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Navigating AI and machine learning in cancer research: an end-to-end translational framework.
Shalini Saha1, Md Saif Ali2, Anand Kumar Tengli3
1Pharmaceutical Analysis, JSS College of Pharmacy, Mysore, Karnataka, India.
Journal of Translational Medicine
|June 27, 2026
Summary
Artificial intelligence (AI) and machine learning (ML) offer powerful computational tools for analyzing complex cancer data. Developing validated, representative, and compliant AI systems is crucial for advancing precision oncology and improving patient outcomes.
Area of Science:
- Oncology
- Bioinformatics
- Computational Biology
Background:
- Cancer is a complex disease with high biological variability.
- High-throughput technologies generate large, high-dimensional datasets in cancer research.
- Existing computational techniques may be insufficient for analyzing complex cancer data.
Purpose of the Study:
- To provide a comprehensive pipeline for artificial intelligence (AI) and machine learning (ML) in cancer research.
- To examine key technologies, data integration, and implementation challenges.
- To address translational barriers for AI in oncology.
Main Methods:
- Review of AI/ML applications across preclinical research, clinical decision support, and real-world implementation.
- Critical examination of multi-omics fusion, regularization-based ML, batch-effect harmonization, explainable AI, and federated learning.
- Analysis of translational barriers including algorithmic bias and regulatory differences.
Main Results:
- AI/ML present significant potential for cancer data analysis.
- Key technologies and challenges in AI/ML implementation for oncology are identified.
- Translational barriers and regulatory considerations across different regions are discussed.
Conclusions:
- Progress in precision oncology requires AI systems that are not only accurate but also externally validated, population-representative, and governance-compliant.
- Sustained real-world impact in oncology necessitates addressing algorithmic bias and regulatory asynchrony.
- AI holds promise for improving early detection and patient outcomes in cancer care.
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