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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: 2/13/2025
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: 2/13/2025
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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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: 2/13/2025
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: 2/13/2025
Contributor(s): Brianna Karpowicz, Chethan Pandarinath, Yahia Ali, Marc Slutzky, Robert Flint, Bareesh Bhaduri
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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: 2/13/2025
Contributor(s): Lee Cooper, David Gutman, David Jaye, Ahmed Aljudi, Ramraj Chandradevan
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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: 2/13/2025
Contributor(s): Daniel Huddleston, Babak Mahmoudi
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Vital Sign Trajectory Algorithm
Application
A precision medicine algorithm that reduces mortality in sepsis patients by individualizing and targeting specific therapies to specific patients.
Key Benefits
An algorithm that uses bedside routine vital signs to optimize the precision treatment of sepsis.
Clinical data show the ability of the algorithm to identify a subset of patients...
Published: 2/13/2025
Contributor(s): Sivasubramanium (Siva) Bhavani
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Automated Breast Arterial Calcifications Segmentation and Quantification on Mammograms Using Deep Learning
Application
Software for the quantification of breast arterial calcifications on routine mammograms to be used for risk stratification for cardiovascular outcomes.
Key Benefits
Optimized image segmentation accuracy with reduced software complexity.
Integrated calcium scoring.
Screens patients who would not normally be indicated for cardiac...
Published: 2/13/2025
Contributor(s): Hari Trivedi, Imon Banerjee, William Charles O'Neill, Xiaoyuan Guo
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Quantitative Multi Energy Computed Tomography (MECT) for the Characterization of Composition and Density Maps of Artificial and Human Materials in Proton Therapy
Application
A novel multi-energy computed tomography (MECT) simulation framework to determine the densities of human tissues and material compositions of implant material maps for proton Monte Carlo does performs the calculation.
Key Benefits
Provides a multi-image computer tomography based alternative methodology of providing complete maps...
Published: 2/13/2025
Contributor(s): Liyong Lin, Chih-Wei Chang, Tiezhi Zhang, Shuai Leng, Serdar Charyyev, Xiaofeng Yang, Joseph (Joe) Harms
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CBCT-Guided Adaptive Photon and Proton Radiotherapy
Application
Generating synthetic MRI images from CBCT images with deep learning.
Key Benefits
Generate high contrast MRI images from cone-beam CT images.
High quality, high contrast images to enable precise radiation treatment.
Market Summary
Radiation therapy (RT) is one of the most common treatment modalities for cancer and is used...
Published: 2/13/2025
Contributor(s): Xiaofeng Yang, Yang Lei, Tian Liu, Jun Zhou
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