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Virtual Myelography: a machine learning method for differentiating cerebrospinal fluid from spinal cord tissue in lumbar spine CT exam
TS-075230 — Problem Computed tomography (CT) is commonly used for its widespread availability, rapid acquisition times, and depiction of fine bony detail, but it struggles to differentiate spinal cord tissue from cerebrospinal fluid (CSF) due to their similar mass densities. Magnetic resonance imaging (MRI) of…
  • College: Office of Health Sciences
  • Inventors: Nguyen, Xuan; Dikici, Engin; Prevedello, Luciano
  • Licensing Officer: Hampton, Andrew

System and method for prediction of artificial intelligence model generalizability for unseen data
TS-075229 — Problem Artificial intelligence models often perform well during development but show unpredictable drops in accuracy and reliability when deployed on data that differ from their training sets. In high‑risk settings such as clinical care, these shifts can arise from changes in hardware, protocols…
  • College: College of Medicine (COM)
  • Inventors: Dikici, Engin; Nguyen, Xuan; Prevedello, Luciano
  • Licensing Officer: Hampton, Andrew

TL-iGeneCombo: Transfer Learning for Individual Sample Specific Gene Combination Effect Prediction and Selection in Cancer Cells
TS-075184 — Problem Synthetic lethality (SL) is defined as a gene combination effect (GCE) of two genes where loss-of-function of both genes, rather than one, causes cell death. While carrying strong therapeutic potential in the treatment of cancer, SL interactions are context specific and sparse, thereby limi…
  • College: College of Medicine (COM)
  • Inventors: Li, Lang; Gökbağ, Birkan
  • Licensing Officer: Hampton, Andrew

A novel machine learning model for prediction of ICI responsive patients based on ICI pharmacokinetics
TS-075183 — Problem Current eligibility biomarkers for Immune checkpoint inhibitors (ICIs) poorly predict patient’s response. Drug clearance, both at baseline and over time, is a stronger predictor of ICI effectiveness, however the current non-linear mixed effects modeling (NLME) approach for estimating …
  • College: College of Pharmacy (COP)
  • Inventors: Phelps, Mitchell "Mitch"; Adeluola, Adeoluwa; Coss, Christopher; Kim, Kyeongmin; Mo, Xiaokui "Molly"; Owen, Dwight
  • Licensing Officer: Hampton, Andrew

EmitGCL: Prediction of Future Metastasis based on Graph Contrastive Learning
TS-075168 — Problem Metastasis is the primary driver of cancer-related deaths, yet accurately predicting its onset is a major clinical challenge. Current diagnostic tools often fail to detect occult metastatic cells and metastatic precursor cells, resulting in either overdiagnosis, with unnecessary treatments,…
  • College: College of Medicine (COM)
  • Inventors: Ma, Qin; Wang, Xiaoying
  • Licensing Officer: Hampton, Andrew

A Regularized Conditional GAN for Posterior Sampling in Inverse Problems
TS-063238 — A novel regularization technique applicable for medical imaging applications that leverages conditional generative adversarial networks (cGANs) to generate reconstructed images in significantly shorter timeframes. The Need Several techniques are used for image reconstruction in the medical aren…
  • College: College of Engineering (COE)
  • Inventors: Bendel, Matthew; Ahmad, Rizwan; Schniter, Philip "Phil"
  • Licensing Officer: Hampton, Andrew

Hybrid Collaborative Filtering Methods for Recommending Search Terms to Clinicians
TS-063237 — Electronic Health Records (EHR) are used in over 88% of all US medical clinics to improve care and streamline data. In addition, they enable sharing of data to multiple providers dealing with the same patient, thereby enhancing efficiency and care. The Need In the last decade, medical practices…
  • College: College of Medicine (COM)
  • Inventors: Ning, Xia; Peng, Bo; Ren, Zhiyun
  • Licensing Officer: Hampton, Andrew

Patient Access Prioritization Score
TS-063212 — When a patient demonstrates signs of imminent clinical deterioration, it is essential to immediately assess and treat the patient to prevent intensive care unit transfer, cardiac arrest, or death. These tasks often include transferring the patient to other facilities with optimal capabilities. T…
  • College: College of Medicine (COM)
  • Inventors: Reinbolt, Raquel; Cohn, David
  • Licensing Officer: Hampton, Andrew

Force Plate Surface Calibration Device
TS-063194 — The Need In the medical and healthcare arena, force plate technology is frequently relied upon for evaluating a patient’s ability to meet normal human standards when performing different physical activities and determining the presence of limitations in mechanistic-type behaviors due to age, …
  • College: College of Medicine (COM)
  • Inventors: Onate, James; Caccese, Jaclyn; Edwards, Nathan; Hagen, Joshua; Kang, Yun Seok
  • Licensing Officer: Hampton, Andrew

Convolutional Neural Network to Assess Phayngeal and Laryngeal Pathology and Function on Nasopharyngolaryngoscopy
TS-063154 — Worldwide, 686,000 new head and neck (H&N) cancers are diagnosed yearly, and 375,000 people will die annually. Human papillomavirus (HPV) is responsible for an increasing subset of H&N malignancies called oropharyngeal squamous cell carcinomas (OPSCC). Although it has a better prognosis than…
  • College: College of Engineering (COE)
  • Inventors: Krening, Samantha; Gifford, Ryan; Jhawar, Sachin; VanKoevering, Kyle
  • Licensing Officer: Hampton, Andrew

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