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Search Results - kamal+hammouda
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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
|
Inventor(s):
Kamal Hammouda
,
Tilak Pathak
,
Anant Madabhushi
,
Tuomas Mirtti
Keywords(s):
Algorithm, AI, and Machine Learning
,
Data Infrastructure and Analysis
,
Diagnostics
,
Molecular Diagnostics
,
Oncology Treatments
,
Personalized Medicine
,
Research Tools
Category(s):
TechPub Algolia > Software
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
|
Inventor(s):
Sebastian Medina
,
Kamal Hammouda
,
Tilak Pathak
,
Anant Madabhushi
,
Tuomas Mirtti
Keywords(s):
Algorithm, AI, and Machine Learning
,
Data Infrastructure and Analysis
,
Diagnostics
,
Immunology and Inflammation Treatments
,
Medical Imaging (MRI, CT, Radiology)
,
Molecular Diagnostics
,
Oncology Treatments
,
Research Tools
Category(s):
TechPub Algolia > Software
Personalized Medicine Using Additive Manufacturing
THE CHALLENGE A major problem posed by the pharmaceutical industry is giving effective dosages while not giving excessive amounts of a particular drug. An estimated 80% of side effects in humans and animals are a direct result of inaccurate dosing because varying weights in patients. Additive manufacturing has emerged as a very promising method to...
Published: 6/26/2025
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Inventor(s):
Emily Wilts
,
Timothy Long
,
Christopher Williams
,
Da Ma
Keywords(s):
Category(s):
Technology Classifications > Additive Manufacturing
,
Technology Classifications > Biomedical
,
Technology Classifications > Chemicals/Materials
,
Technology Classifications > Pharmacology and Therapeutics