scholarly journals A New Method for Syndrome Classification of Non-Small-Cell Lung Cancer Based on Data of Tongue and Pulse with Machine Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yu-lin Shi ◽  
Jia-yi Liu ◽  
Xiao-juan Hu ◽  
Li-ping Tu ◽  
Ji Cui ◽  
...  
Keyword(s):  
Machine Learning ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Deficiency Syndrome ◽  
Small Cell ◽  
Small Cell Lung ◽  
Yin Deficiency ◽  
Significant Difference ◽  
Syndrome Classification

Objective. To explore the data characteristics of tongue and pulse of non-small-cell lung cancer with Qi deficiency syndrome and Yin deficiency syndrome, establish syndrome classification model based on data of tongue and pulse by using machine learning methods, and evaluate the feasibility of syndrome classification based on data of tongue and pulse. Methods. We collected tongue and pulse of non-small-cell lung cancer patients with Qi deficiency syndrome ( n = 163 ), patients with Yin deficiency syndrome ( n = 174 ), and healthy controls ( n = 185 ) using intelligent tongue diagnosis analysis instrument and pulse diagnosis analysis instrument, respectively. We described the characteristics and examined the correlation of data of tongue and pulse. Four machine learning methods, namely, random forest, logistic regression, support vector machine, and neural network, were used to establish the classification models based on symptom, tongue and pulse, and symptom and tongue and pulse, respectively. Results. Significant difference indices of tongue diagnosis between Qi deficiency syndrome and Yin deficiency syndrome were TB-a, TB-S, TB-Cr, TC-a, TC-S, TC-Cr, perAll, and the tongue coating texture indices including TC-CON, TC-ASM, TC-MEAN, and TC-ENT. Significant difference indices of pulse diagnosis were t4 and t5. The classification performance of each model based on different datasets was as follows: tongue and pulse < symptom < symptom and tongue and pulse. The neural network model had a better classification performance for symptom and tongue and pulse datasets, with an area under the ROC curves and accuracy rate which were 0.9401 and 0.8806. Conclusions. It was feasible to use tongue data and pulse data as one of the objective diagnostic basis in Qi deficiency syndrome and Yin deficiency syndrome of non-small-cell lung cancer.

Study on the syndrome characteristics and classification model of non-small cell lung cancer based on tongue and pulse data (Preprint)

2021 ◽  
Author(s):  
Yulin Shi ◽  
Jiayi Liu ◽  
Xiaojuan Hu ◽  
Liping Tu ◽  
Ji Cui ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Deficiency Syndrome ◽  
Small Cell ◽  
Classification Model ◽  
Syndrome Differentiation ◽  
Small Cell Lung ◽  
Yin Deficiency ◽  
Significant Difference

BACKGROUND Lung cancer is a common malignant tumor that affects people's health seriously. Traditional Chinese medicine (TCM) is one of the effective methods for the treatment of advanced lung cancer, accurate TCM syndrome differentiation is essential to treatment. When the symptoms are not obvious, the traditional symptom-based syndrome differentiation cannot be carried out. There is a close relationship between syndrom and index of western medicine, the combination of micro index and macro symptom can assist syndrome differentiation effectively. OBJECTIVE To explore the characteristics of tongue and pulse data of non-small cell lung cancer (NSCLC) with Qi deficiency syndrome and Yin deficiency syndrome, and to establish syndromes classification model based on tongue and pulse data by using machine learning method, and to evaluate the feasibility of the model. METHODS Tongue and pulse data of non-small cell lung cancer (NSCLC) patients with Qi deficiency syndrome (n=163), patients with Yin deficiency syndrome (n=174) and healthy controls (n=185) were collected by using intelligent Tongue and Face Diagnosis Analysis-1 instrument and Pulse Diagnosis Analysis-1 instrument, respectively. The characteristics of tongue and pulse data were analyzed, the correlation analysis was also made on tongue and pulse data. And four machine learning methods, namely Random Forest, Logistic Regression, Support Vector Machine and Neural Network, were used to establish the classification models based on symptoms, tongue & pulse data, and symptoms & tongue & pulse data, respectively. RESULTS Significant difference indexes of tongue diagnosis between Qi deficiency syndrome and Yin deficiency syndrome were TB-a, TB-S, TB-Cr, TC-a, TC-S, TC-Cr, perAll and the tongue coating texture indexes including TC-Con, TC-ASM, TC-MEAN, and TC-ENT. Significant difference indexes of pulse diagnosis were t4 and t5. The classification performance of each model based on different data sets was as follows: model of tongue & pulse data <model of symptom < model of symptom & tongue & pulse data. The Neural Network model had a better classification performance for the symptom & tongue & pulse data, with an area under the ROC curve and accuracy rate were 0.9401 and 0.8806. CONCLUSIONS This study explored the characteristics of tongue and pulse data of NSCLC with Qi deficiency syndrome and Yin deficiency syndrome, and established syndromes classification model. It was feasible to use tongue and pulse data as one of the objective diagnostic indexes in Qi deficiency syndrome and Yin deficiency syndrome of NSCLC. CLINICALTRIAL Trial registration number: ChiCTR1900026008; ChiCTR-IOR-15006502 Date of registration: Jun. 04th, 2015 URL of trial registry record: http://www.chictr.org.cn/showprojen.aspx?proj=11119; http://www.chictr.org.cn/edit.aspx?pid=38828&htm=4 (This is a retrospective registration)

scholarly journals Digital Pathology and PD-L1 Testing in Non Small Cell Lung Cancer: A Workshop Record

Cancers ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1800 ◽  
Author(s):  
Fabio Pagni ◽  
Umberto Malapelle ◽  
Claudio Doglioni ◽  
Gabriella Fontanini ◽  
Filippo Fraggetta ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Gold Standard ◽  
Digital Pathology ◽  
Small Cell ◽  
Small Cell Lung ◽  
Significant Difference ◽  
Standard Quality ◽  
A Minor

A meeting among expert pathologists was held in 2019 in Rome to verify the results of the previous harmonization efforts on the PD-L1 immunohistochemical testing by scoring a representative series of non-small cell lung cancer (NSCLC) digital slides. The current paper shows the results of this digital experimental meeting and the expertise achieved by the community of Italian pathologists. PD-L1 protein expression was determined using tumor proportion score (TPS), i.e., the percentage of viable tumor cells showing partial or complete membrane staining at any intensity. The gold standard was defined as the final PD-L1 score formulated by a panel of seven lung committed pathologists. PD-L1 status was clustered in three categories, namely negative (TPS < 1), low (TPS 1–49%), and high (TPS ≥ 50%). In 23 cases (71.9%) PD-L1 staining was performed using the companion diagnostic 22C3 pharmDx kit on Dako Autostainer, while in nine (28.1%) cases it was performed using the SP263 Ventana kit on BenchMark platform. A complete PD-L1 scoring agreement between the panel of experts and the participants was reached in 57.1% of cases, whereas a minor disagreement in 16.1% of cases was recorded. Italian pathologists performed best in strong positive cases (i.e., tumor proportion score TPS > 50%), whereas only 10.8% of disagreement with the gold standard was observed, and 55.6% regarded a single challenging case. The worst performance was achieved in the negative cases, with 32.0% disagreement. A significant difference resulted from the analysis of the data separated by the different clones used: 22.3% and 38.1% disagreement (p = 0.01) was found in the group of cases analyzed by 22C3 and SP263 antibody clones, respectively. In conclusion, this workshop record proposed the application of a digital pathology platform to share controversial cases in educational meetings as an alternative possibility for improving the interpretation and reporting of specific histological tools. Due to the crucial role of PD-L1 TPS for the selection of patients for immunotherapy, the identification of unconventional approaches as virtual slides to focus experiences and give more detailed practical verifications of the standard quality reached may be a considerable option.

Transient asymptomatic pulmonary opacities and interstitial lung disease in EGFR-mutated non-small cell lung cancer treated with osimertinib

2021 ◽  
pp. 030089162110478
Author(s):  
Gianluca Taronna ◽  
Alessandro Leonetti ◽  
Filippo Gustavo Dall’Olio ◽  
Alessandro Rizzo ◽  
Claudia Parisi ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Clinical Outcomes ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Clinical Variable ◽  
Small Cell Lung ◽  
Significant Difference ◽  
Egfr Mutated

Introduction: Osimertinib is a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) approved as first-line therapy for advanced EGFR-mutated non-small cell lung cancer (NSCLC). Some osimertinib-related interstitial lung diseases (ILDs) were shown to be transient, called transient asymptomatic pulmonary opacities (TAPO)—clinically benign pulmonary opacities that resolve despite continued osimertinib treatment—and are not associated with the clinical manifestations of typical TKI-associated ILDs. Methods: In this multicentric study, we retrospectively analyzed 92 patients with EGFR-mutated NSCLC treated with osimertinib. Computed tomography (CT) examinations were reviewed by two radiologists and TAPO were classified according to radiologic pattern. We also analyzed associations between TAPO and patients’ clinical variables and compared clinical outcomes (time to treatment failure and overall survival) for TAPO-positive and TAPO-negative groups. Results: TAPO were found in 18/92 patients (19.6%), with a median follow-up of 114 weeks. Median onset time was 16 weeks (range 6–80) and median duration time 14 weeks (range 8–37). The most common radiologic pattern was focal ground-glass opacity (54.5%). We did not find any individual clinical variable significantly associated with the onset of TAPO or significant difference in clinical outcomes between TAPO-positive and TAPO-negative groups. Conclusions: TAPO are benign pulmonary findings observed in patients treated with osimertinib. TAPO variability in terms of CT features can hinder the differential diagnosis with either osimertinib-related mild ILD or tumor progression. However, because TAPO are asymptomatic, it could be reasonable to continue therapy and verify the resolution of the CT findings at follow-up in selected cases.

Adjuvant gefitinib versus cisplatin/vinorelbine in Japanese patients with completely resected, EGFR-mutated, stage II-III non-small cell lung cancer (IMPACT, WJOG6410L): A randomized phase 3 trial.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 8501-8501
Author(s):  
Hirohito Tada ◽  
Tetsuya Mitsudomi ◽  
Takeharu Yamanaka ◽  
Kenji Sugio ◽  
Masahiro Tsuboi ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Egfr Mutation ◽  
Disease Free Survival ◽  
Small Cell ◽  
Stage Ii ◽  
Small Cell Lung ◽  
Significant Difference ◽  
Egfr Mutated

8501 Background: Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor is a standard of care for EGFR mutation-positive, untreated metastatic non-small cell lung cancer (NSCLC). However, the efficacy and safety of adjuvant gefitinib for patients with completely resected lung cancer harboring EGFR mutation over cisplatin-based adjuvant chemotherapy were not known in 2011 when this study was initiated. Methods: From September 2011 to December 2015, we randomly assigned 234 patients with completely resected, EGFR mutation-positive (exon 19 deletion or L858R), stage II–III NSCLC to receive either gefitinib (250 mg, once daily) for 24 months or cisplatin (80 mg/m2 on day 1) plus vinorelbine (25 mg/m2 on days 1 and 8) (cis/vin) every 3 weeks for four cycles. The primary endpoint was disease-free survival (DFS) according to a central review in the intent-to-treat (ITT) population. Results: Two patients in the gefitinib arm withdrew consent and were excluded from the ITT population. No treatment-related deaths were seen in the gefitinib arm, but three treatment-related deaths were reported in the cis/vin arm. Median duration of follow-up was 71 months. Median DFS was numerically longer in the gefitinib arm (36 months) than in the cis/vin arm (25.2 months). However, Kaplan-Meier curves began to overlap around 5 years after surgery, and no significant difference in DFS was seen, with a hazard ratio (HR) of 0.92 (95% confidence interval (CI), 0.67–1.28; P = 0.63). Overall survival was also not significantly different (median not reached in either arm). Five-year survival rates for gefitinib and cis/vin arms were 78.0% and 74.6%, respectively, with an HR for death of 1.03; 95%CI, 0.65–1.65; P = 0.89. Exploratory subset analysis revealed that patients ³70 years old in the gefitinib arm (n = 19/27 with G to cis/vin) survived longer than those in the cis/vin arm (HR 0.31; 95%CI, 0.10–0.98; P = 0.046). Conclusions: Adjuvant gefitinib appeared to prevent early relapse, but did not significantly prolong DFS or OS in patients with completely resected stage II–III, EGFR-mutated NSCLC. The apparent non-inferiority of DFS/OS may justify the use of adjuvant gefitinib in selected subset of patients, especially those deemed unsuitable for cis/vin adjuvant therapy. Clinical trial information: UMIN000006252.

scholarly journals Metronomic Chemotherapy with Vinorelbine Produces Clinical Benefit and Low Toxicity in Frail Elderly Patients Affected by Advanced Non-Small Cell Lung Cancer

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Michela D’Ascanio ◽  
Aldo Pezzuto ◽  
Chiara Fiorentino ◽  
Bruno Sposato ◽  
Pierdonato Bruno ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Elderly Patients ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Safety Profile ◽  
Small Cell ◽  
Small Cell Lung ◽  
Significant Difference ◽  
Ecog Ps ◽  
Metronomic Vinorelbine

Background. Lung cancer is the leading cause of death worldwide. The treatment choice for advanced stage of lung cancer may depend on histotype, performance status (PS), age, and comorbidities. In the present study, we focused on the effect of metronomic vinorelbine treatment in elderly patients with advanced unresectable non-small cell lung cancer (NSCLC).Methods. From January 2016 to December 2016, 44 patients affected by non-small cell lung cancer referred to our oncology day hospital were progressively analyzed. The patients were treated with oral vinorelbine 30 mg x 3/wk or 40 mg x 3/wk meaning one day on and one day off. The patients were older than 60, stage IIIB or IV, ECOG PS ≥ 1, and have at least one important comorbidity (renal, hepatic, or cardiovascular disease). The schedule was based on ECOG-PS and comorbidities. The primary endpoint was progression-free survival (PFS). PFS was used to compare patients based on different scheduled dosage (30 or 40 mg x3/weekly) and age (more or less than 75 years old) as exploratory analysis. We also evaluated as secondary endpoint toxicity according to Common Toxicity Criteria Version 2.0.Results. Vinorelbine showed a good safety profile at different doses taken orally and was effective in controlling cancer progression. The median overall survival (OS) was 12 months. The disease control rate (DCR) achieved 63%. The median PFS was 9 months. A significant difference in PFS was detected comparing patients aged below with those over 75, and the HR value was 0.72 (p<0.05). Not significant was the difference between groups with different schedules.Conclusions.This study confirmed the safety profile of metronomic vinorelbine and its applicability for patients unfit for standard chemotherapies and adds the possibility of considering this type of schedule not only for very elderly patients.

Gemcitabine and Paclitaxel: Pharmacokinetic and Pharmacodynamic Interactions in Patients With Non–Small-Cell Lung Cancer

1999 ◽  
Vol 17 (7) ◽  
pp. 2190-2190 ◽  
Author(s):  
Judith R. Kroep ◽  
Giuseppe Giaccone ◽  
Daphne A. Voorn ◽  
Egbert F. Smit ◽  
Jos H. Beijnen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Hepatic Function ◽  
Small Cell ◽  
Pharmacokinetics And Pharmacodynamics ◽  
Small Cell Lung ◽  
Percentage Decrease ◽  
Pharmacodynamic Interactions ◽  
Significant Difference

PURPOSE: To assess possible pharmacokinetic and pharmacodynamic interactions between gemcitabine and paclitaxel in a phase I/II study in non–small-cell lung cancer (NSCLC) patients. PATIENTS AND METHODS: Eighteen patients with advanced NSCLC received the following in a 3-week schedule: gemcitabine 1,000 mg/m2 (30 minutes, days 1 and 8) and paclitaxel 150 (n = 9) or 200 mg/m2 (n = 9) before gemcitabine (3 hours, day 1). Plasma pharmacokinetics and pharmacodynamics in mononuclear cells were studied. RESULTS: Gemcitabine did not influence paclitaxel pharmacokinetics at 150 and 200 mg/m2 (area under the concentration-time curve [AUC], 7.7 and 8.8 μmol/ L · h, respectively; maximum plasma concentration [Cmax], 3.2 and 4.0 μmol/L, respectively), and paclitaxel did not influence that of gemcitabine (Cmax, 30 ± 3 μmol/L) and 2′,2′-difluorodeoxyuridine. Paclitaxel, however, dose-dependently increased the Cmax of gemcitabine triphosphate (dFdCTP), the active metabolite of gemcitabine, from 55 ± 10 to 106 ± 16 pmol/106 cells. No significant difference in the AUC of dFdCTP was observed. Moreover, the gemcitabine-paclitaxel combination significantly increased ribonucleotide levels, most pronounced for adenosine triphosphate (six- to seven-fold). Postinfusion paclitaxel AUC was related to pretreatment hepatic function (bilirubin: r = 0.79; P < .001) and to the percentage decrease in platelets (r = 0.61; P = .009). The latter was also related to the duration of paclitaxel concentration above 0.1 μmol/L (r = 0.62; P = .007). Gemcitabine Cmax was related to the percentage decrease in platelets (r = 0.58; P = .01), pretreatment hepatic function (bilirubin: r = 0.77; P < .001), and to plasma creatinine (r = 0.5; P = .03). The pharmacokinetics and pharmacodynamics were not related to response or survival. CONCLUSION: Gemcitabine and paclitaxel pharmacokinetics were related to the percentage decrease in platelets. Paclitaxel did not affect the pharmacokinetics of gemcitabine, nor did gemcitabine affect the pharmacokinetics of paclitaxel, but paclitaxel increased dFdCTP accumulation. This might enhance the antitumor activity of gemcitabine.

scholarly journals MLTI-04. EVOLUTION OF TREATMENT PARADIGMS FOR PATIENTS WITH ≥1 BRAIN METASTASES FROM PRIMARY NON-SMALL-CELL LUNG CANCER – A SYSTEMATIC REVIEW

2019 ◽  
Vol 1 (Supplement_1) ◽  
pp. i15-i15
Author(s):  
Karanbir Brar ◽  
Yosef Ellenbogen ◽  
Nebras Warsi ◽  
Jetan Badhiwala ◽  
Alireza Mansouri
Keyword(s):  
Lung Cancer ◽  
Systematic Review ◽  
Brain Metastases ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Egfr Inhibitors ◽  
Small Cell Lung ◽  
Significant Difference ◽  
Management Paradigms

Abstract BACKGROUND: Brain metastases (BM) are common in non-small cell lung cancer (NSCLC), with approximately 10% of patients presenting with BM at the time of diagnosis. The aim of this systematic review was to critically evaluate the evolution of management paradigms for BM from NSCLC. METHODS: We searched MEDLINE, EMBASE, Web of Science, ClinicalTrials.gov, and CENTRAL for randomized controlled trials (RCTs) published until October 2018. Comparative RCTs based on ≥ 50 patients were selected. The primary outcomes of interest were overall survival (OS) and progression-free survival (PFS). RESULTS: Among 3188 abstracts, 14 RCTs (2494 patients) met inclusion criteria. Median sample size was 97 (range 59–538). Most trials were open-label, parallel, superiority trials. All included patients aged ≥18 with histologically proven NSCLC and ≥1 BM proven on CT/MRI. The majority of trials (11/14) excluded patients with non-favorable performance status (ECOG, KPS, or WHO scales), prior SRS or WBRT, and/or leptomeningeal metastases. Interventions assessed included WBRT (11/14), SRS (3/14), targeted therapies (e.g. EGFR inhibitors, 5/14), and various chemotherapeutic regimens (12/14). Most trials (12/13) reported no significant difference in OS between interventions. 4/10 trials reported a difference in PFS, two of which only included patients with EGFR-mutant NSCLC; these showed a significant increase in PFS in patients managed with EGFR inhibitors. The other two trials reported longer PFS with sodium glycididazole + WBRT vs. WBRT alone (p=0.038) and temozolomide + SRS vs. SRS alone (p=0.003). The incidence of adverse events was consistent across most treatment groups. CONCLUSIONS: Most trials showed no significant improvement in OS; however, improvement in PFS was seen in several trials, most notably in EGFR-positive patients treated with EGFR inhibitors. Given the long-standing merit of radiation-based therapies for BM management, these data support the need for an in-depth meta-analysis assessing the comparative efficacy of current management paradigms for specific patient populations.

scholarly journals Machine learning highlights the deficiency of conventional dosimetric constraints for prevention of high-grade radiation esophagitis in non-small cell lung cancer treated with chemoradiation

2020 ◽  
Vol 22 ◽  
pp. 69-75
Author(s):  
José Marcio Luna ◽  
Hann-Hsiang Chao ◽  
Russel T. Shinohara ◽  
Lyle H. Ungar ◽  
Keith A. Cengel ◽  
...  
Keyword(s):  
Machine Learning ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
High Grade ◽  
Small Cell Lung ◽  
Radiation Esophagitis

scholarly journals Approach and assessment of automated stereotactic radiotherapy planning for early stage non-small-cell lung cancer

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Xue Bai ◽  
Guoping Shan ◽  
Ming Chen ◽  
Binbing Wang
Keyword(s):  
Machine Learning ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Automated Planning ◽  
Small Cell ◽  
Radiotherapy Planning ◽  
Plan Quality ◽  
Small Cell Lung ◽  
Planning Time

Abstract Background Intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) are standard physical technologies of stereotactic body radiotherapy (SBRT) that are used for patients with non-small-cell lung cancer (NSCLC). The treatment plan quality depends on the experience of the planner and is limited by planning time. An automated planning process can save time and ensure a high-quality plan. This study aimed to introduce and demonstrate an automated planning procedure for SBRT for patients with NSCLC based on machine-learning algorithms. The automated planning was conducted in two steps: (1) determining patient-specific optimized beam orientations; (2) calculating the organs at risk (OAR) dose achievable for a given patient and setting these dosimetric parameters as optimization objectives. A model was developed using data of historical expertise plans based on support vector regression. The study cohort comprised patients with NSCLC who were treated using SBRT. A training cohort (N = 125) was used to calculate the beam orientations and dosimetric parameters for the lung as functions of the geometrical feature of each case. These plan–geometry relationships were used in a validation cohort (N = 30) to automatically establish the SBRT plan. The automatically generated plans were compared with clinical plans established by an experienced planner. Results All 30 automated plans (100%) fulfilled the dose criteria for OARs and planning target volume (PTV) coverage, and were deemed acceptable according to evaluation by experienced radiation oncologists. An automated plan increased the mean maximum dose for ribs (31.6 ± 19.9 Gy vs. 36.6 ± 18.1 Gy, P < 0.05). The minimum, maximum, and mean dose; homogeneity index; conformation index to PTV; doses to other organs; and the total monitor units showed no significant differences between manual plans established by experts and automated plans (P > 0.05). The hands-on planning time was reduced from 40–60 min to 10–15 min. Conclusion An automated planning method using machine learning was proposed for NSCLC SBRT. Validation results showed that the proposed method decreased planning time without compromising plan quality. Plans generated by this method were acceptable for clinical use.

scholarly journals Using Machine Learning Modeling to Explore New Immune-Related Prognostic Markers in Non-Small Cell Lung Cancer

2020 ◽  
Vol 10 ◽  
Author(s):  
Jiasheng Xu ◽  
Han Nie ◽  
Jiarui He ◽  
Xinlu Wang ◽  
Kaili Liao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Prognostic Markers ◽  
Small Cell ◽  
Small Cell Lung
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