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Artificial Intelligence and Machine Learning Research

From molecules to populations, data comes in all sizes. The secrets within could unlock unprecedented health care advances—from better treatments to safer practices to faster response times. With the help of our partners, we can continue transforming this data to power human health for many years to come.

Artificial Intelligence and Machine Learning Research

Experts at the School of Biomedical Informatics are developing applications to collect and analyze massive amounts of data to power discoveries that improve health care delivery and help prevent disease. In doing so, they are expanding the frontiers of patient safety, health care quality, artificial intelligence, telemedicine, data security, drug discovery, and precision medicine.

We are the only academic biomedical informatics program in Texas and one of the world’s largest programs of our kind, and our faculty boast expertise in diverse backgrounds ranging from computer science to nursing to mechanical engineering. The multidisciplinary nature of our school, fueled by collaborations across the six schools of UTHealth and organizations throughout the Texas Medical Center, uniquely positions us to lead the growing field of biomedical informatics.

Today, our research is mining the mysteries encrypted in numbers; it’s transcribing the algorithms that bring machines to life; it’s uncovering the genetic basis of cancer and chronic diseases. Tomorrow, our work will become the treatments and cures that lead to longer, healthier lives for all.

We stand at the intersection of technological advancement and technical expertise, prepared to drive the discoveries that will revolutionize the way we think about—and deliver—health care. Your support of Many Faces. One Mission. can help us continue pursuing big data solutions that lead to lifesaving discoveries.

  • I am honored to hold a professorship at UTHealth School of Biomedical Informatics. This endowment has allowed me to publish my COVID-19-related research, supported our recent datathon, and covered the cost to access a database that will advance research on Alzheimer's disease and related dementias. I am grateful for all the ways this professorship is making a positive impact on the future of health care.

    Xiaoqian Jiang, PhD

    Christopher Sarofim Family Professor in Biomedical Informatics and Bioengineering

    Professor

    UTHealth School of Biomedical Informatics

  • Electronic Health Records

    We are analyzing hospital patients’ electronic health records to predict sepsis, the most common cause of death among hospital patients in the United States. When risk is identified, clinicians and practitioners are alerted so they can intervene in real-time and improve the chance of survival.

    Additionally, we are mining data from electronic health records in order to discover new functions for existing drugs already approved by the Food and Drug Administration. This could lead to a reduction in the amount of time and resources required to bring treatments to patients. In turn, this frees these resources to be used for other pressing health concerns facing our community.

  • Artificial Intelligence for Quicker Diagnoses

    We are applying artificial intelligence to detect early warning signs of Parkinson’s disease. Through special algorithms, we can measure people’s typing patterns, including the speed at which they press and release keys. Because people with Parkinson’s have a different typing pattern, this could one day aid in diagnosis, early intervention, and a slowing of symptoms.

    We are also developing tools that will be used to make a nonintrusive diagnosis of COVID-19 and to evaluate cardiovascular outcomes of patients who survive the virus.