Machine Learning-Based Integration Develops a Macrophage-Related Index for Predicting Prognosis and Immunotherapy Response in Lung Adenocarcinoma

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Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer

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Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients

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Macrophage Polarization States in the Tumor Microenvironment

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Identification of the pyroptosis‑related prognostic gene signature and the associated regulation axis in lung adenocarcinoma

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Machine learning-based pathomics signature could act as a novel prognostic marker for patients with clear cell renal cell carcinoma

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M2 macrophage-derived exosomes promote lung adenocarcinoma progression by delivering miR-942

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Machine learning in the prediction of depression treatment outcomes: a systematic review and meta-analysis

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Deep learning in cancer diagnosis, prognosis and treatment selection

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The Role of Tumor-Associated Macrophages in the Progression and Chemoresistance of Ovarian Cancer

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Development and validation of an immune‐related prognostic signature in lung adenocarcinoma

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STK11/LKB1 Mutations and PD-1 Inhibitor Resistance in KRAS -Mutant Lung Adenocarcinoma

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Development and Validation of a Novel Signature to Predict Overall Survival in “Driver Gene–negative” Lung Adenocarcinoma (LUAD): Results of a Multicenter Study

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Metabolic Competition in the Tumor Microenvironment Is a Driver of Cancer Progression

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Ectopic Activation of Germline and Placental Genes Identifies Aggressive Metastasis-Prone Lung Cancers

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Epidermal Growth Factor Receptor Tyrosine Kinase Defines Critical Prognostic Genes of Stage I Lung Adenocarcinoma

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Macrophage Diversity Enhances Tumor Progression and Metastasis

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