AI Bio-Imaging Bank for Cancer Detection
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Source– This post is based on the article “How AI can help detect cancer and why India’s biggest cancer treatment hospital is utilizing it” published in “The Indian Express” on 7th January 2024.

Why in the News?

Mumbai’s Tata Memorial Hospital (TMH), India’s largest cancer hospital, embraces AI with a ‘Bio-Imaging Bank’ for early stage cancer detection.

What is Bio-Imaging Bank?

1) It is a comprehensive repository containing radiology and pathology images with clinical details, outcome data, treatment specifics, and additional metadata.

2) This resource is strategically crafted for training, validation, and rigorous testing of AI algorithms.

3) The project uses deep learning to develop a cancer specific tailored algorithm for early detection, incorporating data from 60,000 patients.

4) Initially the project is dedicated to head and neck cancers as well as lung cancers, with a goal of having at least 1000 patients for each cancer type.

5) It focuses on medical tasks like screening for lymph node metastases, nucleus segmentation, classification, and predicting biomarkers (e.g., HPV in oropharyngeal, EGFR in lung cancer), as well as therapy response prediction.

5) Funded by– The Department of Biotechnology, in collaboration with IIT-Bombay, RGCIRC-New Delhi, AIIMS-New Delhi, and PGIMER-Chandigarh.

How does AI help in early cancer detection?

1) It analyzes radiological and pathological images, learning from extensive datasets to identify unique features associated with different cancers, enabling early detection of tissue changes and potential malignancies.

2) The teams at TMH segments and annotates images, correlating them with biopsy results, histopathology reports, and genomic sequences to develop algorithms.

What is its Significance?

1) The AI aids in early diagnosis which has proven to be 98 percent correct after doctors cross-check.

2) AI’s potential lies in tailoring treatment approaches based on diverse patient profiles, and thus optimising therapy outcomes.

3) It reduces radiation exposure for pediatric patients undergoing CT scans by 40 %.

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