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Related Experiment Video

Updated: Oct 11, 2025

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Molecular-based precision oncology clinical decision making augmented by artificial intelligence.

Jia Zeng1, Md Abu Shufean1

  • 1Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, U.S.A.

Emerging Topics in Life Sciences
|December 7, 2021
PubMed
Summary

Artificial intelligence (AI) aids clinicians in interpreting complex genomic data from next-generation sequencing (NGS) for personalized cancer treatment. This review explores AI systems for precision oncology, highlighting their benefits and current limitations.

Keywords:
artificial intelligenceclinical decision makingmachine learningnext-generation sequencingprecision oncology

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Area of Science:

  • Genomics
  • Bioinformatics
  • Oncology

Background:

  • Next-generation sequencing (NGS) costs are decreasing, enabling large-scale genomic analysis in oncology.
  • Personalized cancer treatment relies on comprehensive molecular testing for optimal patient management.

Purpose of the Study:

  • To review artificial intelligence (AI) systems that assist clinicians in making decisions based on molecular sequencing data.
  • To focus on the application of AI in precision oncology and discuss its challenges.

Main Methods:

  • Literature review of AI systems applied to clinical decision-making in oncology.
  • Analysis of AI's role in translating molecular sequencing reports into actionable insights.

Main Results:

  • AI systems can facilitate the interpretation of complex genomic data for clinicians.
  • Several representative AI systems are discussed concerning their application in precision oncology.

Conclusions:

  • AI holds significant potential to enhance clinical decision-making in precision oncology.
  • Current limitations and challenges in AI application for clinical decision support are identified.