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Algorithm is the core category and basic methods of the digital age, and advanced technologies such as big data, artificial intelligence, and blockchain all need to rely on various algorithm designs or take the algorithm as the underlying principle. However, due to the characteristics of algorithm design, application, and technology itself, there are also hidden worries such as algorithm black-box, algorithm discrimination, and difficulty in accountability in the operation process to varying degrees. This paper summarizes these problems into three aspects: unexplainable, self-reinforcing and autonomous. Facing the opportunities and risks generated by the application of the algorithm in national governance, while actively promoting the development of algorithm technology to continuously promote the modernization process of national governance, it is also necessary to increase the governance of the algorithm. The practice has proved that enhancing the interpretability of algorithm, optimizing algorithm design, and adopting legal regulatory algorithm are the basic approaches to effective regulatory algorithm in the era of intelligent governance. [ABSTRACT FROM AUTHOR]

With the rapid development of AI and big data mining technologies, computerized medical decision-making has become increasingly prominent. The aim of high-utility pattern mining (HUPM) is to discover meaningful patterns in medical databases that contribute to maximizing the utility from the perspective of diagnosis. However, HUPM pays less attention to the interpretability and explainability of these patterns in medical decision-making scenarios. This paper proposes a novel algorithm called the Improved fuzzy high-utility pattern mining (IF-HUPM) to address this problem. First, the paper applies a fuzzy preprocessing method to divide the fuzzy intervals of a medical quantitative data set, which enhances the fuzziness and interpretability of the data. Next, in the process of IF-HUPM, both fuzzy tree and list structures are employed to calculate fuzzy high-utility values. By combining the characteristics of the one-stage and two-stage algorithms of HUPM, an adaptive-phase Fuzzy HUPM hybrid frame is proposed. The experimental results demonstrate that the proposed IF-HUPM algorithm enhances both accuracy and efficiency and the mining process requires less time and space on average. [ABSTRACT FROM AUTHOR]