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A guide to artificial intelligence for cancer researchers.

Raquel Perez-LopezNarmin Ghaffari LalehFaisal MahmoodJakob Nikolas Kather
Published in: Nature reviews. Cancer (2024)
Artificial intelligence (AI) has been commoditized. It has evolved from a specialty resource to a readily accessible tool for cancer researchers. AI-based tools can boost research productivity in daily workflows, but can also extract hidden information from existing data, thereby enabling new scientific discoveries. Building a basic literacy in these tools is useful for every cancer researcher. Researchers with a traditional biological science focus can use AI-based tools through off-the-shelf software, whereas those who are more computationally inclined can develop their own AI-based software pipelines. In this article, we provide a practical guide for non-computational cancer researchers to understand how AI-based tools can benefit them. We convey general principles of AI for applications in image analysis, natural language processing and drug discovery. In addition, we give examples of how non-computational researchers can get started on the journey to productively use AI in their own work.
Keyphrases
  • artificial intelligence
  • big data
  • machine learning
  • deep learning
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  • squamous cell
  • drug discovery
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  • childhood cancer
  • social media