Hundreds of AI tools for health care — from transcription and imaging to diagnostics — tout accuracy rates above 90%, but most are tested only in isolation.
Why it matters: Those tools become less reliable when used together, an analysis by Korean AI scientist Kwansub Yun suggests.
