医疗图像处理装置专利价值评价数据

通过收集医疗图像处理装置领域专利申请人、法律状态、技术主题分类、简单同族成员数量等数据，形成了主要包括全球专利数据库中与医疗图像处理装置相关的发明专利和实用新型专利数据，在结果中筛选关键词医疗图像处理装置，找出医疗图像处理装置方向专利数据，并根据自有算法对专利数据进行了评价和分类，可用于了解医疗图像处理装置专利数据变化情况，有助于了解医疗图像处理装置知识产权工作成果；通过对各企业/个人医疗图像处理装置专利数据的对比，可了解各企业/个人的技术创新能力、创新水平差异；了解医疗图像处理装置的技术发展趋势，有助于企业避免重复研发，避免企业开发的技术侵犯他人的知识产权。数据基于AHP层次法，采用定量与定性相结合，从专利价值度法出发，指标层将专利价值指标体系分为技术、法律、经济3项一级指标，一级指标层向下为二级指标，包括技术价值指标：独立权利要求数量、权利要求数量、首项权利要求字数、专利维持有效时间、同族专利数、引证其它专利数、被其他专利引证数、发明人数量、IPC数量；法律价值指标：专利类型、说明书页数、诉讼次数；经济价值指标：转让次数、许可次数、质押次数；根据一级、二级指标建立3个维度的矩阵，通过专利接口数据获取专利评价对应的数据指标，采用1-9分标度法（最低为1分，最高为9分），求得相应的指标权重，用权重技术各个指标的分值，所有指标分值的和即为专利得分，根据分值的区间段对专利进行划分，80-100为高价值专利、60-80为重要专利、60分以下为一般专利，为医疗图像处理装置企业研发人员提供技术参考及指引，为公司提供研发决策指导。

This dataset is constructed by collecting multi-dimensional data including patent applicants, legal status, technical subject classification, and number of simple family members in the field of medical image processing devices. It mainly covers invention patents and utility model patents related to medical image processing devices from the global patent database. First, patent data focused on medical image processing devices is filtered out using the keyword "medical image processing device", then evaluated and categorized via self-developed algorithms. This dataset can be used to track changes in patent data related to medical image processing devices, helping to understand the achievements of intellectual property work in this field. By comparing the medical image processing device patent data of different enterprises or individual inventors, it is possible to analyze the technological innovation capabilities and differences in innovation levels among various entities. Additionally, it can reveal the technological development trends of medical image processing devices, assisting enterprises in avoiding redundant R&D and potential intellectual property infringement risks. The patent evaluation is based on the Analytic Hierarchy Process (AHP), combining quantitative and qualitative methods based on patent valuation methodology. The patent value indicator system is divided into three first-level indicators: technical value, legal value, and economic value. Corresponding second-level indicators are set under each first-level indicator: 1. Technical value indicators: number of independent claims, total number of claims, word count of the first claim, valid patent duration, number of family patents, number of cited external patents, number of citations received by the patent, number of inventors, and number of IPC classifications; 2. Legal value indicators: patent type, number of pages of the specification, and number of litigation cases; 3. Economic value indicators: number of transfer transactions, number of licensing transactions, and number of pledge transactions. A three-dimensional matrix is established based on the first-level and second-level indicators. Data indicators required for patent evaluation are obtained through patent interface data. The 1-9 scaling method (with 1 as the lowest score and 9 as the highest) is adopted to calculate the weight of each indicator, which is then used to compute the score of each individual indicator. The sum of all indicator scores constitutes the total patent score. Patents are classified into three categories based on their total scores: 80-100 for high-value patents, 60-80 for important patents, and below 60 for general patents. This dataset provides technical references and decision-making guidance for R&D personnel of enterprises engaged in medical image processing device development, and supports enterprises in formulating targeted R&D strategies.

搜集汇总

数据集介绍

特点

该数据集包含655条医疗图像处理装置领域的专利价值评价数据，每年更新一次。数据通过AHP层次法从技术、法律和经济三个维度进行评分，评分区间为1-9分，最终将专利分为高价值、重要和一般三类。数据集可用于了解技术发展趋势、企业创新能力对比以及避免重复研发和知识产权侵权。