Bengaluru AI Breakthrough in Early Cervical Cancer Detection

In a promising development for women's health, researchers in Bengaluru are leveraging artificial intelligence (AI) to detect cervical cancer risk well before traditional diagnostic methods. Lalasa Mukku, a researcher at Christ (Deemed-to-be University), has spearheaded this innovative approach.

The Research

Mukku's work focuses on identifying women at increased risk of cervical cancer by analyzing Cervical Intraepithelial Neoplasia (CIN), which are precancerous cellular changes. These changes often precede cervical cancer, providing a critical window for early intervention.

AI Model Development

Leveraging her expertise in artificial intelligence and data science engineering, Mukku has developed a series of AI-based models. Notably, she holds patents for an AI model capable of predicting cancer risk up to five years before tumor formation.

The model, known as CMT-CNN, combines:

• Colposcopy examination images

• Clinical patient data

This approach achieves a classification accuracy of 92.3% in identifying Cervical Intraepithelial Neoplasia (CIN).

Addressing Challenges

One of the major challenges in AI-assisted cervical cancer detection is accurately interpreting colposcopy images. Bright reflections caused by moisture can resemble the white lesions associated with precancerous changes, potentially misleading AI systems.

To address this issue, Mukku developed a technique that:

• Removes bright reflections from colposcopy images.

• Isolates the cervical region for more accurate analysis.

• Improves the reliability of AI-based diagnosis.

This technique was published in the journal Multimedia Tools and Applications.

Advanced Techniques

In 2025, Mukku presented a research paper at an IEEE conference introducing a Quantum Convolutional Neural Network (QCNN) architecture for medical image analysis.

The model was evaluated using publicly available cervical cancer screening datasets and achieved an impressive:

• Overall Accuracy: 98.6%

These advancements demonstrate the growing potential of AI to improve diagnostic accuracy and support clinicians in detecting cervical abnormalities at an earlier stage.

Implications and Future Prospects

Cervical cancer remains one of the leading causes of cancer-related deaths among women worldwide, particularly in low- and middle-income countries where access to screening and specialist care is limited.

Early diagnosis significantly improves treatment outcomes and survival rates.

Although Mukku's technology is currently in the research phase and requires extensive clinical validation, its successful implementation could:

• Revolutionize cervical cancer screening.

• Enable earlier and more accurate diagnosis.

• Reduce dependence on specialist interpretation.

• Improve access to quality healthcare in resource-limited settings.

• Save lives through timely medical intervention.

The integration of artificial intelligence into medical diagnostics is transforming healthcare by enabling faster and more accurate disease detection.

Lalasa Mukku's research represents a significant advancement in the early detection of cervical cancer. By combining AI, image processing, and clinical data analysis, her work offers the potential to identify cancer risk years before tumors develop.

As these technologies continue to evolve and undergo clinical validation, they hold the promise of improving screening programs, enhancing patient outcomes, and ultimately reducing the global burden of cervical cancer.