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Lou Oberndorf establishes the Oberndorf Clinical Artificial Intelligence Scholars Award

Lou Oberndorf establishes the Oberndorf Clinical Artificial Intelligence Scholars Award

Last year, OEI Chairman and CEO, Lou Oberndorf established the Oberndorf Clinical Artificial Intelligence Scholars Award at the University of Florida, the college’s first-ever AI-focused award. The award creates an endowed fund that will be disbursed in perpetuity as a monetary prize for second-, third- or fourth-year medical students working on AI-focused team research projects.

The award is an example of the university’s commitment to making AI the centerpiece of a long-term initiative to support leading-edge research efforts and a transformative approach to its curriculum.

“When I considered the potential power of AI that could be harnessed for health care and the innovative research happening in our academic health center at UF, I saw an opportunity to advance the reputation and position of the university and to do good at the same time,” Oberndorf said. “The real excitement came when we heard about the energy building among the medical students and the teams that were forming. That’s when the idea came to me — let’s do something to recognize them, reward them, motivate them to really do some exciting things.”

The gift was announced at the 13th annual UF College of Medicine Celebration of Research in February of 2023, a two-day event that highlights pioneering scholarship across the College of Medicine.

In its inaugural year, six students with creative and impactful ideas were selected as recipients of the Oberndorf Clinical Artificial Intelligence Scholarship Award. The students and their projects are:

Justin Daniels — Development of an AI Model for Ultrasound-Based Detection of the Stomach and its Content

Danielle Snyder — Precision in Prediction: Harnessing Machine Learning for an Innovative Endometriosis Prediction Model

Maisha Akbar — AI for Global Health: Developing AI for Cervical Cancer Detection in Haitian Women of African Descent.

Sean Kwak — Development of an AI Model to Automate the Segmentation of Key Dermatohistologic Structures.

Gabriel Flambert — Using AI for Equitable Oncology: A Machine Learning Model to Determine Hormone Receptor Status in Breast Cancer Among Women of African Descent in Haiti.

Daniel Stribling — Individualized Deep Neural Network oncomiR Target Prediction for Personalized Cancer Therapy.

Details

  • Baltimore, MD, USA
  • Operative Experience Inc.