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Artificial Intelligence in Lung Cancer Pathology Image Analysis

Cancers · 2019 · Vol. 11(11) · pp. 1673–1673

Shidan Wang(The University of Texas Southwestern Medical Center)Donghan M. Yang(The University of Texas Southwestern Medical Center)Ruichen Rong(The University of Texas Southwestern Medical Center)Xiaowei Zhan(The University of Texas Southwestern Medical Center)Junya Fujimoto(The University of Texas MD Anderson Cancer Center)Hongyu Liu(The University of Texas Southwestern Medical Center)John D. Minna(The University of Texas Southwestern Medical Center)Ignacio I. Wistuba(The University of Texas MD Anderson Cancer Center)Yang Xie(The University of Texas Southwestern Medical Center)Guanghua Xiao✉(The University of Texas Southwestern Medical Center)

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Abstract

With the advance of technology, digital pathology could have great potential impacts in lung cancer patient care. We point out some promising future directions for lung cancer pathology image analysis, including multi-task learning, transfer learning, and model interpretation.

Radiomics and Machine Learning in Medical Imaging Lung Cancer Diagnosis and Treatment AI in cancer detectionDigital pathologyLung cancerDeep learningMedicinePathologyMolecular pathologyDigital image analysisComputer scienceArtificial intelligenceMedical physics