The intelligent healthcare management is of great concern to mobilize the enthusiasm of individuals and groups, and effectively use limited resources to achieve maximum health improvement by AI technology. When considering the intelligent healthcare management evaluation, the primary issues involve many uncertainties. Interval-valued fuzzy soft set, depicted by membership degree with interval form, is a more resultful means for capturing uncertainty. In this paper, the comparison issue in interval-valued fuzzy soft environment is disposed of by proposing novel score function. Later, some new properties for interval-valued fuzzy soft matrix are investigated in detail. Moreover, the objective weight is calculated by CRITIC (Criteria Importance Through Inter-criteria Correlation) method. Meanwhile, the combined weight is determined by reflecting both subjective weight and the objective weight. Then, interval-valued fuzzy soft decision-making algorithm-based CoCoSo (Combined Compromise Solution) is developed. Lastly, the validity of algorithm is expounded by the healthcare management industry evaluation issue, along with their sensitivity analysis. The main characteristics of the presented algorithm are: (1) without counterintuitive phenomena; (2) no division by zero problem; (3) have strong ability to distinguish alternatives.

智能医疗管理非常关注调动个人和团体的积极性，并有效利用有限的资源通过AI技术实现最大程度的健康改善。在考虑智能医疗管理评估时，主要问题涉及许多不确定性。用隶属度和间隔形式表示的区间值模糊软集是捕获不确定性的一种更有效的方法。通过提出新颖的得分函数，解决了区间值模糊软环境下的比较问题。随后，详细研究了区间值模糊软矩阵的一些新性质。此外，通过CRITIC（通过标准间关联的标准重要性）方法来计算目标权重。与此同时，综合权重是通过反映主观权重和客观权重来确定的。然后，开发了基于区间值的模糊软决策算法CoCoSo（组合折衷解决方案）。最后，通过医疗保健行业评价问题及其敏感性分析，阐述了算法的有效性。该算法的主要特点是：（1）没有违反直觉的现象；（2）没有被零除的问题；（3）有较强的区分能力。该算法的主要特点是：（1）没有违反直觉的现象；（2）没有被零除的问题；（3）有较强的区分能力。该算法的主要特点是：（1）没有违反直觉的现象；（2）没有被零除的问题；（3）有较强的区分能力。