Mintu Turakhia argues that technical capabilities already exist to allow fully autonomous medical AI, making deployment a matter of societal acceptance and liability framing.
“That's a societal issue. That's not a technical hurdle at this point.”
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More from Mintu Turakhia
Insight
Turakhia: Continuous learning in medical AI risks patient harm from biased data
“Bad data could heavily bias the system and cause harm, right? So if you start learning from bad inputs that come into the system for whatever reason, you could intentionally or unintentionally, you know, cause harm.”
Mintu TurakhiaJan 2, 2019▶ 22:21a16z Podcast | Putting AI in Medicine, in Practice
Insight
Turakhia: Missing wearable data is the strongest predictor of illness
“In fact, the biggest predictor, Of someone getting ill with a lot of wearable studies is missing data because they were too sick to wear the sensor.”
Mintu TurakhiaJan 2, 2019▶ 6:16a16z Podcast | Putting AI in Medicine, in Practice
AssertionNot checkable as stated
Turakhia: AI cannot predict acute heart attacks days in advance
“You can predict a cumulative probability, like a probability of getting condition X or diagnosis X over a time horizon of five or 10 years. But we are nowhere near saying, you know, you're going to have a heart attack in the next three days.”
Mintu TurakhiaJan 2, 2019▶ 5:38a16z Podcast | Putting AI in Medicine, in Practice
AssertionSupported
Turakhia: Neural networks replicate human error patterns in EKG and imaging studies
“Some of the most promising aspects of the imaging studies and the EKG studies are that the confusion matrices, the way humans misclassify things is recapitulated by the convolutional neural networks.”
Mintu TurakhiaJan 2, 2019▶ 10:49a16z Podcast | Putting AI in Medicine, in Practice
Opinion
Turakhia: FDA's Digital Health Office effectively mitigates regulatory risk
“The regulatory risk thing is being largely addressed by this new Office of Digital Health and the FDA, and they're really doing, seem much more forward thinking about it.”
Mintu TurakhiaJan 2, 2019▶ 21:46a16z Podcast | Putting AI in Medicine, in Practice
AssertionSupported
Turakhia: No standardized quality improvement metrics exist for EKG interpretation
“There's actually no standardized metrics for QI in any of this.”
Mintu TurakhiaJan 2, 2019▶ 24:35a16z Podcast | Putting AI in Medicine, in Practice
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