Arindam Ray

Evaluation of the Diagnostic Accuracy of Cervical Cell Morphologies from Android Device-Captured Cytopathological Microscopic Images through Artificial Intelligence in Mainly Rural or Resource-Constraint Areas of India

This study aims at develop and evaluate an artificial intelligence programming software, an integrated system that automatically detects and classifies cells from microscopic Pap smear slide images taken on Android phones or tabs to diagnose the cervical cell morphology in a time-efficient and cost-effective manner. This study presents an integrated system designed to automatically detect and classify cells in Pap smear slide images, differentiating cellular morphologies. The system leverages three deep learning (DL) and one machine learning (ML) models, each tailored to specific tasks in the image analysis pipeline. The analysis of 292 hospital in-house microscopic Pap smear images was conducted from July 2023 to December 2024 at CliniMed LifeSciences, Kolkata, India. The following article describes the datasets used, the training procedures and the performance metrics for each model.  Results: Pap smear images have been validated and standardized by using SipakMed, Herlev (public datasets) and hospital in-house data. A total of 292 in-house Pap smear images have been analysed through the newly developed AI software. Standardization and validation include an Intersection-over-Union score of cell-nuclei boundary extraction model of 71.14%, the accuracy of cell classification model and morphological feature based ML model are 99.213% and 91.23% respectively. The custom AI model could successfully classify 98.09% and 80.49%  of normal and abnormal cells in hospital in-house samples respectively. Also a significant meaningful correlation is observed between biopsy (gold standard) and AI reports. AI offers a lot of promise for diagnosing cervical cancer, and its uses in cervical cytology screening are particularly well-established. Manual screening of cervical cytology smears is a time-tested method, but AI is set to revolutionize the process by improving outreach, availability, accuracy and economy. A total of 292 hospital in-house Pap smear images have been validated and examined in this study with significant accuracy percentages between AI and expert eyes.

Google Trends for the Human Papillomavirus Vaccine in India From 2010 to 2024: Infodemiological Study

Abstract Background Human papillomavirus (HPV) is a leading cause of cervical cancer. It has a substantial impact on global public health, with low- and middle-income countries, including India, facing the highest burden. In 2022, India reported 127,526 new cases and 79,906 deaths due to cervical cancer, projected to increase by 61% by 2040. Although the National Technical Advisory Group on Immunization recommended the HPV vaccine for cervical cancer prevention, it is yet to be a part of India’s universal immunization program. Objective This study aims to examine online interest in the HPV vaccine in India from January 2010 to April 2024 using Google Trends. Methods A cross-sectional analysis of Google Trends data was performed, using the relative search volume to track interest on a scale of 0‐100. Trends were analyzed annually using 1-way ANOVA and joinpoint regression to identify significant changes in search behavior related to public health events. Statistical significance was set at P<.05. Results The average annual growth in HPV vaccine-related searches was 13.7% (95% CI 7.9%‐19.1%), with the highest relative search volume in 2024 (49.5) and the lowest in 2017 (3.38). Spikes in search interest aligned with key events like the 2018 National Technical Advisory Group on Immunization recommendation and the 2022 launch of the indigenous HPV vaccine. The results highlight online search data’s value in tracking public interest, which fluctuates in response to health policy changes or developments on social media. In India, targeted digital strategies will be vital for addressing vaccine hesitancy and increasing HPV vaccine uptake. Conclusions Google Trends data can inform public health strategies by identifying periods of high interest, aiding in the promotion of HPV vaccination in India.