Attention-based deep learning for analysis of pathology images and gene expression data in lung squamous premalignant lesions.

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Title: Attention-based deep learning for analysis of pathology images and gene expression data in lung squamous premalignant lesions.
Authors: Xu L; Faculty of Computing & Data Sciences, Boston University, Boston, MA, USA., Kefella Y; Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, 72 E. Concord Street, Boston, MA, 02118, USA., Zhang Y; Faculty of Computing & Data Sciences, Boston University, Boston, MA, USA., Conrad RD; Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, 72 E. Concord Street, Boston, MA, 02118, USA., Anderson KE; Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, 72 E. Concord Street, Boston, MA, 02118, USA., Krysan K; Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.; Jonsson Comprehensive Cancer Center at UCLA, Los Angeles, CA, USA., Liu G; Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, 72 E. Concord Street, Boston, MA, 02118, USA., Kane E; Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, 72 E. Concord Street, Boston, MA, 02118, USA., Pennycuick A; Lungs for Living Research Centre, UCL Respiratory, University College London, London, UK.; University College London Manchester Lung Cancer Centre of Excellence, London, UK., Merrick DT; Departement of Pathology, University of Colorado School of Medicine, Aurora, CO, USA., Janes SM; Lungs for Living Research Centre, UCL Respiratory, University College London, London, UK.; University College London Manchester Lung Cancer Centre of Excellence, London, UK., Reid ME; Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA., Burks EJ; Department of Pathology and Laboratory Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA., Billatos E; Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, 72 E. Concord Street, Boston, MA, 02118, USA., Mazzilli SA; Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, 72 E. Concord Street, Boston, MA, 02118, USA., Kolachalama VB; Faculty of Computing & Data Sciences, Boston University, Boston, MA, USA.; Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, 72 E. Concord Street, Boston, MA, 02118, USA.; Department of Computer Science, College of Arts & Sciences, Boston University, Boston, MA, USA., Beane JE; Faculty of Computing & Data Sciences, Boston University, Boston, MA, USA. jbeane@bu.edu.; Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, 72 E. Concord Street, Boston, MA, 02118, USA. jbeane@bu.edu.
Source: Genome medicine [Genome Med] 2026 Apr 08; Vol. 18 (1). Date of Electronic Publication: 2026 Apr 08.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101475844 Publication Model: Electronic Cited Medium: Internet ISSN: 1756-994X (Electronic) Linking ISSN: 1756994X NLM ISO Abbreviation: Genome Med Subsets: MEDLINE; In Process
Database: MEDLINE Ultimate
Description
ISSN:1756-994X
DOI:10.1186/s13073-026-01636-8