Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting originating from Durham, Ne w Hampshire, by NewsRx correspondents, research stated, “The proliferation of di gital and social media technologies has enabled quick and wide dissemination of news stories and press releases about new medical treatments. Evaluating these s tories is difficult for two reasons.” Our news editors obtained a quote from the research from the University of New H ampshire, “First, these stories are often not completely true or false. A nuance d approach that considers different aspects of these stories (e.g., the presence of inflated claims, suppression of risks associated with the treatment or withh olding other essential information) is more appropriate for evaluation. Second, evaluating the quality and completeness of the arguments in the stories is costl y and requires expertise in the relevant medical field, which laypeople do not h ave. To address this problem, in this study, we train different machine learning models on multi-criteria expert evaluations for health news stories about new m edical treatments and compare their performance. We then compare the machine lea rning model evaluations to laypeople evaluations. We find that machine learning models overall outperform laypeople, who have a propensity to overestimate the c omprehensiveness of the claims. Our machine learning models employ multi-criteri a evaluation, which is different from most previous studies that evaluate news s tories on whether they are true or false.”
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