Research
Organizations investing in AI for healthcare should recognize that model selection matters less than solving upstream data challenges—curation, integration, and access—which will shape vendor selection and deployment timelines.
A startup argues that AI's path to cancer treatment breakthroughs hinges on data quality and availability rather than model capability alone. The piece explores what practical infrastructure and datasets are needed before AI can meaningfully contribute to oncology.
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