Artificial Intelligence Expedites Breast Cancer Risk Prediction

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Researchers at Houston Methodist have developed an artificial intelligence (AI) software that reliably interprets mammograms, assisting doctors with a quick and accurate prediction of breast cancer risk. According to a new study published online Aug. 29 in Cancer, the computer software intuitively translates patient charts into diagnostic information at 30 times human speed and with 99 percent accuracy. "This software intelligently reviews millions of records in a short amount of time, enabling us to determine breast cancer risk more efficiently using a patient's mammogram. This has the potential to decrease unnecessary biopsies," said Stephen T. Wong, Ph.D., P.E., chair of the Department of Systems Medicine and Bioengineering at Houston Methodist Research Institute. The team led by Wong and Jenny C. Chang, M.D., director of the Houston Methodist Cancer Center used the AI software to evaluate mammograms and pathology reports of 500 breast cancer patients.


Researchers use artificial intelligence to better detect breast cancer

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Health researchers at Houston Methodist Hospital have developed an artificial intelligence application they cite as being 30 times faster than human doctors and 99% accurate in reading and interpreting mammograms. Houston Methodist used the artificial intelligence software to evaluate mammograms and pathology reports of 500 breast cancer patients. The software scanned patient charts, collected diagnostic features and correlated mammogram findings for breast cancer. Clinicians then used the results, like the expression of tumor proteins, to accurately predict each patient's probability of a breast cancer diagnosis, the hospital says. In the U.S., 12.1 million mammograms are performed annually, according to the Centers for Disease Control and Prevention.


Artificial intelligence expedites breast cancer risk prediction

#artificialintelligence

"This software intelligently reviews millions of records in a short amount of time, enabling us to determine breast cancer risk more efficiently using a patient's mammogram. This has the potential to decrease unnecessary biopsies," says Stephen T. Wong, Ph.D., P.E., chair of the Department of Systems Medicine and Bioengineering at Houston Methodist Research Institute. The team led by Wong and Jenny C. Chang, M.D., director of the Houston Methodist Cancer Center used the AI software to evaluate mammograms and pathology reports of 500 breast cancer patients. The software scanned patient charts, collected diagnostic features and correlated mammogram findings with breast cancer subtype. Clinicians used results, like the expression of tumor proteins, to accurately predict each patient's probability of breast cancer diagnosis.


Artificial Intelligence Is Helping Doctors Find Breast Cancer Risk 30 Times Faster

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Sudanese radiologist Dr Hania Fadl speaks with reporters in 2015 at the Khartoum Breast Care Centre (KBCC), which she opened in 2010 and equipped with screening and anesthetic equipment despite financial advisers' warnings to abandon the project. The mammogram is one of medical science's best tools for detecting breast cancer, but when the typically painful test reveals a potential problem, women frequently undergo breast biopsies for a closer look--a practice that's all too often unnecessary, according to a group of artificial intelligence (AI) researchers, and which doctors may be able to significantly reduce thanks to a little insight from computers. Announced today, researchers from Houston Methodist have developed AI software that can interpret mammogram results a full 30 times quicker than doctors and with 99 percent accuracy, according to the team's recent study. Published in the journal Cancer, the study found that the software was able to intuitively translate patient charts into diagnostic information for human review at top speeds, which offers doctors reliable and seriously time-saving support when it comes to assessing patient cancer risk and the need for further tests. To determine the software's effectiveness for assessing breast cancer risk, the team provided its AI with mammogram and pathology reports of 500 breast cancer patients, as well as information on diagnostic features and correlated mammogram findings for breast cancer subtypes.


Artificial Intelligence Expedites Breast Cancer Risk Prediction - DATAVERSITY

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The release goes on, "The team led by Wong and Jenny C. Chang, M.D., director of the Houston Methodist Cancer Center used the AI software to evaluate mammograms and pathology reports of 500 breast cancer patients. The software scanned patient charts, collected diagnostic features and correlated mammogram findings with breast cancer subtype. Clinicians used results, like the expression of tumor proteins, to accurately predict each patient's probability of breast cancer diagnosis. In the United States, 12.1 million mammograms are performed annually, according to the Centers for Disease Control and Prevention (CDC). Fifty percent yield false positive results, according to the American Cancer Society (ACS), resulting in one in every two healthy women told they have cancer.