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Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

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Artificial Intelligence for Outcome Modeling in Radiotherapy.

Sunan Cui¹, Andrew Hope², Thomas J Dilling³

¹Stanford University, Palo Alto, CA.

Seminars in Radiation Oncology

|October 6, 2022

Summary

This summary is machine-generated.

Artificial intelligence (AI) and machine learning (ML) enhance radiotherapy by integrating complex patient data. These advanced methods improve personalized treatment and precision medicine for better patient outcomes.

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Area of Science:

Oncology
Medical Physics
Radiotherapy

Background:

Outcome modeling is crucial for personalized radiotherapy, including adaptive radiotherapy.
Traditional models often rely solely on dosimetric data, overlooking multi-factorial influences.
Patient response to radiotherapy is complex, involving treatment, patient, and tumor microenvironment factors.

Purpose of the Study:

To highlight the role of artificial intelligence (AI) and machine learning (ML) in modern radiotherapy.
To emphasize the integration of diverse patient-specific data for improved outcome modeling.
To support the application of AI/ML in personalized and precision radiotherapy.

Main Methods:

Leveraging large datasets of patient-specific biological and imaging data.
Utilizing advanced biotechnology and multi-modality imaging techniques.
Applying AI and ML algorithms to analyze heterogeneous data and aid clinical decision-making.

Main Results:

AI/ML models can effectively process complex, multi-factorial data for radiotherapy.
Retrospective studies demonstrate the efficacy of AI/ML in radiotherapy outcome prediction.
Emerging prospective evidence supports the use of AI/ML for personalized radiotherapy.

Conclusions:

AI and ML are essential tools for making sense of complex patient data in radiotherapy.
These technologies facilitate personalized treatment strategies and precision medicine.
The integration of AI/ML promises to advance the field of adaptive radiotherapy and improve patient outcomes.