A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL.

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A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL.

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2016 nî lūn-bûn

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2016年の論文

@ja

2016年論文

@yue

2016年論文

@zh-hant

2016年論文

@zh-hk

2016年論文

@zh-mo

2016年論文

@zh-tw

2016年论文

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2016年论文

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2016年论文

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name

A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL.

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A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL.

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A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL.

@en

A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL.

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A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL.

@en

A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL.

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P1476

A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL.

@en

P2093

Benjamin Young

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Carlos A Jimenez

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Corrine Kliment

http://www.w3.org/2001/XMLSchema#string

Francisco A Almeida

http://www.w3.org/2001/XMLSchema#string

George A Eapen

http://www.w3.org/2001/XMLSchema#string

Hans Lee

http://www.w3.org/2001/XMLSchema#string

Harmeet Bedi

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Horiana B Grosu

http://www.w3.org/2001/XMLSchema#string

Javier Diaz-Mendoza

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Joseph Cicenia

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P2860

Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines.

Noninvasive staging of non-small cell lung cancer: ACCP evidenced-based clinical practice guidelines (2nd edition).

Relationship between tumor size and disease stage in non-small cell lung cancer.

Validation of two models to estimate the probability of malignancy in patients with solitary pulmonary nodules.

Evaluation and management of the solitary pulmonary nodule.

Clinical practice. The solitary pulmonary nodule.

A clinical model to estimate the pretest probability of lung cancer in patients with solitary pulmonary nodules.

Neural networks for nodal staging of non-small cell lung cancer with FDG PET and CT: importance of combining uptake values and sizes of nodes and primary tumor.

External validation of a prediction model for pathologic N2 among patients with a negative mediastinum by positron emission tomography.

Test performance of positron emission tomography and computed tomography for mediastinal staging in patients with non-small-cell lung cancer: a meta-analysis.

P304

1651-1660

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P31

scholarly article

P356

10.1164/RCCM.201607-1397OC

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P407

English

P433

http://www.w3.org/2001/XMLSchema#string

P478

195

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P50

David Ost

David Feller-Kopman

P577

2017-06-01T00:00:00Z

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P698

28002683

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P932

5476908

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