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A case study of disease analysis based on symptoms is presented to illustrate the decision-making procedure involving four medical professionals, five symptoms, and five probable diseases. Furthermore, We have presented two cases of disease analysis using non-standard and standard Pythagorean fuzzy soft matrices. The results suggest that the proposed Mabala\u2019s distance measure has great potential for improving disease analysis. The proposed Mabala distance measure is compared to five existing distance measures using an identical data set of prospective disease symptoms. The comparative analysis indicates that the suggested Mabala distance measure\u2019s result almost coincides with the results of the other distance measurements. A set of sensitivity analysis is provided to analyze the durability and consistency of the proposed distance measurements across different input scenarios.<\/jats:p>","DOI":"10.1007\/s40747-024-01376-5","type":"journal-article","created":{"date-parts":[[2024,3,9]],"date-time":"2024-03-09T09:01:52Z","timestamp":1709974912000},"page":"4373-4395","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["Group decision on rationalizing disease analysis using novel distance measure on Pythagorean fuzziness"],"prefix":"10.1007","volume":"10","author":[{"given":"B.","family":"Baranidharan","sequence":"first","affiliation":[]},{"given":"Jie","family":"Liu","sequence":"additional","affiliation":[]},{"given":"G. S.","family":"Mahapatra","sequence":"additional","affiliation":[]},{"given":"B. 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