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Foundation Models for Translational Cancer Biology
Kevin K Tsang1,2, Sophia Kivelson1, Jose M Acitores Cortina1
1Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, California, USA;
Foundation models are revolutionizing cancer research by integrating diverse data for precision medicine. These advanced AI tools enhance tumor classification, surgical assistance, and personalized treatments, accelerating progress in oncology.
Area of Science:
- Oncology
- Artificial Intelligence
- Bioinformatics
Background:
- Cancer is a leading global cause of death.
- Diverse cancer datasets challenge precision medicine.
- Foundation models offer a unified approach.
Purpose of the Study:
- To review foundation models in cancer research.
- To explore applications in NLP, computer vision, molecular biology, and cheminformatics.
- To discuss current and future impacts on precision oncology.
Main Methods:
- Review of state-of-the-art foundation models.
- Analysis of applications in translational cancer research.
- Exploration of prospective advances.
Main Results:
- Foundation models advance precision tumor classification.
- AI-assisted surgery is enhanced by these models.
- Applications span early detection to personalized treatment and drug discovery.
Conclusions:
- Foundation models are crucial for future cancer research and care.
- They offer curated resources for researchers and insights for practitioners.
- Significant opportunities exist for novel applications in oncology.
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