Division of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Chennai, India.
Department of Radiology, Karpagam Medical College and Hospital, Coimbatore 641032, Tamil Nadu, India.
Acta Trop. 2024 Apr;252:107132. doi: 10.1016/j.actatropica.2024.107132. Epub 2024 Jan 26.
Tuberculosis (TB) is a contagious illness caused by Mycobacterium tuberculosis. The initial symptoms of TB are similar to other respiratory illnesses, posing diagnostic challenges. Therefore, the primary goal of this study is to design a novel decision-support system under a bipolar intuitionistic fuzzy environment to examine an effective TB diagnosing method.
To achieve the aim, a novel fuzzy decision support system is derived by integrating PROMETHEE and ARAS techniques. This technique evaluates TB diagnostic methods under the bipolar intuitionistic fuzzy context. Moreover, the defuzzification algorithm is proposed to convert the bipolar intuitionistic fuzzy score into crisp score.
The proposed method found that the sputum test (T) is the most accurate in diagnosing TB. Additionally, comparative and sensitivity analyses are derived to show the proposed method's efficiency.
The proposed bipolar intuitionistic fuzzy sets, combined with the PROMETHEE-ARAS techniques, proved to be a valuable tool for assessing effective TB diagnosing methods.
结核病（TB）是由结核分枝杆菌引起的传染性疾病。TB 的初始症状与其他呼吸道疾病相似，这给诊断带来了挑战。因此，本研究的主要目标是在双极直觉模糊环境下设计一个新的决策支持系统，以检验一种有效的 TB 诊断方法。
为了实现这一目标，通过整合 PROMETHEE 和 ARAS 技术，得到了一个新的模糊决策支持系统。该技术在双极直觉模糊环境下评估 TB 诊断方法。此外，提出了一种去模糊算法，将双极直觉模糊分数转换为清晰分数。
该方法发现痰检（T）在诊断 TB 方面最准确。此外，还进行了比较和敏感性分析，以显示所提出方法的效率。
所提出的双极直觉模糊集与 PROMETHEE-ARAS 技术相结合，被证明是评估有效 TB 诊断方法的有用工具。
