A researcher from CHRIST (Deemed to be University), Bengaluru, has developed a series of artificial intelligence (AI) based predictive models designed to identify women at elevated risk of cervical cancer years before clinical diagnosis, potentially enabling earlier intervention and improving patient outcomes.

The research, led by Lalasa Mukku, focuses on analysing Cervical Intraepithelial Neoplasia (CIN) precancerous changes in the cells of the cervix that can progress to cervical cancer if left untreated. By leveraging machine learning algorithms and clinical data analysis, the AI models aim to detect high risk patterns and support earlier identification of women who may require closer monitoring and preventive treatment.

According to the researcher, the models were developed to address one of the key challenges in cervical cancer management: identifying patients who are most likely to progress from precancerous lesions to invasive cancer. The AI driven approach integrates multiple clinical and pathological parameters to improve risk prediction and assist healthcare professionals in making timely decisions.

Cervical cancer remains one of the most common cancers affecting women globally. According to the World Health Organization (WHO), approximately 660,000 new cases of cervical cancer and around 350,000 deaths were reported worldwide in 2022. In India, cervical cancer is the second most common cancer among women, accounting for an estimated over 120,000 new cases and nearly 80,000 deaths annually, according to data from the Indian Council of Medical Research (ICMR) and global cancer observatories.

Experts note that early detection and treatment of cervical precancerous lesions can prevent the majority of cervical cancer cases. Artificial intelligence is increasingly being explored in oncology to improve screening accuracy, identify high risk individuals and support personalized healthcare interventions.

The research highlights the growing role of AI in preventive healthcare and cancer diagnostics, particularly in resource constrained settings where access to specialist care and advanced screening programmes remains limited. By enabling earlier risk assessment, AI based predictive tools could help strengthen cervical cancer prevention strategies and improve long term health outcomes.

While further clinical validation and large scale studies are required before widespread implementation, researchers believe such technologies have the potential to complement existing screening methods and support India’s efforts to reduce the burden of cervical cancer through early detection and targeted interventions.

The study adds to the expanding body of research exploring the use of artificial intelligence in precision medicine and reinforces the importance of integrating advanced technologies into cancer prevention and public health programmes.