首页|Data on Machine Learning Reported by Stefan Feuerriegel and Colleagues (Causal m achine learning for predicting treatment outcomes)
Data on Machine Learning Reported by Stefan Feuerriegel and Colleagues (Causal m achine learning for predicting treatment outcomes)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating from Munich, Germ any, by NewsRx correspondents, research stated, “Causal machine learning (ML) of fers flexible, data-driven methods for predicting treatment outcomes including e fficacy and toxicity, thereby supporting the assessment and safety of drugs. A k ey benefit of causal ML is that it allows for estimating individualized treatmen t effects, so that clinical decision-making can be personalized to individual pa tient profiles.” Our news editors obtained a quote from the research, “Causal ML can be used in c ombination with both clinical trial data and real-world data, such as clinical r egistries and electronic health records, but caution is needed to avoid biased o r incorrect predictions. In this Perspective, we discuss the benefits of causal ML (relative to traditional statistical or ML approaches) and outline the key co mponents and steps.”
MunichGermanyEuropeCyborgsEmergi ng TechnologiesMachine Learning
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