Citation algorithms for identifying research milestones driving biomedical innovation

Citation algorithms for identifying research milestones driving biomedical innovation
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DOI:
10.1007/s11192-016-2238-1
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发表时间:
2016-11
期刊:
影响因子:
3.9
通讯作者:
Jordan A. Comins;L. Leydesdorff
Jordan A. Comins;L. Leydesdorff
中科院分区:
管理学3区
文献类型:
--
作者:
Jordan A. Comins;L. Leydesdorff

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科学活动在生物医学和卫生保健的创新中起着重要作用。例如,对疾病病理和机制的基础研究可以产生药物治疗的潜在靶点。这种共同进化被提供新观点和开辟新领域的论文所打断。尽管科学发现和生物医学进步之间存在关系,但确定这些真正影响生物医学创新的研究里程碑可能很困难,而且很大程度上完全基于主题专家的意见。在这里,我们考虑一类新的引文算法,即参考出版年光谱(RPYS)和多RPYS,是否可以识别创新(如治疗方法)与基础研究之间的联系。具体而言,我们评估这些分析技术的结果是否与专家意见在推动基底细胞癌治疗生物医学创新的研究里程碑相一致。我们的研究结果表明,这些算法成功地识别了专家详细描述的大多数里程碑论文(Wong和plugosz在J Investig Dermatol 134(e1): E18-E22, 2014),从而验证了这些算法收敛于主题专家衍生的开创性科学作品的独立意见的能力。这些进步提供了一个机会,以确定能够促进生物医学创新的科学活动。
Scientific activity plays a major role in innovation for biomedicine and healthcare. For instance, fundamental research on disease pathologies and mechanisms can generate potential targets for drug therapy. This co-evolution is punctuated by papers which provide new perspectives and open new domains. Despite the relationship between scientific discovery and biomedical advancement, identifying these research milestones that truly impact biomedical innovation can be difficult and is largely based solely on the opinions of subject matter experts. Here, we consider whether a new class of citation algorithms that identify seminal scientific works in a field, Reference Publication Year Spectroscopy (RPYS) and multi-RPYS, can identify the connections between innovation (e.g., therapeutic treatments) and the foundational research underlying them. Specifically, we assess whether the results of these analytic techniques converge with expert opinions on research milestones driving biomedical innovation in the treatment of Basal Cell Carcinoma. Our results show that these algorithms successfully identify the majority of milestone papers detailed by experts (Wong and Dlugosz in J Investig Dermatol 134(e1):E18–E22, 2014)—thereby validating the power of these algorithms to converge on independent opinions of seminal scientific works derived by subject matter experts. These advances offer an opportunity to identify scientific activities enabling innovation in biomedicine.