Background <p>The use of artificial intelligence (AI) for medical diagnostics and treatment has seen enormous advances in recent years, particularly in terms of image processing and clinical decision-making.</p> Objective <p>The aim of this work is to provide an overview of the current status and future potential of AI applications in the field of oncology.</p> Materials and methods <p>A selective literature search was conducted in scientific databases, and current developments pertaining to AI-supported oncology were analyzed.</p> Results <p>The application of AI enables automation of repetitive tasks in radiology and histopathology, and several products approved for clinical application are already available. Although large language models such as ChatGPT (generative pretrained transformer) have potential for decision support, the lack of formal approvals and problems with hallucinations prevent their widespread implementation.</p> Conclusion <p>Although AI has the potential to enable huge advancements in cancer medicine, there are regulatory and technical hurdles to be overcome before these technologies can be routinely applied.</p>

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Einsatz der künstlichen Intelligenz in der Diagnostik und Therapie solider Tumoren

  • Jan C. Peeken,
  • Jakob Nikolas Kather

摘要

Background

The use of artificial intelligence (AI) for medical diagnostics and treatment has seen enormous advances in recent years, particularly in terms of image processing and clinical decision-making.

Objective

The aim of this work is to provide an overview of the current status and future potential of AI applications in the field of oncology.

Materials and methods

A selective literature search was conducted in scientific databases, and current developments pertaining to AI-supported oncology were analyzed.

Results

The application of AI enables automation of repetitive tasks in radiology and histopathology, and several products approved for clinical application are already available. Although large language models such as ChatGPT (generative pretrained transformer) have potential for decision support, the lack of formal approvals and problems with hallucinations prevent their widespread implementation.

Conclusion

Although AI has the potential to enable huge advancements in cancer medicine, there are regulatory and technical hurdles to be overcome before these technologies can be routinely applied.