Explainable Artificial Intelligence based Detection and Early Diagnosis of Polycystic Ovaries Syndrome using Optimized Hybrid Deep Learning Technique

Author:

Amol Bajirao Kale ,Preeti Baban Lokhande ,Ramshi Purushottam Pathak ,Shivaji Arun Shinde

Abstract

Customer satisfaction is directly related with the customer retention. The marketer should understand the needs and expectations of his customers for making an effective marketing strategy. Measurement of customer satisfaction enables the firm to deliver maximum value to the customer. Delivering the values to customers facilitates in the creation of loyal customers. The main thrust area among these challenges is the dissatisfaction of customers. The main reason behind this dissatisfaction is the expectations of modern customers who are tech-savvy guys. The digitalization in the area of business is likely to continue in future which will create more challenges before the marketers. Hence customer satisfaction cannot be ignored in the modern digital age

Publisher

Naksh Solutions

Reference14 articles.

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2. Tiwari, S., Kane, L., Koundal, D., Jain, A., Alhudhaif, A., Polat, K., ... &Althubiti, S. A. (2022). SPOSDS: A smart Polycystic Ovary Syndrome diagnostic system using machine learning. Expert Systems with Applications, 203, 117592.

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4. Al Wattar, B. H., Fisher, M., Bevington, L., Talaulikar, V., Davies, M., Conway, G., &Yasmin, E. (2021). Clinical practice guidelines on the diagnosis and management of polycystic ovary syndrome: a systematic review and quality assessment study. The Journal of Clinical Endocrinology & Metabolism, 106(8), 2436-2446.

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