首页|Data on Machine Learning Reported by Jernej Završnik and Colleagues (Trusting AI made decisions in healthcare by making them explainable)
Data on Machine Learning Reported by Jernej Završnik and Colleagues (Trusting AI made decisions in healthcare by making them explainable)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Machine Learning is the subject o f a report. According to news reporting out of Maribor, Slovenia, by NewsRx edit ors, research stated, “In solving the trust issues surrounding machine learning algorithms whose reasoning cannot be understood, advancements can be made toward the integration of machine learning algorithms into mHealth applications. The a im of this paper is to provide a transparency layer to black-box machine learnin g algorithms and empower mHealth applications to maximize their efficiency.” Our news journalists obtained a quote from the research, “Using a machine learni ng testing framework, we present the process of knowledge transfer between a whi te-box model and a black-box model and the evaluation process to validate the su ccess of the knowledge transfer. The presentation layer of the final output of t he base white-box model and the knowledge-infused white-box model shows clear di fferences in reasoning. The correlation between the base black-box model and the new knowledge-infused model is very high, indicating that the knowledge transfe r was successful. There is a clear need for transparency in digital health and h ealth in general.” According to the news editors, the research concluded: “Adding solutions to the toolbox of explainable artificial intelligence is one way to gradually decrease the obscurity of black-box models.” This research has been peer-reviewed.
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