In the context of machine learning models for healthcare that predominantly handle discrete data and require high interpretability and simplicity, which approach offers more advantages:
Rough Set Theory or Neutrosophic Logic?
I invite experts to share their insights or experiences regarding the effectiveness, challenges, and suitability of these methodologies in managing uncertainties within health applications.
https://lc.kubagro.ru/Installation_Eidos.php
Lutsenko E.V. Forecasting the duration of the postoperative recovery period by the method of cardio-respiratory synchronism (SDS) using ASK analysis (part 1) / E.V. Lutsenko, E.V. Sergeeva // Polythematic network electronic scientific journal of Kuban State Agrarian University (Scientific Journal of KubGAU) [Electronic resource]. – Krasnodar: KubGAU, 2010. – №10(064). Pp. 142 – 178. – Cipher of the Information Register: 0421000012\0280, IDA [article ID]: 0641010014. – Access mode: http://ej.kubagro.ru/2010/10/pdf/14.pdf , 2,312 cu.l.
Lutsenko E.V. Forecasting the duration of the postoperative recovery period by the method of cardio-respiratory synchronism (SDS) using ASK analysis (part 2) / E.V. Lutsenko, E.V. Sergeeva // Polythematic network electronic scientific journal of Kuban State Agrarian University (Scientific Journal of KubGAU) [Electronic resource]. – Krasnodar: KubGAU, 2010. – №10(064). Pp. 179-203. – Cipher of the Information Register: 0421000012\0279, IDA [article ID]: 0641010015. – Access mode: http://ej.kubagro.ru/2010/10/pdf/15.pdf , 1,562 cu.p.l.
A systemic cognitive approach to predicting the duration of the postoperative recovery period based on information about the patient obtained by the method of cardio-respiratory synchronism (SDS) (cognitive structuring and formalization of the subject area and preparation of a training sample) / V.M. Pokrovsky, S.V. Polishchuk, E.V. Fomina, etc. // Polythematic network electronic Scientific Journal of the Kuban State University Agrarian University (KubGAU Scientific Journal) [Electronic resource]. – Krasnodar: KubGAU, 2009. – №07(051). Pp. 163-190. – The cipher of the Information Register: 0420900012\0084, IDA [article ID]: 0510907008. – Access mode: http://ej.kubagro.ru/2009/07/pdf/08.pdf , 1.75 cu.p.l.
A systemic cognitive approach to predicting the duration of the postoperative recovery period based on information about the patient obtained by the method of cardio-respiratory synchronism (SDS) (synthesis and verification of the semantic information model) / V.M. Pokrovsky, S.V. Polishchuk, E.V. Fomina, etc. // Polythematic network electronic Scientific Journal of the Kuban State Agrarian University (Scientific KubGAU Journal) [Electronic resource]. – Krasnodar: KubGAU, 2009. – №07(051). Pp. 191-206. – The cipher of the Information Register: 0420900012\0083, IDA [article ID]: 0510907009. – Access mode: http://ej.kubagro.ru/2009/07/pdf/09.pdf , 1 u.p.l.
A systemic cognitive approach to predicting the duration of the postoperative recovery period based on information about the patient obtained by the method of cardio-respiratory synchronism (SDS) (solving problems of forecasting, decision support and research of the subject area) / V.M. Pokrovsky, S.V. Polishchuk, E.V. Fomina, etc. // Polythematic network electronic Scientific Journal of Kuban State Agrarian University (KubGAU Scientific Journal) [Electronic resource]. – Krasnodar: KubGAU, 2009. – №07(051). Pp. 207-247. – The cipher of the Information Register: 0420900012\0082, IDA [article ID]: 0510907010. – Access mode: http://ej.kubagro.ru/2009/07/pdf/10.pdf , 2,562 cu.p.l.
I appreciate the resources shared by R.Eugene Veniaminovich Lutsenko.
However, these references seem to focus on a different aspect of healthcare modeling. I'm still interested in gathering insights specifically about the suitability of Rough Set Theory and Neutrosophic Logic for handling discrete data in machine learning healthcare models.
Please feel free to contribute to this discussion if you have expertise in this area. Thank you
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