Lung Cancer Study Selection Process.xlsx

	A	B	C	D	E	F	G	H	I	J	K	L	M	N	O	P
1	Paper Title	QA1: Relevance to lung cancer prediction	QA2: Use of tabular/structured datasets	QA3: Machine learning model(s) used	QA4: Performance evaluation metrics reported	QA5: Feature selection and preprocessing methods discussed	QA6: Dataset availability and details	QA7: Comparison with other models	QA8: Explainability and interpretability methods	QA9: Challenges and limitations discussed	QA10: Recent publication (last 5-7 years)	Total Score	Data Extracted	Quartile	Note

2	Artificial Intelligence/Machine Learning in Respiratory Medicine and Potential Role in Asthma and COPD Diagnosis	Yes	No	No	Yes	Yes	No	Yes	No	Yes	Yes	6				0
3	Artificial intelligence-based prediction of clinical outcome in immunotherapy and targeted therapy of lung cancer	No	No	No	No	No	No	No	No	No	No	0				0
4	Application of Artificial Intelligence in Lung Cancer	Yes	No	No	No	No	No	No	No	No	Yes	2				0
5	Prediction of Effectiveness and Toxicities of Immune Checkpoint Inhibitors Using Real-World Patient Data	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	Yes	8	Yes	Q1		0
6	Predicting cancer using supervised machine learning: Mesothelioma	Yes	Yes	Yes	Yes	No	No	Yes	No	Yes	Yes	7	Yes	Q3		0
7	Predicting COVID-19 mortality with electronic medical records	No	No	No	No	No	No	No	No	No	No	0				0
8	Dosiomics and radiomics-based prediction of pneumonitis after radiotherapy and immune checkpoint inhibition: The relevance of fractionatio	Yes	Yes	Yes	Yes	Yes	No	Yes	No	Yes	Yes	8	Yes	Q1		0
9	A Machine Learning-Based Investigation of Gender-Specific Prognosis of Lung Cancers	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	10	Yes	Q1		0
10	Interpretable deep learning survival predictive tool for small cell lung cancer	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	10	Yes	Q2	Lung cancer Survival Prediction	0
11	Machine Learning and Real-World Data to Predict Lung Cancer Risk in Routine Care	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	10	Yes	Q1	Lung cancer risk prediction	0
12	A Heuristic Machine Learning-Based Optimization Technique to Predict Lung Cancer Patient Survival	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	9	Yes	Not Rated	Lung cancer Survival Prediction	0
13	An explainable machine learning framework for lung cancer hospital length of stay prediction.	Yes	No	No	No	No	No	No	No	No	No	1			Hospital Length Stay Prediction	0
14	Machine Learning-Assisted Recurrence Prediction for Patients With Early-Stage Non-Small-Cell Lung Cancer	Yes	No	No	No	No	No	No	No	No	No	1			probability of relapse in patients	0
15	Developing Artificial Intelligence Models for Extracting Oncologic Outcomes from Japanese Electronic Health Records	Yes	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	8				0
16	Prediction of Postoperative Lung Function in Lung Cancer Patients Using Machine Learning Models	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	9	Yes	Q2	Prediction of Lung Functions	0
17	Machine learning predictive models and risk factors for lymph node metastasis in non-small cell lung cancer	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	10	Yes	Q2		0
18	Boosting predictive models and augmenting patient data with relevant genomic and pathway information	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	9	Yes	Q1	relapse prediction	0
19	Clinical characteristics of adrenal insufficiency induced by pembrolizumab in non-small-cell lung cancer	No	No	No	No	No	No	No	No	Yes	No	1				0
20	Machine Learning-Based Prediction of Pulmonary Embolism Prognosis Using Nutritional and Inflammatory Indices	No	Yes	Yes	Yes	No	Yes	Yes	No	Yes	Yes	7				0
21	Performance of machine learning algorithms for lung cancer prediction: a comparative approach	Yes	Yes	Yes	Yes	Yes	No	Yes	No	Yes	Yes	8	Yes	Q1		0
22	Interpretable machine learning model for digital lung cancer prescreening in Chinese populations with missing data	Yes	Yes	Yes	Yes	No	No	No	Yes	No	Yes	6	Yes	Q1	Survival Prediction	0
23	A deep learning approach for overall survival prediction in lung cancer with missing values	Yes	Yes	Yes	No	No	No	No	Yes	Yes	Yes	6	Yes	Q1	Main Focus is working with missing data in training time without imputation	0
24	Clinical utility of an artificial intelligence radiomics-based tool for risk stratification of pulmonary nodules	No	Yes	No	Yes	No	No	Yes	No	Yes	Yes	5	No	Q1		0
25	Radiotranscriptomics of non-small cell lung carcinoma for assessing high-level clinical outcomes using a machine learning-derived multi-modal signature	No	Yes	No	No	No	No	Yes	Yes	No	Yes	4				0
26	Low muscle mass in lung cancer is associated with an inflammatory and immunosuppressive tumor microenvironment	No	Yes	No	No	No	Yes	No	No	No	Yes	3				0
27	Development of a predictive model of venous thromboembolism recurrence in anticoagulated cancer patients using machine learning	No	No	Yes	Yes	Yes	No	Yes	No	Yes	Yes	6			Works with VTE Recurrence	0
28	Application of unsupervised analysis techniques to lung cancer patient data	No	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	No	7			Works on Lung Cancer Survival	0
29	AI-Driven Synthetic Biology for Non-Small Cell Lung Cancer Drug Effectiveness-Cost Analysis in Intelligent Assisted Medical Systems	No	Yes	Yes	Yes	Yes	No	No	No	Yes	Yes	6				0
30	Classification prediction of early pulmonary nodes based on weighted gene correlation network analysis and machine learning	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	Yes	8			classification of early pulmonary nodules (a key aspect of lung cancer) using gene expression data and machine learning algorithms.	0
31	Digital health delivery in respiratory medicine: adjunct, replacement or cause for division?	Yes	No	Yes	No	No	No	No	No	Yes	Yes	4				0
32	Predicting post-discharge cancer surgery complications via telemonitoring of patient-reported outcomes and patient-generated health data	Yes	Yes	Yes	Yes	Yes	No	No	Yes	Yes	Yes	8	Yes	Q1	predicts post-discharge complications for cancer surgery patients	0
33	Simulation of a machine learning enabled learning health system for risk prediction using synthetic patient data	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	9	Yes	Q1		0
34	Machine learning approaches for prediction of early death among lung cancer patients with bone metastases using routine clinical characteristics: An analysis of 19,887 patients	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	9	Yes	Q1	predict 3 month mortality specifically among lung cancer patients with bone metastases	0
35	An Artificial Intelligence-Based Tool for Data Analysis and Prognosis in Cancer Patients: Results from the Clarify Study	Yes	Yes	Yes	No	Yes	No	No	Yes	Yes	Yes	7	Yes	Q1	prognosis, risk stratification, and survival analysis in lung cancer patients.	0
36	Comparison of nomogram and machine-learning methods for predicting the survival of non-small cell lung cancer patients	Yes	Yes	Yes	Yes	Yes	No	Yes	No	Yes	Yes	8	Yes	Q2	predicting the survival of non-small cell lung cancer patients	0
37	Prognostic value of plasma microRNAs for non-small cell lung cancer based on data mining models	No	No	No	No	No	No	No	No	No	No	0				0
38	Synthetic Tabular Data Based on Generative Adversarial Networks in Health Care: Generation and Validation Using the Divide-and-Conquer Strategy	No	No	No	No	No	No	No	No	No	No	0			generate Structured Tabular Data based on the GAN algorithm, while preserving data with logical relationships.	0
39	Clinical Characteristics, Care Trajectories and Mortality Rate of SARS-CoV-2 Infected Cancer Patients: A Multicenter Cohort Study	Yes	No	No	No	No	No	No	No	No	No	1			assess the rate of COVID-19 in hospitalized cancer patients	0
40	A prediction model based on high serum SH2B1 in patients with non-small cell lung cancer	No	Yes	No	Yes	Yes	No	No	Yes	Yes	Yes	6			investigates the predictive value of serum SH2B1 levels in NSCLC patients	0
41	Serum pleiotrophin as a diagnostic and prognostic marker for small cell lung cancer	Yes	Yes	No	Yes	No	No	No	No	Yes	No	4			investigates the diagnostic and prognostic value of serum pleiotrophin (PTN) as a biomarker for SCLC	0
42	Radiomics and Clinical Data for the Diagnosis of Incidental Pulmonary Nodules and Lung Cancer Screening: Radiolung Integrative Predictive Model	Yes	No	Yes	Yes	Yes	No	Yes	No	Yes	Yes	7			diagnosis of pulmonary nodules (PN) and lung cancer screening using radiomics and clinical data	0
43	A new tool to predict lung cancer based on risk factors	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	9			development of a tool for early prediction of lung cancer based on risk factors	0
44	Computational prediction of diagnosis and feature selection on mesothelioma patient health records	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	9				0
45	Prediction of Brain Metastases Development in Patients With Lung Cancer by Explainable Artificial Intelligence From Electronic Health Records	No	Yes	Yes	Yes	Yes	No	Yes	Yes	Yes	Yes	8			predicting brain metastases (BM) in patients with lung cancer using electronic health record (EHR)	0
46	Integration of Clinical Information and Imputed Aneuploidy Scores to Enhance Relapse Prediction in Early Stage Lung Cancer Patients	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	9			e Relapse Prediction in Early Stage Lung Cancer Patients	0
47	Synergy between imputed genetic pathway and clinical information for predicting recurrence in early stage non-small cell lung cancer	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	9			predicting recurrence in early-stage non-small cell lung cancer (NSCLC)	0
48	Interpretable prediction of cardiopulmonary complications after non-small cell lung cancer surgery based on machine learning and SHapley additive exPlanations	No	Yes	Yes	Yes	Yes	No	Yes	Yes	Yes	Yes	8			predicting cardiopulmonary complications after non-small cell lung cancer (NSCLC) surgery	0
49	Multi-Class Neural Networks to Predict Lung Cancer	Yes	Yes	Yes	Yes	Yes	Yes	No	No	No	Yes	7	Yes	Q1		0
50	Identification of non-small cell lung cancer with chronic obstructive pulmonary disease using clinical symptoms and routine examination: a retrospective study	Yes	Yes	Yes	Yes	Yes	No	Yes	No	Yes	Yes	8	Yes	Q2		0
51	Single Modality vs. Multimodality: What Works Best for Lung Cancer Screening?	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	9	Yes	Q1		0
52	Analysis of the Causes of Solitary Pulmonary Nodule Misdiagnosed as Lung Cancer by Using Artificial Intelligence: A Retrospective Study at a Single Center	No	No	Yes	Yes	No	No	Yes	No	Yes	Yes	5			focuses on the misdiagnosis of solitary pulmonary nodules (SPNs) as lung cancer using AI	0
53	Exploring the efficacy of artificial neural networks in predicting lung cancer recurrence: a retrospective study based on patient records	Yes	Yes	Yes	Yes	Yes	No	No	Yes	Yes	Yes	8	Yes	Q1		0
54	Recurrence prediction of lung adenocarcinoma using an immune gene expression and clinical data trained and validated support vector machine classifier	Yes	Yes	Yes	Yes	Yes	No	No	No	Yes	Yes	7	Yes	Q1	predicting the recurrence of lung adenocarcinoma (LUAD	0
55	Outcomes and prognosis of non-small cell lung cancer patients who underwent curable surgery: a protocol for a real-world, retrospective, population-based and nationwide Chinese National Lung Cancer Cohort (CNLCC) study	Yes	Yes	No	No	Yes	No	No	No	Yes	Yes	5			study focuses on non-small cell lung cancer (NSCLC) patients who underwent curable surgery, and it aims to explore factors influencing outcomes and prognosis	0
56	A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data	No	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	8			Predict Lung Cancer Long-Term Survival	0
57	Predicting the efficacy of immune checkpoint inhibitors monotherapy in advanced non-small cell lung cancer: a machine learning method based on multidimensional data	No	Yes	Yes	Yes	Yes	No	No	Yes	Yes	Yes	7			predicting the efficacy of immune checkpoint inhibitors (ICIs) monotherapy in advanced non-small cell lung cancer (NSCLC)	0
58	Primary tumor type prediction based on US nationwide genomic profiling data in 13,522 patients	No	Yes	Yes	Yes	Yes	No	No	Yes	Yes	Yes	7			predicting primary tumor types	0
59	Fibroblast Growth Factor 11 Enables Tumor Cell Immune Escape by Promoting T Cell Exhaustion and Predicts Poor Prognosis in Patients with Lung Adenocarcinoma	Yes	Yes	No	No	No	Yes	No	No	Yes	Yes	5			The paper focuses on lung adenocarcinoma, a type of lung cancer, and investigates the role of FGF11 in tumor immune escape and prognosis	0
60	Effect of osimertinib in treating patients with first-generation EGFR-TKI-resistant advanced non-small cell lung cancer and prognostic analysis	Yes	Yes	No	No	No	No	No	No	Yes	Yes	4			efficacy and safety of Osimertinib in treating advanced non-small cell lung cancer (NSCLC)	0
61	Learning to detect chest radiographs containing pulmonary lesions using visual attention networks	Yes	No	Yes	Yes	Yes	No	Yes	Yes	Yes	Yes	8			assessing the predictive accuracy of lung cancer, metastases, and benign lesions using an AI-driven computer-aided diagnosis system	0
62	Assessing the predictive accuracy of lung cancer, metastases, and benign lesions using an artificial intelligence-driven computer aided diagnosis system	Yes	No	Yes	Yes	No	No	Yes	No	Yes	Yes	6				0
63	Development of a "meta-model" to address missing data, predict patient-specific cancer survival and provide a foundation for clinical decision support	Yes	Yes	Yes	Yes	Yes	No	Yes	No	Yes	Yes	8	Yes	Q1	development of a meta-model for predicting patient-specific cancer survival	0
64	Body composition radiomic features as a predictor of survival in patients with non-small cellular lung carcinoma: A multicenter retrospective study	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	10	Yes	Q2	Survival Prediction	0
65	Clinical decision support algorithm based on machine learning to assess the clinical response to anti-programmed death-1 therapy in patients with non-small-cell lung cancer	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	Yes	Yes	9	Yes	Q1	clinical response to anti-PD-1 therapy in patients with non-small-cell lung cancer (NSCLC)	0
66	Transformer-based deep learning model for the diagnosis of suspected lung cancer in primary care based on electronic health record data	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	Yes	Yes	9	Yes	Q1		0
67	Applying Data Science methods and tools to unveil healthcare use of lung cancer patients in a teaching hospital in Spain	Yes	Yes	No	No	Yes	No	No	No	Yes	Yes	5			analyzing healthcare use by lung cancer patients	0
68	A Prognostic 14-Gene Expression Signature for Lung Adenocarcinoma: A Study Based on TCGA Data Mining	No	No	No	No	No	No	No	No	No	No	0			A Study Based on TCGA Data Mining	0
69	Performance Comparison of 10 State-of-the-Art Machine Learning Algorithms for Outcome Prediction Modeling of Radiation-Induced Toxicity	No	No	No	No	No	No	No	No	No	No	0				0
70	Establishment and Validation of a Ferroptosis-Related Gene Signature to Predict Overall Survival in Lung Adenocarcinoma	Yes	Yes	No	No	No	Yes	Yes	No	Yes	Yes	6			RNA sequencing data and relevant clinical data from The Cancer Genome Atlas (TCGA) dataset and Gene Expression Omnibus (GEO) dataset	0
71	Nonlinear association between PD-L1 expression levels and the risk of postoperative recurrence in non-small cell lung cancer	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	Yes	Yes	9	Yes	Q1	predicting postoperative recurrence in non-small cell lung cancer (NSCLC)	0
72	AKIP1 expression in tumor tissue as a new biomarker for disease monitoring and prognosis in non-small cell lung cancer: Results of a retrospective study	No	No	No	No	No	No	No	No	Yes	Yes	2			investigates the role of AKIP1 as a biomarker for disease monitoring and prognosis	0
73	Prediction of the 1-Year Risk of Incident Lung Cancer: Prospective Study Using Electronic Health Records from the State of Maine	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	Yes	No	8	Yes	Q1		0
74	Automated derivation of diagnostic criteria for lung cancer using natural language processing on electronic health records: a pilot study	No	No	No	No	No	No	No	No	No	No	0				0
75	AI diagnostics in bone oncology for predicting bone metastasis in lung cancer patients using DenseNet-264 deep learning model and radiomics	Yes	No	Yes	Yes	Yes	No	Yes	No	No	Yes	6			predict bone metastasis in lung cancer patients	0
76	Molecular characterization of clinical responses to PD-1/PD-L1 inhibitors in non-small cell lung cancer: Predictive value of multidimensional immunomarker detection for the efficacy of PD-1 inhibitors in Chinese patients	Yes	Yes	No	No	Yes	No	No	No	Yes	Yes	5			predicting the efficacy of PD-1/PD-L1 inhibitors in non-small cell lung cancer (NSCLC) patients,	0
77	Exploring the impact of HDL and LMNA gene expression on immunotherapy outcomes in NSCLC: a comprehensive analysis using clinical & gene data	No	No	No	No	No	No	No	No	No	No	0			impact of peripheral lipid levels on the efficacy of	0
78	Automated Diagnosis of Bone Metastasis by Classifying Bone Scintigrams Using a Self-defined Deep Learning Model	No	No	No	No	No	No	No	No	No	No	0			immune checkpoint inhibitor therapy in non-small cell lung cancer (NSCLC)	0
79	Cancer adjuvant chemotherapy strategic classification by artificial neural network with gene expression data: An example for non-small cell lung cancer	No	No	No	No	No	No	No	No	No	No	0			patient	0
80	Development of an AI model for predicting hypoxia status and prognosis in non-small cell lung cancer using multi-modal data	No	No	No	No	No	No	No	No	No	No	0				0
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