Sujatha, V. and Santhi, S. (2024) Prediction of Psychological Issues Relating to Infertility Women under ANFIS. In: 2024 2nd International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT), Faridabad, India.
Full text not available from this repository. (Request a copy)Abstract
Many women find that infertility is a huge psychological barrier influencing their general state of mind and mental health. Psychological issues and infertility can interact in a complex manner that usually results in emotional turbulence, anxiety, and depression. Over 15% of couples globally suffer from infertility, which has major psychological implications for women. Good mental health care and intervention depend on an awareness of and prognosis for psychological disorders in infertile women. Problem Statement: The problem of conventional methods of assessing psychological distress in infertile women are often lack accuracy and adaptability. This work addresses the desire for a more accurate predictive model by describing complex, nonlinear relationships between variables by mixing neural networks with fuzzy logic. Examined a dataset of demographic information from a cohort of women undergoing reproductive therapies, psychological tests, and stress related to infertility using ANFIS (Adaptive Neuro-Fuzzy Inference System). Findings: The model was trained and evaluated using this data to predict psychological stress levels depending on identified stressors and personal factors. With a root mean square error (RMSE) of 0.12 and a correlation value of 0.89 the ANFIS model presented a clear improvement in prediction accuracy over conventional statistical methods. These results reveal that ANFIS can fairly depict the nuances of psychological issues in infertile women and offer perceptive study for customized mental health support.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Subjects: | Mathematics > Probability |
Domains: | Mathematics |
Depositing User: | Mr IR Admin |
Date Deposited: | 28 Aug 2025 09:28 |
Last Modified: | 28 Aug 2025 09:28 |
URI: | https://ir.vistas.ac.in/id/eprint/10950 |