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AI Model for Extracting Patterns from EMG Data
Application
Aritificial neural network-based dynamical systems modeling on electromyography (EMG) data for simultaneously estimating de-noised, high-resolution muscle activation signals across multiple muscles with millisecond-timescale precision.
Key Benefits
Generates models that produce estimates that avoid trivial output solutions (e.g., replicating...
Published: 11/5/2025
Contributor(s): Lahiru Wimalasena, Chethan Pandarinath, Mohammad Reza Keshtkaran
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Automated Image Analysis of Bone Histomorphometry Using Deep Learning
Application
An automated pipeline for digital phenotyping of brightfield bone biopsy images to generate feature maps for static histomorphometry.
Key Benefits
Combines automation with deep learning models to improve tissue delineation and quantify tissue and cellular components pertinent to static histomorphometric parameters.
Incorporates Morphological...
Published: 11/7/2025
Contributor(s): Satvika Bharadwaj, Anant Madabhushi, Madhumathi Rao, Hartmut Malluche, Florence Lima
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Efficient Combinatorial Optimization
Application
Optimization heuristic for solving large-scale combinatorial problems.
Key Benefits
Efficient exploration of highly non-convex instances.
Capable of handling large-scale problems.
Reduces total computation time through massive parallelization.
Especially designed for unconstrained binary problems.
Market Summary
The combinatorial...
Published: 9/22/2025
Contributor(s): Stefan Boettcher
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Multi-Modal Sensing Platform for Diagnosing Depression and Schizophrenia
Application
A multi-sense deep learning platform and interview protocol used for detection and assessment of depression and schizophrenia.
Key Benefits
Automated and remote mental illness assessment without the need for self-reporting or clinical observation.
Improved disease tracking for patients and clinicians.
A more objective classifier and...
Published: 11/7/2025
Contributor(s): Gari Clifford, Robert Cotes, Mina Boazak, Zifan Jiang, Seyed Salman Seyedi, Ali Bahrami Rad
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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: 5/30/2025
Contributor(s): Rohan Dhamdhere, Sadeer Al-Kindi, Gourav Modanwal, Anant Madabhushi
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Multimodal Identification of Atrial Fibrillation Recurrence Sites
Application
Identifies areas of interest associated with atrial fibrillation recurrences.
Key Benefits
Identifies sites associated with recurrences for AF patients.
Predict AF recurrence risk in patients’ post-catheter ablation.
Development of prediction model by extracting features from the surface of interest (SOI).
Market Summary
Atrial...
Published: 10/3/2025
Contributor(s): Abhishek Midya, Anant Madabhushi, Golnoush Asaeikheybari, Mina K. Chung, Amogh Hiremath, Moore Benjamin Shoemaker, Majd A. El-Harasis, John Barnard, Rod S. Passman
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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: 11/3/2025
Contributor(s): Gari Clifford, Amit J. Shah, Ayse Cakmak, Erik Reinertsen
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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: 10/15/2025
Contributor(s): Shamim Nemati, Supreeth Shashikumar, Amit J. Shah, Qiao Li, Gari Clifford
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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: 3/28/2025
Contributor(s): Brianna Karpowicz, Chethan Pandarinath, Yahia Ali, Marc Slutzky, Robert Flint, Bareesh Bhaduri
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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: 11/3/2025
Contributor(s): Gari Clifford, Shamim Nemati, Qiao Li, Supreeth Shashikumar
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