Row 28928

Row ID: 28928 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 28928 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

This is the major issue preventing ML penetration of things like diagnostics and treatments -- biology and computers move at different speeds (not to mention clinical trials and the regulatory framework). We need good evidence that things work, because human biology is complicated and lots of things that sound like good ideas or test well in animals can't actually be shown to improve human health. Running proper trials and collecting evidence takes time, and is expensive, so we have multi-phase testing to prioritize the most promising ideas. Right now the really high impact ML applications are still in the bench testing phase, and, probably, most of these ideas will never make it to the clinic, just like most "cures for cancer" we see in the news don't actually become approved treatments.

FieldValue
text This is the major issue preventing ML penetration of things like diagnostics and treatments -- biology and computers move at different speeds (not to mention clinical trials and the regulatory framework). We need good evidence that things work, because human biology is complicated and lots of things that sound like good ideas or test well in animals can't actually be shown to improve human health. Running proper trials and collecting evidence takes time, and is expensive, so we have multi-phase …
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-21
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Raw Record

{
  "text": "This is the major issue preventing ML penetration of things like diagnostics and treatments -- biology and computers move at different speeds (not to mention clinical trials and the regulatory framework). We need good evidence that things work, because human biology is complicated and lots of things that sound like good ideas or test well in animals can't actually be shown to improve human health. Running proper trials and collecting evidence takes time, and is expensive, so we have multi-phase testing to prioritize the most promising ideas. Right now the really high impact ML applications are still in the bench testing phase, and, probably, most of these ideas will never make it to the clinic, just like most \"cures for cancer\" we see in the news don't actually become approved treatments.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-21",
  "username_encoded": "Z0FBQUFBQm5Lak1FQnZjQzhvbnNOWThtdUFtZ1JWbElzUDdVMElaRXlJNm5EN3ZUc1hhcWRUWHN3Q0xsLXVuNW9nU1pRWGVrbXJMMzctU25iWFE3aXpQZ1VFU0lYWTBXYXc9PQ==",
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}
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