<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>15(3)</volume><submitter>Yao B</submitter><journal>Journal of Cancer</journal><pagination>737-746</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC10777045</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>A Novel Model Using Serum Thymidine Kinase 1 and Low-dose Computed Tomography Parameters to Predict Three-year Lung Cancer Risk in People with Pulmonary Nodules: A Retrospective Study</pubmed_title><pmcid>PMC10777045</pmcid><pubmed_authors>He E</pubmed_authors><pubmed_authors>Li X</pubmed_authors><pubmed_authors>Li J</pubmed_authors><pubmed_authors>Hong H</pubmed_authors><pubmed_authors>Huang X</pubmed_authors><pubmed_authors>Skog S</pubmed_authors><pubmed_authors>Yao B</pubmed_authors><pubmed_authors>Zhang M</pubmed_authors><pubmed_authors>Wang H</pubmed_authors><pubmed_authors>Wu F</pubmed_authors><pubmed_authors>Zhou J</pubmed_authors></additional><is_claimable>false</is_claimable><name>A Novel Model Using Serum Thymidine Kinase 1 and Low-dose Computed Tomography Parameters to Predict Three-year Lung Cancer Risk in People with Pulmonary Nodules: A Retrospective Study</name><description/><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Jan</publication><modification>2025-04-22T18:15:08.062Z</modification><creation>2024-12-04T13:28:38.394Z</creation></dates><accession>S-EPMC10777045</accession><cross_references/></HashMap>