The Princeton (N.J.) University Department of Operations Research and Financial Engineering is partnering with ODH, a data science company focused on health technology, to research artificial intelligence and machine learning techniques to help healthcare providers evaluate the mental and social health factors affecting their patients.
In healthcare, machine learning can help sift through large troves of data to make predictions about future outcomes. As part of the collaboration, ODH's and ORFE's data scientists, researchers and mathematicians will develop data-driven techniques to identify patterns within medical information.
The goal is to prioritize secondary factors of a condition are often overlooked — such as alcohol use for liver failure patients — to empower care teams' decision making processes when determining which treatment is best fit for each patient. The technique also aims to inform the most effective interventions, like substance abuse treatment programs, medication adherence education or even medical transportation.
"The healthcare industry is just starting to come to grips with the potential of machine learning," said Michael Jarjour, president and CEO of ODH. "We see a huge opportunity to push the boundaries by improving machine learning methodologies so that we can better identify underlying behavioral and social factors contributing to individuals' health conditions and target interventions accordingly. We are thrilled to collaborate with Princeton on this venture. The University's expertise in artificial intelligence and data science will be a key driver of our research."
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