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Uncovering pedestrian midblock crash severity patterns using association rules mining.

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Title: Uncovering pedestrian midblock crash severity patterns using association rules mining.
Authors: Chakraborty, Rohit1 (AUTHOR) xuw12@txstate.edu, Das, Subasish2 (AUTHOR), Khan, Md Nasim3 (AUTHOR)
Source: Transportmetrica A: Transport Science. Feb2026, Vol. 22 Issue 1, p1-48. 48p.
Database: Academic Search Ultimate
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  Data: Uncovering pedestrian midblock crash severity patterns using association rules mining.
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  Data: <searchLink fieldCode="JN" term="%22Transportmetrica+A%3A+Transport+Science%22">Transportmetrica A: Transport Science</searchLink>. Feb2026, Vol. 22 Issue 1, p1-48. 48p.
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1080/23249935.2024.2379948
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      – Code: eng
        Text: English
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        PageCount: 48
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      – TitleFull: Uncovering pedestrian midblock crash severity patterns using association rules mining.
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            NameFull: Chakraborty, Rohit
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            NameFull: Das, Subasish
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            NameFull: Khan, Md Nasim
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              Text: Feb2026
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              Y: 2026
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