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Info‑Latents: AI‑Driven Generation of Neural Activity
Application
An automatic software algorithm to generate new synthetic neural training data for BCI/BMI systems using information maximizing diffusion models.
Key Benefits
Flexible to support various architectures and modality of input with desired characteristics and task-relevant actions.
Saves on time and resources for traning BCI models.
Provides...
Published: 7/10/2026
Contributor(s): Jonathan McCart, Chethan Pandarinath
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Advanced Doppler Monitoring for Pregnancy Health Assessment
Application
Non-invasive prenatal monitoring to support assessment of maternal blood pressure and fetal cardiac activity using smartphone based 1D Doppler ultrasound and AI driven signal analysis.
Key Benefits
Low cost, cuff free approach for evaluating fetal cardiac signals and estimating maternal blood pressure during pregnancy.
Improves access...
Published: 7/10/2026
Contributor(s): Gari Clifford, Nasim Katebi (Katebijahromi)
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Heart Rate-Based PTSD Classification System
Application
This technology delivers an objective, data‑driven PTSD assessment based on heart activity, addressing the absence of standardized physiological criteria and reducing dependence on subjective self‑reports.
Key Benefits
Uses measurable physiological signals rather than self-reported symptoms.
Employs non-invasive electrocardiography...
Published: 4/10/2026
Contributor(s): Gari Clifford, Erik Reinertsen, Amit J. Shah, Shamim Nemati
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SMuRF: Software for Predicting Outcomes in Head and Neck Cancer
Application
Novel data learning framework for integrating radiology and pathology data for discovering prognostic biomarkers and predicting outcomes in head and neck cancer.
Key Benefits
Integrates radiology and pathology data to improve risk prediction for head and neck cancer and support more informed treatment decisions.
Can analyze multiple...
Published: 6/15/2026
Contributor(s): Bolin Song, Amaury Leroy, Anant Madabhushi
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AI-Driven Prognostic and Predictive Model for Muscle-Invasive Bladder Cancer
Application
This AI-driven prognostic and predictive model aims to predict outcomes for muscle-invasive bladder cancer (MIBC) patients undergoing neoadjuvant chemo-immunotherapy, aiding in treatment decision-making and patient stratification.
Key Benefits
Harnesses nuclear morphology and architectural features for precise prognostication in MIBC...
Published: 7/10/2026
Contributor(s): Kamal Hammouda, Tilak Pathak, Anant Madabhushi, Tuomas Mirtti
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Predictive Model for Post Surgery Prostate Cancer Recurrence
Application
An artificial intelligence based prognostic model for early Biochemical recurrence (BCR) risk assessment of men post-radical prostatectomy.
Key Benefits
Identifies significant features, including tumor-infiltrating lymphocytes (TIL), in prostate cancer recurrence.
Market Summary
Prostate cancer is one of the most diagnosed cancers...
Published: 3/2/2026
Contributor(s): Sebastian Medina, Kamal Hammouda, Tilak Pathak, Anant Madabhushi, Tuomas Mirtti
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Non-invasive Diagnostic for Meningiomas
Application
A non-invasive molecular diagnostic tool that reliably predicts the tumor characteristics and risk of recurrence of meningiomas.
Key Benefits
Combines meningioma gene expression data, construction of a gene interaction network, and tumor histology data to diagnose and predict clinical outcomes.
Complete analytical handling from specimen...
Published: 1/28/2026
Contributor(s): Ali Alawieh, Youssef Ismail, Tomas Garzon-Muvdi
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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: 1/20/2026
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: 4/10/2026
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: 7/21/2026
Contributor(s): Stefan Boettcher
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