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@PinakiLaskar 2 years ago
Why are #machinelearning models trained to make medical decisions that perform at nearly the same level as human experts not in clinical use? https://www.linkedin.com/posts/pinakilaskar_machinelearning-algorithms-deeplearning-activity-6806429189512728576-8Dhl #BigData #Analytics #DataScience #Python #RStats #JavaScript #ReactJS #Serverless #Linux #Coding #100DaysofCode
@moorejh 3 years ago
The labels attached to images used to train machine-vision systems are often wrong. That could mean bad decisions by self-driving cars and medical algorithms. https://www.wired.com/story/foundations-ai-riddled-errors/ #machinelearning #datascience #deeplearning
@ewenharrison 4 years ago
Black box models are not acceptable for high stakes decisions in medicine. Models must be interpretable, not just explainable (explanations are wrong by definition). Here’s your great long-read for today by @CynthiaRudin https://arxiv.org/abs/1811.10154 #rstats #DataScience
@SwissCognitive 4 years ago
“#MachineLearning is particularly good at identifying patterns, which is deeply relevant to assessing patient risk. Risk scores are useful for communicating patient state, which is valuable in making efficient care decisions.” http://ow.ly/bAfz30px9lg #Healthcare #Medicine #AI