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STAR-Echo: Software to Predict Cardiovascular Disease in Chronic Kidney Disease Patients
Application A novel software for prognosis of MACE in chronic kidney disease patients using spatiotemporal analysis and transformer-based radiomics models. Key Benefits Unique interpretable features – identifies novel features based on longitudinal changes in LVW shape (perimeter & sphericity) and texture (intensity variations) over a...
Published: 4/11/2024       Contributor(s): Rohan Dhamdhere, Sadeer Al-Kindi, Gourav Modanwal, Anant Madabhushi
Automated Software to Quantify Breast Arterial Calcifications from Mammograms
Application Deep learning software for the automated detection and quantification of breast arterial calcifications in screening mammograms. Key Benefits Optimized image segmentation accuracy with improved generalizability towards mammograms with and without BAC presence. Robust ability to quantitate narrow or heavy BAC and/or partial depositions...
Published: 5/21/2024       Contributor(s): Hari Trivedi, Imon Banerjee, William Charles O'Neill, Aisha Urooj Khan
Artificial Neural Network for Prediction of Clinical Outcomes
Application A machine learning model to predict the need for ventriculoperitoneal shunt after posterior fossa tumor resection. Key Benefits Highly accurate prediction of post-surgical complications. Reducing healthcare costs by predicting prognoses and increasing efficiency of post-surgical treatment. Market Summary Neurosurgical procedures...
Published: 11/27/2023       Contributor(s): Kimberly Hoang, Ali Alawieh, David Bray
System for Assessing Health Severity and Predicting Readmissions
Application A smartphone-based system for monitoring patients to identify and prevent severe cardiac events. Key Benefits A remote monitoring system that uses smartphone data to accurately predict a user’s risk for a severe cardiac event (e.g., heart attack). Tracks the user's movement, location, and physical activity to calculate FDA-accepted...
Published: 4/23/2024       Contributor(s): Gari Clifford, Amit J. Shah, Ayse Cakmak, Erik Reinertsen
Wearable Device for the Early Detection and Monitoring of Atrial Fibrillation
Application A wearable device that enables long-term, continuous monitoring and screening for AFib by monitoring light signals on the skin. Key Benefits Inexpensive and compatible with existing wearable products by leading technology companies from Apple and others. Novel algorithms suppress irrelevant signals originating from a user's constant...
Published: 5/21/2024       Contributor(s): Shamim Nemati, Supreeth Shashikumar, Amit J. Shah, Qiao Li, Gari Clifford
Latent Variable Modeling for Developing Neuroprosthetic Devices
Application A high-performing neural decoder that reconstructs spiking data from local field potentials to analyze neural recordings for developing neuro-prosthetic devices. Key Benefits Capable of augmenting local field potential to overcome perturbations in data. Improved decoding stability with high accuracy. Potential to lead to the development...
Published: 5/21/2024       Contributor(s): Brianna Karpowicz, Chethan Pandarinath, Yahia Ali, Marc Slutzky, Robert Flint, Bareesh Bhaduri
Monitoring System for Tracking Behavior and Detecting Health Issues in the Elderly
Application Automated medical monitoring device for older adults that can alert caregivers, medical personnel, and family of adverse medical events. Key Benefits Low-cost and easy-to-use medical alert system for falls and adverse health events. The technology does not require the individual to carry a device. Provides voice-assisted interface,...
Published: 5/21/2024       Contributor(s): Gari Clifford, Jacob Zelko, Nicolas Shu, Pradyumna Suresha, Ayse Cakmak
Automated Sleep Analysis Using Cardiovascular Signals
Application Sleep stage classification algorithm and diagnostic platform. Key Benefits Real-time sleep classification using a single electrocardiogram sensor. Eliminates the need for multiple head, eye, skin, and heart sensors with current diagnostics. Preliminary results using human data demonstrate high accuracy in identifying different sleep...
Published: 4/24/2024       Contributor(s): Gari Clifford, Shamim Nemati, Qiao Li, Supreeth Shashikumar
Machine Learning Diagnostic for Automated Identification and Classification of Bone Marrow Cells
Application Machine learning tool to aid in the diagnosis of hematologic disorders of bone marrow. Key Benefits Automated machine learning-based approach for performing bone marrow differential counts that accounts for all viable cells on the smear. Data generated by a prototype shows the system is fast and demonstrates precision compared to manual...
Published: 11/27/2023       Contributor(s): Lee Cooper, David Gutman, David Jaye, Ahmed Aljudi, Ramraj Chandradevan
Machine Learning for Neurodegenerative Disease Diagnosis and Monitoring
Application A machine learning classification model incorporating biomarkers for detecting Parkinson's disease. Key Benefits The image processing methods are simple to use, and the processing pipeline is fully automated. The method is novel and customized to address the practical requirements of clinical and research imaging. Market Summary Parkinson’s...
Published: 4/23/2024       Contributor(s): Daniel Huddleston, Babak Mahmoudi
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