New AI-Based Breast Cancer Diagnostic Tool Is Ready

New AI-Based Breast Cancer Diagnostic Tool Is Ready

By Healthcare Tech Outlook | Thursday, December 05, 2019

Healthcare OncologyThe team of researchers from Lancaster University and Airedale NHS Foundation Trust is making use of a specialized chemical analytical technique known as Raman Spectroscopy. Raman analysis helps in providing real-time information on cells and can be applied to test how the cells are behaving, expanding, and developing elsewhere in the body.

FREMONT, CA: In a bid to develop an affordable breast cancer diagnostic tool scientists are employing a new approach to understand the unique chemical fingerprints that distinct between types of breast cancers. These new chemical fingerprints will be used to train Artificial Intelligence (AI) software creating a new tool for rapid and accurate diagnosis of breast cancers.

The team of researchers from Lancaster University and Airedale NHS Foundation Trust is making use of a specialized chemical analytical technique known as Raman Spectroscopy. Raman analysis helps in providing real-time information on cells and can be applied to test how the cells are behaving, expanding, and developing elsewhere in the body. The biopsy is done to classify the molecular structure of different types of breast cancer, along with variations within each cancer cell group. The result of this study is published in the journal Expert Review of Molecular Diagnostics. Upon categorizing the chemical fingerprints of breast cancer cells, and examining how they change, the researchers used the data to train intricate machine learning algorithms to discover four subtypes of cancer.

Furthermore, the algorithms effectively predicted diagnostic patterns for every subtype with a high level of precision ranging between 70 percent and 100 percent. Similar versions of the algorithms have previously been used to recognize other forms of cancers and diseases like skin, oral, and lung cancers.

Experts in the next phase of the examination will look at creating databases of the chemical structures of different types of breast cancer cells and the forms they can take. These databases will be then used to train more AI algorithms using ML, ultimately leading to a new diagnostic tool to sit beside mammograms and MRI scans.

The new algorithms promise to offer data swiftly to assist medical specialists in making a quicker diagnosis. Additionally, the approach will facilitate to determine the nature of the disease at various points in its succession and will become vital in planning the therapeutic procedure of individual patients.

Check out: Top Artificial Intelligence Solution Companies

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