The National Institutes of Health (NIH) AI/ML Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Program has awarded a grant to MedCognetics to research unbiased AI for breast cancer detection. Photo credit: Getty Images.
January 26, 2023 — MedCognetics, Inc., an Artificial Intelligence (AI) software firm, announced that it has been awarded a $750,000 grant from the National Institutes of Health (NIH) to research unbiased AI for breast cancer detection. The research grant is from the NIH’s Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity Program, or AIM-AHEAD program.
The MedCognetics, Inc. statement noted the company has developed an unbiased advanced imaging algorithm that leverages AI and Machine Learning (ML) to detect the earliest manifestations of cancer in all ethnicities. The company, founded in 2019, is a subaward from the University of North Texas Health Science Center (HSC) at Fort Worth, TX.
“One of the main reasons for establishing the AIM-AHEAD grant program is to address health inequities and disparities,” said Dr. Jamboor Vishwanatha, Regents Professor at the University of North Texas, Health Science Center at Fort Worth, TX and, the principal investigator of the AIM-AHEAD coordinating center. “We selected MedCognetics as one of our grant recipients because of its focus on developing technology aimed at addressing the data bias of historically ignored populations, especially regarding breast health and imaging. We are encouraged by the company’s initial success and look forward to collaborating towards the mutual goal of improved healthcare, prevention, diagnoses and overall better outcomes.”
MedCognetics was founded on research that originated from the Quality of Life Technology Laboratory at The University of Texas at Dallas. Its partnership with the University of Texas Southwestern Medical Center (UTSW) provided the clinical data that assisted in the validation of its unbiased AI algorithm. Founded in 2019, and based in Dallas, TX, the company provides an advanced AI software platform which integrates into radiology workflow. In addition, the AI algorithm is trained on a diverse global patient dataset to mitigate data biasing.
The AIM-AHEAD program was created to close the gaps in the AI/ML field, which currently lacks diversity in its researchers and in data, including electronic health records (EHRs), according to MedCognetics. It noted that these gaps pose a risk of creating and continuing harmful biases in how AI/ML is used, how algorithms are developed and trained, and how findings are interpreted. This objective dovetails well with the company’s mission to leverage technology to improve efficiencies and reliability in the field of medical imaging. In the case of mammograms, its product reduces the amount of time a radiologist needs to review a case, by 30 to 50 percent, which directly translates into more saved lives. This is especially vital in underserved communities and areas of the world where medicine and diagnostic imaging are scarce.
“This is a prestigious honor and the recognition validates MedCognetics’ mission to provide unbiased AI-enabled healthcare services around the world,” said Debasish Nag, Chief Executive Officer, MedCognetics, Inc. He added, “The future of AI in healthcare is providing unbiased services and improving cost and efficiencies in medical facilities. We are developing the technology that will unequivocally reduce burnout in the radiology community and in turn, improve patient outcomes across diverse populations. This NIH grant will play an important role in future product development as well as helping us further expand our global market penetration.” AI in medical imaging provides both the scale and performance to address gap
In December, 2022, as reported by ITN, MedCognetics announced it received U.S Food and Drug Administration (FDA) 510(k) clearance for its AI enabled software for breast cancer screening, QmTRIAGE. The company provides an advanced AI software platform with the goal of reducing time and cost of imaging, and improving outcomes across diverse patient populations, according to a company statement. The platform integrates into radiology workflow and is also training its AI algorithm on a diverse global patient database to mitigate data biasing. MedCognetics has teamed up with the University of Texas at Dallas and University of Texas Southwestern Medical Center (UTSW) in Dallas, Texas to help achieve its two-fold goals: to help educate AIs to create less bias, and to help reduce the case load of overworked radiologists currently experiencing a high burnout rate.
For more information:
MedCognetics: www.medcognetics.com
NIH - https://www.nih.gov/
AIM-AHEAD: https://datascience.nih.gov/artificial-intelligence/aim-ahead
Quality of Life Technology Laboratory at UT Dallas: https://ecs.utdallas.edu/research/researchlabs/QoLT/index.html
University of Texas Southwestern Medical Center: https://www.utsouthwestern.edu/
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