In one paragraphArticle in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
17 authors.
Davide DalfovoOncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine, University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Helmholtz-Zentrum Dresden-Rossendorf, 01067 Dresden, Germany.
Carolina SassorossiUnit of Thoracic Surgery, Catholic University of the Sacred Heart, 00168 Rome, Italy.ORCID 0000-0003-4654-1577 Elisa De PaolisDepartmental Unit of Molecular and Genomic Diagnostics, Genomics Core Facility, Gemelli Science and Technology Park (G-STeP), A. Gemelli University Hospital Foundation IRCCS, 00168 Rome, Italy.
Annalisa CampanellaUnit of Thoracic Surgery, Catholic University of the Sacred Heart, 00168 Rome, Italy.
Leonardo Petracca CiavarellaUnit of Thoracic Surgery, Catholic University of the Sacred Heart, 00168 Rome, Italy.ORCID 0000-0002-9659-1014 Luca BoldriniAdvanced Radiotherapy Center, A. Gemelli University Hospital Foundation IRCCS, 00168 Rome, Italy.ORCID 0000-0002-5631-1575 Esther G C TroostOncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine, University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Helmholtz-Zentrum Dresden-Rossendorf, 01067 Dresden, Germany.
Róza ÁdányELKH-DE Public Health Research Group, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, 4001 Debrecen, Hungary.ORCID 0000-0002-9679-6669 Núria FarréInstitut de Recerca de L'Hospital de la Santa Creu i Sant Pau (IR-HSCSP), 08001 Barcelona, Spain.
Ece ÖztürkSchool of Medicine, Turkey and Koç University Research Center for Translational Medicine (KUTTAM), Koç University, Istanbul 34450, Turkey.ORCID 0000-0001-8635-0279 Angelo MinucciDepartmental Unit of Molecular and Genomic Diagnostics, Genomics Core Facility, Gemelli Science and Technology Park (G-STeP), A. Gemelli University Hospital Foundation IRCCS, 00168 Rome, Italy.ORCID 0000-0002-0833-4334 Rocco TrisoliniInterventional Pulmonology Unit, A. Gemelli University Hospital Foundation IRCCS, 00168 Rome, Italy.ORCID 0000-0002-1067-4696 Emilio BriaMedical Oncology, A. Gemelli University Hospital Foundation IRCCS, Largo a. Gemelli 8, 00168 Rome, Italy.
Steffen LöckOncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine, University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Helmholtz-Zentrum Dresden-Rossendorf, 01067 Dresden, Germany.ORCID 0000-0002-7017-3738 Stefano MargaritoraUnit of Thoracic Surgery, Catholic University of the Sacred Heart, 00168 Rome, Italy.
Filippo LococoUnit of Thoracic Surgery, Catholic University of the Sacred Heart, 00168 Rome, Italy.
Funding
No grant is acknowledged in the PubMed record.
6 · The paper itselfAbstract
Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality globally. While multi-modal artificial intelligence (AI) models offer significant predictive potential, their translation into routine clinical practice is delayed by the "black box" nature of complex algorithms and the fragmentation of heterogeneous data. We present LANTERN-XGB, a hierarchical machine learning workflow designed to bridge this gap by generating interpretable "digital human avatars" for precision oncology. The methodology employs a multi-stage scalable tree boosting system (XGBoost) architecture utilizing shapley additive explanations (SHAP) for rigorous hierarchical feature selection, missing value management, and patient-specific decision support. The workflow was developed and benchmarked using a retrospective cohort of 437 patients with clinical N0 NSCLC, followed by validation on a prospective dataset (n = 100) and an independent external dataset (
Indexed as
Carcinoma, Non-Small-Cell LungClinical Decision-MakingLung NeoplasmsMachine LearningBoosting Machine Learning AlgorithmsFemaleHumansLymphatic MetastasisRetrospective Studiesartificial intelligencelung cancermulti-modal integrationprecision oncologyradiogenomics
Identifiers
PMID41977313
PMCPMC13074020
What OpenQuestion holds
Textmetadata
LicenceCC BY
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