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DTSTART;TZID=UTC:20260305T120000
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SUMMARY:Applied Statistics and Data Science Seminar on Thursday 05 March 2026
DESCRIPTION:Title: FertiMeter: A Data-Driven Innovation to Address the Reproductive Health Crisis of Polycystic\nOvary Syndrome \nVenue\, date and time: ISRT\, 5 March 2026\, 12:15 pm \nSpeaker: K. M. Tanvir\, Lecturer\, ISRT\, University of Dhaka \nAbstract: \nBackground:\nPolycystic ovary syndrome (PCOS) affects around 12.5% of women in Bangladesh and is a major cause of infertility and pregnancy complications. Although early detection can help manage symptoms and reduce risks\, nearly 70% of women remain undiagnosed due to limited awareness and inadequate access\nto medical care.\nObjectives:\nThis study aims to develop a data-driven machine learning model that predicts the likelihood of PCOS using non-clinical features and to integrate it into a mobile application\, FertiMeter.\nMethods:\nA total of 546 participants\, including 273 women diagnosed with PCOS and 273 without PCOS\, were enrolled in the study. The CatBoost machine learning algorithm was applied to develop a predictive model for PCOS status and the model was incorporated into the FertiMeter mobile application.\nKey Findings:\nUsing eight SHAP-selected non-clinical features\, the CatBoost model achieved an average cross-validated accuracy of 86%.\nConclusions:\nApproximately 6.7 million women in Bangladesh who remain undiagnosed with PCOS can use FertiMeter mobile application to assess their likelihood of having the condition free of cost.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-23-february-2026/
CATEGORIES:seminar
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