague at any given time, with the possibility distribution function determined by the initial tumor cell population, tumor net population rate, and carrying capacity of the tumor. Moreover, this work provides information on the expected tumor cell population in the maximum period. This study examines fuzzy tumor growth modeling insights based on fuzziness to reduce tumor uncertainty and achieve a degree of realism. Finally, numerical simulations are utilized to show the significant conclusions of the proposed study.

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Fuzzy logic in medicine

Cited by 28 publications

References 41 publications

Application of fuzzy TOPSIS for prioritization of patients on elective surgeries waiting list - A novel multi-criteria decision-making approach

Application of fuzzy TOPSIS for prioritization of patients on elective surgeries waiting list - A novel multi-criteria decision-making approach

The European Conference on Aging & Gerontology 2022: Official Conference Proceedings

Uncertainty-based Gompertz growth model for tumor population and its numerical analysis

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