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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: 3/2/2026
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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Smartphone Diagnostic for Rapid Respiratory Virus Detection
Application
Diagnostic and automatic surveillance platform to identify RSV, Influenza A, and COVID-19 in real-time.
Key Benefits
Rapid smartphone-based detection of multiple respiratory viruses in nasal swab, breath condensate, and saliva.
Requires few reagents and no expensive equipment.
Limit of detection on par with PCR and rapid readout.
Enables...
Published: 2/5/2026
Contributor(s): Selma Piranej, Khalid Salaita
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Improved Clinical Diagnostic Method for SARS-CoV-2 Infection
Application
A more reliable and accurate method for diagnosing SARS-CoV-2 infection based on the biochemical interactions between the spike trimer and ACE-2 protein.
Key Benefits
A fast, affordable, and easy-to-use SARS-Cov-2 diagnostic test for use in clinical settings.
Market Summary
SARS-CoV-2 has evolved significantly since the onset of...
Published: 9/3/2025
Contributor(s): John Roback, Andrew Neish, Narayanaiah Cheedarla, Hans Verkerke, Huixia Wu, William Osick, Kaleb Mclendon, Sindhu Potlapalli
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