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Related Experiment Video

Updated: Oct 1, 2025

Author Spotlight: Integrating Computational and Experimental Approaches in Precision Oncology

Author Spotlight: Integrating Computational and Experimental Approaches in Precision Oncology

Published on: December 1, 2023

Artificial Intelligence for Precision Oncology.

Sherry Bhalla¹, Alessandro Laganà²

¹Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Advances in Experimental Medicine and Biology

|March 1, 2022

Summary

This summary is machine-generated.

Artificial intelligence (AI) advances precision oncology by analyzing complex patient data from omics technologies. AI aids in cancer diagnosis, prognosis, and treatment, including subtype identification and drug prioritization.

Keywords:

Artificial intelligence Cancer Cancer subtype Deep learning Drug prioritization High-throughput technologies Machine learning Medical image analysis Multi-omics Precision oncology Sequencing

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Area of Science:

Oncology
Bioinformatics
Artificial Intelligence

Background:

Precision oncology utilizes individual genetic profiles for cancer care.
High-throughput omics technologies generate vast amounts of complex patient data.
Computational tools are essential for managing and analyzing this big data.

Purpose of the Study:

To provide an overview of AI applications in precision oncology and cancer research.
To highlight the role of AI in analyzing multi-omics datasets.
To discuss AI-powered medical image analysis and FDA-approved tools.

Main Methods:

Review of public data resources.
Application of AI and machine learning for pattern deciphering in large datasets.
Analysis of multi-omics data for cancer research.

Main Results:

AI, particularly machine learning, is well-suited for pattern recognition in large omics datasets.
AI applications span cancer subtype identification and drug prioritization.
AI is impacting medical image analysis in oncology, with FDA-approved tools now available.

Conclusions:

AI offers significant opportunities to advance precision oncology.
AI integration in cancer research facilitates data-driven insights and personalized treatments.
AI-powered tools are transforming cancer diagnosis and management.