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 in Cancer (early online Aug. 29), 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,” 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.
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.
Currently, when mammograms fall into the suspicious category, a broad range of 3 to 95 percent cancer risk, patients are recommended for biopsies.
Over 1.6 million breast biopsies are performed annually nationwide, and about 20 percent are unnecessarily performed due to false-positive mammogram results of cancer free breasts, estimates the ACS.
The Houston Methodist team hopes this artificial intelligence software will help physicians better define the percent risk requiring a biopsy, equipping doctors with a tool to decrease unnecessary breast biopsies.
Manual review of 50 charts took two clinicians 50-70 hours. AI reviewed 500 charts in a few hours, saving over 500 physician hours.
“Accurate review of this many charts would be practically impossible without AI,” says Wong.
The Latest on: Breast cancer risk prediction
via Google News
The Latest on: Breast cancer risk prediction
- Mammographic Density, Breast Cancer Risk and Risk Predictionon August 23, 2019 at 5:00 pm
Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models ...
- Improving risk prediction for canceron August 7, 2019 at 4:54 am
Using advanced modelling techniques, we looked at how knowledge from nearly 70 genetic variants known to be associated with breast cancer susceptibility ... along with age to predict risk could ...
- Sport-Inspired Risk Model Improves Cancer Risk Predictionon July 16, 2019 at 7:54 am
A sport-inspired dynamic risk assessment model that combines multiple risk ... increasing the C-Statistic from 0.72 to 0.80 (P
- Artificial intelligence expedites breast cancer risk predictionon July 9, 2019 at 5:00 pm
HOUSTON, TX, UNITED STATES - Sep 1, 2016 - Researchers at Houston Methodist have developed an artificial intelligence (AI) software that reliably interprets mammograms, assisting doctors with a quick ...
- This AI Breast Cancer Predictor by MIT is a Game Changeron July 1, 2019 at 9:53 am
Can Deep Learning Save Women at Risk for Breast Cancer? MIT’s Computer Science and Artificial Intelligence Lab has developed a new deep learning-based AI prediction model that can anticipate the ...
- AI model predicts malignant breast cancer as well as humans: IBMon June 27, 2019 at 8:18 am
... that have been correlated with a higher risk of developing breast cancer,” Michal Rosen-Zvi, director of IBM Research, told HCB News. “It generates a per person risk prediction that is based on ...
- Biomarkers of DNA methylation can be a predictor of breast cancer riskon June 27, 2019 at 5:32 am
Biomarkers of DNA methylation, which regulate gene expression, can be a predictor of breast cancer risk, according to a study published ... and then applied the prediction models to a large genetic ...
- MIT AI tool can predict breast cancer up to 5 years early, works equally well for white and black patientson June 26, 2019 at 7:34 am
MIT’s Computer Science and Artificial Intelligence Lab has developed a new deep learning-based AI prediction model that can anticipate the development of breast cancer up to five years ... or received ...
- Breast cancer risk prediction is less accurate for Black patients. Deep learning is changing that.on June 19, 2019 at 2:45 am
Editor's note: A version of this post previously ran on The Reading Room. Health equity is a central strategic goal for many safety-net institutions, and population health investments to address ...
- Comprehensive new breast cancer risk prediction tool “could be a game changer”on January 15, 2019 at 5:22 pm
The system accounts for over 300 genetic risk factors, alongside family history and variables such as weight, alcohol consumption and age at menopause. "This is the first time that anyone has combined ...
via Bing News