Application of Machine Learning Algorithms to Identify Optimal Candidates for Primary Tumor Resection in Patients with Metastatic Non-small Cell Neuroendocrine Tumors

Optimal Extent of Pulmonary Resection in Clinical Stage IA Non-Small Cell Lung Cancer

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Prognostic Significance of the Uncertain Resection in NSCLC

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Optimising Renal Tumour Management Through Artificial Intelligence Modules

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Establishment of a Feasibility Model for NOSE Surgery Based on Machine Learning

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Deep Learning Model Predicts Pathological Complete Response of Lung Cancer Following Neoadjuvant Immunochemotherapy

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Development and Demonstration of Intelligent Assessment Based on Multi-modal Information Fusion for Tumor Risk and Diagnosis and Treatment

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Postoperative Chronic Operation-related Symptoms After Minimally Invasive Lung Surgery

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Artificial Intelligence-based Model for the Prediction of Occult Lymph Node Metastasis and Improvement of Clinical Decision-making in Non-small Cell Lung Cancer

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HSI for Intersegmental Plane Identification During Sublobar Pulmonary Resections

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Prediction of Targeted Therapy Efficacy in EGFR-mutant Lung Cancer Patients Using AI-based Multimodal Data

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Multimodal Large Model-Driven Risk and Prognosis Assessment for Brain Metastases in Lung Cancer

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Real-world Clinical Outcomes of Patients With Early-stage Lung Cancer After the Surgery

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Surgical Strategy of NSCLC Patients After Neo-adjuvant or Induction Treatment

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Perioperative Treatment Outcomes of Early NSCLC

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Immune Treatment of Brain Metastasis of Lung Cancer Combined With Large-segmentation Precision Radiotherapy

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Selective Lymph Node Resection for Invasive Non-small Cell Lung Cancer With the CTR of 0.5-1 and the Diameter of ≤ 2 cm

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A Study of Real-world Treatment Patterns and Outcomes in Chinese Advanced NSCLC Patients Who Previously Received at Least 2 Line Treatments

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A Machine Learning Approach to Identify Patients With Resected Non-small-cell Lung Cancer With High Risk of Relapse

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A Perioperative Comprehensive Diagnosis and Treatment System for Lung Cancer in the Era of Neoadjuvant Immunotherapy

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Identify Prognostic Biomarkers of Lung Cancer

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A Radiomic Model for Risk of Local Recurrence and DFS for T3 and T4 Non-small Cell Lung Cancer

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Integrating Machine Learning for Prognostic Prediction in Stage I NSCLC by CT Images and Pathological Factors

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Machine Learning for Predicting and Managing Quality of Life in Lung Cancer Immunotherapy Patients

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Partial Pressure of Oxygen Control Method in Identification of Intersegmental Plane

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Pulmonary Ventilation/Perfusion Imaging for the Prediction of Postoperative Residual Pulmonary Function

NCT03357094 ·Status: UNKNOWN