<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Bailey MJ</submitter><funding>NICHD NIH HHS</funding><funding>NIA NIH HHS</funding><pagination>101474</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9912950</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>87</volume><pubmed_abstract>The demographic and epidemiological transitions of the past 200 years are well documented at an aggregate level. Understanding differences in individual and group risks for mortality during these transitions requires linkage between demographic data and detailed individual cause of death information. This paper describes the digitization of almost 185,000 causes of death for Ohio to supplement demographic information in the Longitudinal, Intergenerational Family Electronic Micro-database (LIFE-M). To extract causes of death, our methodology combines handwriting recognition, extensive data cleaning algorithms, and the semi-automated classification of causes of death into International Classification of Diseases (ICD) codes. Our procedures are adaptable to other collections of handwritten da</pubmed_abstract><journal>Explorations in economic history</journal><pubmed_title>Breathing new life into death certificates: Extracting handwritten cause of death in the LIFE-M project.</pubmed_title><pmcid>PMC9912950</pmcid><funding_grant_id>P2C HD041023</funding_grant_id><funding_grant_id>R24 HD041028</funding_grant_id><funding_grant_id>P2C HD041022</funding_grant_id><funding_grant_id>R01 AG057704</funding_grant_id><funding_grant_id>P2C HD041028</funding_grant_id><funding_grant_id>R21 AG056912</funding_grant_id><funding_grant_id>P30 AG012846</funding_grant_id><pubmed_authors>Bailey MJ</pubmed_authors><pubmed_authors>Roberts E</pubmed_authors><pubmed_authors>Price J</pubmed_authors><pubmed_authors>Spector L</pubmed_authors><pubmed_authors>Zhang M</pubmed_authors><pubmed_authors>Leonard SH</pubmed_authors></additional><is_claimable>false</is_claimable><name>Breathing new life into death certificates: Extracting handwritten cause of death in the LIFE-M project.</name><description>The demographic and epidemiological transitions of the past 200 years are well documented at an aggregate level. Understanding differences in individual and group risks for mortality during these transitions requires linkage between demographic data and detailed individual cause of death information. This paper describes the digitization of almost 185,000 causes of death for Ohio to supplement demographic information in the Longitudinal, Intergenerational Family Electronic Micro-database (LIFE-M). To extract causes of death, our methodology combines handwriting recognition, extensive data cleaning algorithms, and the semi-automated classification of causes of death into International Classification of Diseases (ICD) codes. Our procedures are adaptable to other collections of handwritten da</description><dates><release>2023-01-01T00:00:00Z</release><publication>2023 Jan</publication><modification>2025-04-04T03:01:19.071Z</modification><creation>2025-04-04T03:01:19.071Z</creation></dates><accession>S-EPMC9912950</accession><cross_references><pubmed>36778518</pubmed><doi>10.1016/j.eeh.2022.101474</doi></cross_references></HashMap>