{"id":"doi:10.1016/j.aap.2018.10.015","kind":"article","title":"A spatiotemporal deep learning approach for citywide short-term crash risk prediction with multi-source data","authors":["Jie Bao","Pan Liu","Satish V. Ukkusuri"],"author_count":3,"year":2018,"published":"2018-11-01","venue":"Accident Analysis & Prevention","cited_by":279,"doi":"10.1016/j.aap.2018.10.015","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.aap.2018.10.015","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.aap.2018.10.015","updated":null,"pmid":"30390519","pmcid":null,"openalex_id":"W2898788157","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"retracted":false,"peer_reviewed":null,"categories":["Traffic and Road Safety"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0).","topics":[{"slug":"ai-weather-climate","name":"AI Weather & Climate Modeling","domain_slug":"energy"}],"cited_in_dossiers":[]}