Research graph
References from Utilizing Machine Learning to Identify Multimodal Signatures for Patients Who Would Benefit from the Addition of Tremelimumab to Durvalumab and Chemotherapy (TRIDENT). Local targets link to admitted publications; unresolved targets remain external evidence.
Next-generation immunotherapy: igniting new hope for lung cancer
10.1177/17588359241302021 · 2024 · External reference
Non-oncogene-addicted metastatic non-small-cell lung cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up
10.1016/j.annonc.2022.12.013 · 2023 · External reference
Immunotherapy for advanced non-small cell lung cancer: a decade of progress
10.1200/edbk_321483 · 2021 · External reference
Durvalumab with or without tremelimumab in combination with chemotherapy as first-line therapy for metastatic non-small-cell lung cancer: the phase III POSEIDON study
10.1200/jco.22.00975 · 2023 · External reference
Pembrolizumab plus pemetrexed and platinum in nonsquamous non-small-cell lung cancer: 5-year outcomes from the phase 3 KEYNOTE-189 study
10.1200/jco.22.01989 · 2023 · External reference
Pembrolizumab plus chemotherapy in squamous non-small-cell lung cancer: 5-year update of the phase III KEYNOTE-407 study
10.1200/jco.22.01990 · 2023 · External reference
Five-year survival outcomes with nivolumab plus ipilimumab versus chemotherapy as first-line treatment for metastatic non-small-cell lung cancer in CheckMate 227
10.1200/jco.22.01503 · 2023 · External reference
Five-year outcomes with pembrolizumab versus chemotherapy as first-line therapy in patients with non-small-cell lung cancer and programmed death ligand-1 tumor proportion score ≥1% in the KEYNOTE-042 study
10.1200/jco.21.02885 · 2023 · External reference
Five-year outcomes with pembrolizumab versus chemotherapy for metastatic non-small-cell lung cancer with PD-L1 tumor poportion score ≥50
10.1200/jco.21.00174 · 2021 · External reference
Durvalumab with or without tremelimumab in combination with chemotherapy in first-line metastatic NSCLC: five-year overall survival outcomes from the phase 3 POSEIDON trial
10.1016/j.jtho.2024.09.1381 · 2025 · External reference
Five-year outcomes with first-line nivolumab plus ipilimumab with 2 cycles of chemotherapy versus 4 cycles of chemotherapy alone in patients with metastatic non-small cell lung cancer in the randomized CheckMate 9LA trial
10.1016/j.ejca.2024.114296 · 2024 · External reference
Associations of tissue tumor mutational burden and mutational status with clinical outcomes with pembrolizumab plus chemotherapy versus chemotherapy for metastatic NSCLC
10.1016/j.jtocrr.2022.100431 · 2023 · External reference
Effects of co-occurring genomic alterations on outcomes in patients with KRAS-mutant non-small cell lung cancer
10.1158/1078-0432.ccr-17-1841 · 2018 · External reference
STK11 and KEAP1 mutations as prognostic biomarkers in an observational real-world lung adenocarcinoma cohort
10.1136/esmoopen-2020-000706 · 2020 · External reference
Co-occurring genomic alterations define major subsets of KRAS-mutant lung adenocarcinoma with distinct biology, immune profiles, and therapeutic vulnerabilities
10.1158/2159-8290.cd-14-1236 · 2015 · External reference
STK11/LKB1 mutations and PD-1 inhibitor resistance in KRAS-mutant lung adenocarcinoma
10.1158/2159-8290.cd-18-0099 · 2018 · External reference
Clinical efficacy of atezolizumab plus bevacizumab and chemotherapy in KRAS-mutated non-small cell lung cancer with STK11, KEAP1, or TP53 comutations: subgroup results from the phase III IMpower150 trial
10.1136/jitc-2021-003027 · 2022 · External reference
CTLA4 blockade abrogates KEAP1/STK11-related resistance to PD-(L)1 inhibitors
10.1038/s41586-024-07943-7 · 2024 · External reference
Cancer biomarkers: emerging trends and clinical implications for personalized treatment
10.1016/j.cell.2024.02.041 · 2024 · External reference
Precision medicine: disease subtyping and tailored treatment
10.3390/cancers15153837 · 2023 · External reference
A review of radiomics and genomics applications in cancers: the way towards precision medicine
10.1186/s13014-022-02192-2 · 2022 · External reference
Radiomic signature accurately predicts the risk of metastatic dissemination in late-stage non-small cell lung cancer
10.21037/tlcr-23-60 · 2023 · External reference
Predicting cancer outcomes with radiomics and artificial intelligence in radiology
10.1038/s41571-021-00560-7 · 2022 · External reference
A framework for artificial intelligence in cancer research and precision oncology
10.1038/s41698-023-00383-y · 2023 · External reference
The AI revolution: how multimodal intelligence will reshape the oncology ecosystem
10.1038/s44387-025-00044-4 · 2025 · External reference
The age of foundation models
10.1038/s41571-024-00941-8 · 2024 · External reference
Artificial intelligence in oncology: current landscape, challenges, and future directions
10.1158/2159-8290.cd-23-1199 · 2024 · External reference
LORIS robustly predicts patient outcomes with immune checkpoint blockade therapy using common clinical, pathologic and genomic features
10.1038/s43018-024-00772-7 · 2024 · External reference
The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping
10.1148/radiol.2020191145 · 2020 · External reference
Unresolved reference
2024 · External reference
Statistics and causal inference
10.1080/01621459.1986.10478354 · 1986 · External reference
Estimating individual treatment effect on disability progression in multiple sclerosis using deep learning
10.1038/s41467-022-33269-x · 2022 · External reference
Do machine learning methods lead to similar individualized treatment rules? A comparison study on real data
10.1002/sim.10059 · 2024 · External reference
Effectively selecting a target population for a future comparative study
10.1080/01621459.2013.770705 · 2013 · External reference
Missing value estimation methods for DNA microarrays
10.1093/bioinformatics/17.6.520 · 2001 · External reference
Limits of estimating heterogeneous treatment effects: guidelines for practical algorithm design
2018 · External reference
Inference for the generalization error
10.1023/a:1024068626366 · 2003 · External reference
Interpretable machine learning
2020 · External reference
NSCLC biomarkers to predict response to immunotherapy with checkpoint inhibitors (ICI): from the cells to in vivo images
10.3390/cancers13184543 · 2021 · External reference
Tumour burden and efficacy of immune-checkpoint inhibitors
10.1038/s41571-021-00564-3 · 2022 · External reference
Prediction of checkpoint inhibitor immunotherapy efficacy for cancer using routine blood tests and clinical data
10.1038/s41591-024-03398-5 · 2025 · External reference
The predictive approaches to treatment effect heterogeneity (PATH) statement
10.7326/m18-3667 · 2020 · External reference
1916P AI-powered multimodal prediction of response in 1L non-mutated mNSCLC using routine pre-treatment data (DEEP Lung-IV)
10.1016/j.annonc.2025.08.2540 · 2025 · External reference
Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study
10.1016/s2589-7500(23)00082-1 · 2023 · External reference
Rationale and design for a phase IIIb trial of first-line tremelimumab plus durvalumab versus pembrolizumab, in combination with chemotherapy, in patients with non-squamous metastatic non-small-cell lung cancer and mutations or co-mutations in STK11, KEAP1, or KRAS: the TRITON study
10.1177/17588359251386611 · 2025 · External reference
Cross-validation: what does it estimate and how well does it do it?
10.1080/01621459.2023.2197686 · 2024 · External reference
Consensus features nested cross-validation
10.1093/bioinformatics/btaa046 · 2020 · External reference
Dissecting the clinicopathologic, genomic, and immunophenotypic correlates of KRAS(G12D)-mutated non-small-cell lung cancer
10.1016/j.annonc.2022.07.005 · 2022 · External reference
