Altered modular organization in schizophrenia patients and analysis using supervised association rule mining

GeethaRamani, R.; Sivaselvi, K.

doi:10.1016/j.bbe.2016.02.002

Cited by 2 publications

(2 citation statements)

References 57 publications

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“…e Apriori algorithm was used to mine the potential relevance of innovation elements in patent data, analyze the constitution rules of innovation elements, and identify the potential opportunities of technological relevance. e method iteratively mined frequent item sets through layer-by-layer search and generated strong association rules [19,20]. Support and Confidence are commonly used to measure whether a rule meets the expectations.…”

Section: Apriori Algorithmmentioning

confidence: 99%

“…is Atlas can be utilized by research institutions to adjust their technology development strategies and grasp technological opportunities. Among them, the frequency of technical field 1 and functional cluster are in the following order: Cluster 4 (37), Cluster 1 (36), Cluster 3 (19), and Cluster 2 (17). For technical field 2: Cluster 3 (163), Cluster 2 (50), Cluster 1 (30), and Cluster 4 (22).…”

Section: Opportunity Decision Assistance Atlas Of Non-pharmaceutical ...mentioning

confidence: 99%

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Technology Opportunity Recognition Algorithm and Decision Assistance for Non-Drug Antidepressant Field in China

Cui

Zhao²,

Xia

2022

Mathematical Problems in Engineering

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The aim of this study is to propose a framework for non-pharmaceutical antidepressant technology opportunity identification in China, based on patent analysis and assisted decision making. Semantic mining technology was used to divide technology life cycle, classify technology, identify key technology associated opportunities, and identify core technology functions of 532 non-drug antidepressant patent data in China from 1995 to 2021. Combined with co-occurrence and multi-dimensional scale analysis, strategic coordinate maps and technology decision assistance maps were drawn. The development of non-drug antidepressant technology in China was divided into embryonic stage, formative stage, and development stage. Six technical categories, 30 high-frequency technical associated opportunities, and low-frequency and high-frequency core technical opportunities for non-drug antidepressants were summarized. Based on four technical fields and four functional clusters of strategic coordinate graphs, the technical opportunity decision auxiliary atlas was constructed. By comparison, this map is more intuitive than the technology-efficacy matrix, when presenting technology efficiency mapping. This study provides a set of systematic algorithms for opportunity identification and decision assistance based on patent data, in addition to reference for strategic decision making of non-drug antidepressant technology subjects in China.

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Section: Apriori Algorithmmentioning

confidence: 99%

Section: Opportunity Decision Assistance Atlas Of Non-pharmaceutical ...mentioning

confidence: 99%

Technology Opportunity Recognition Algorithm and Decision Assistance for Non-Drug Antidepressant Field in China

Cui

Zhao²,

Xia

2022

Mathematical Problems in Engineering

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Neural Mechanisms of Early-Life Social Stress as a Developmental Risk Factor for Severe Psychiatric Disorders

Reinwald

Becker

Mallien

et al. 2018

Biological Psychiatry

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Altered modular organization in schizophrenia patients and analysis using supervised association rule mining

Cited by 2 publications

References 57 publications

Technology Opportunity Recognition Algorithm and Decision Assistance for Non-Drug Antidepressant Field in China

Technology Opportunity Recognition Algorithm and Decision Assistance for Non-Drug Antidepressant Field in China

Neural Mechanisms of Early-Life Social Stress as a Developmental Risk Factor for Severe Psychiatric Disorders

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