Flaw Found in AI for Sepsis Treatment
In brief
- Researchers found a flaw in many studies using a type of AI called reinforcement learning for sepsis treatment.
- The flaw is in how data is preprocessed and indexed.
- This causes the AI to sometimes use future events to predict the past.
- If used in a health care setting, these flawed systems would recommend incorrect treatment in nearly half of patient cases.
- The researchers found that fixing the flaw can decrease patient mortality by 8-10 percent.
- They will continue to work on building safer and more reliable AI models for health care.
Terms in this brief
- Reinforcement Learning
- A type of machine learning where an AI learns to make decisions by performing actions and receiving feedback in the form of rewards or penalties. It's like teaching a child to play a game by rewarding them when they do something right, encouraging them to repeat that behavior.
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