Personalized Medicine
     Definition: Tailoring medical treatment based on individual factors like genetic makeup, tumor behavior, or                 immune status.
     Example: Choosing a drug based on a patient's tumor DNA mutation.

​

Patient-Specific Predictive Modeling
     Definition: Using mathematical models and personal patient data (like tumor growth, imaging, and genetics) to           predict how they will respond to treatment.
     Example: Using a model to figure out the best time for a patient to start therapy.

​

Predictive Modeling
     Definition: Using data and math to predict how a disease or treatment will progress.
     Example: Estimating the chance that a tumor will come back after treatment.

​

Treatment Response Metrics (e.g., Days Gained)
     Definition: Measuring how much a treatment helps slow down disease progression.
     Example: “Days Gained” measures how many extra days a treatment delays tumor growth compared to no                 treatment.

​

MGMT Methylation
     Definition: A genetic marker used to help decide the best chemotherapy for glioblastoma patients.
     Example: Low MGMT methylation may mean the tumor won’t respond well to certain drugs.

​

Clinical Imaging
     Definition: Non-invasive tools like MRI and CT scans to observe and measure tumors.
     Example: Measuring tumor size before and after chemotherapy using MRI.

​

Multiparametric Imaging Integration
     Definition: Using different types of medical images together to better understand a tumor’s properties.
     Example: Combining MRI and PET scans to help calibrate treatment models.

​

Treatment Response Monitoring
     Definition: Using imaging and mathematical models to track how tumors shrink or change during treatment.
     Example: Monitoring tumor changes using serial MRI scans during radiation therapy.

​

Radiomics
     Definition: Analyzing medical images to extract detailed features that help assess tumor characteristics.
     Example: Analyzing the texture of an MRI scan to determine how aggressive a tumor is.

​

Radiogenomics
     Definition: Connecting features from medical images with genetic data to understand a tumor better.
     Example: Using CT scan features to predict a genetic mutation in the tumor using machine learning.

​

Machine Learning in Radiogenomics
     Definition: Using algorithms to learn from both medical images and genetic data to make predictions.
     Example: Using machine learning to predict a tumor’s HPV status from its CT scan features.

​

Big Data
     Definition: Large sets of data from clinical, genetic, and imaging sources that help doctors make better treatment       decisions.
     Example: Using patient data, genetic information, and imaging to develop personalized treatment plans.

​

Bayesian Inference
     Definition: A method of using existing knowledge and new data to estimate uncertainties in predictions.
     Example: Using Bayesian methods to figure out how certain we are about how much a treatment delays tumor             growth.

​

Random Forests
     Definition: A machine learning technique that builds multiple decision trees and combines them to make                       predictions.
     Example: Using random forests to predict tumor malignancy by combining decisions from several trees based on         tumor features like size and texture.