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Using A.I. to Detect Lung Cancer gets an A!

Reporter: Irina Robu, PhD

3.3.19

3.3.19   Using A.I. to Detect Lung Cancer gets an A!, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

Google researchers hypothesized that computers are as good or better than doctors at detecting tiny lung cancers on CT scans, since CT scan combines data from several X-rays to produce a detailed image of a structure inside the body. CT scans produce 2-dimensional images of a slice of the body and the data can also be used to construct 3-D images.

However, the technology published in Nature Medicine offers input in the future of artificial intelligence in medicine. By feeding vast amounts of data from medical imaging into systems called artificial neural networks, scientists can teach computers to identify patterns linked to a specific condition, like pneumonia, cancer or a wrist fracture that would be hard for a person to see. The system trails an algorithm, or set of instructions, and learns as it goes. The more data it receives, the better it becomes at interpretation.

The process, known as deep learning enables computers to identify objects and understand speech but it also created systems to help pathologists read microscope slides to diagnose cancer, and to help ophthalmologists detect eye disease in people with diabetes. In their recent study, the scientist used artificial intelligence to CT scans used to screen people for lung cancer, which caused 160,000 deaths in the United States last year, and 1.7 million worldwide. The scans are recommended for people at high risk because of a long history of smoking.

Screening studies showed that it can reduce the risk of dying from lung cancer and can also identify spots that might later become cancer, so that radiologists can categorize patients into risk groups and decide whether they need biopsies or more frequent follow-up scans to keep track of the suspect regions.

However, the test has errors. It can miss tumors or mistake benign spots for malignancies and shove patients into invasive, risky procedures like lung biopsies or surgery.

SOURCE

https://www.nytimes.com/2019/05/20/health/cancer-artificial-intelligence-ct-scans.html

Other related articles were published in this Online Scientific Open Access Journal including the following:

Multiple Barriers Identified Which May Hamper Use of Artificial Intelligence in the Clinical Setting

AI System Used to Detect Lung Cancer

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