The incidence of stomach cancer has been found to be gradually decreasing; however, it remains one of the most frequently occurring malignant cancers in Korea. According to statistics of 2017, stomach cancer is the top cancer in men and the fourth most important cancer in women, necessitating methods for its early detection and treatment. Considerable research in the field of bioinformatics has been conducted in cancer studies, and bioinformatics approaches might help develop methods and models for its early prediction. We aimed to develop a classification method based on deep learning and demonstrate its application to gene expression data obtained from patients with stomach cancer. Data of 60,483 genes from 334 patients with stomach cancer in The Cancer Genome Atlas were evaluated by principal component analysis, heatmaps, and the convolutional neural network (CNN) algorithm. We combined the RNA-seq gene expression data with clinical data, searched candidate genes, and analyzed them using the CNN deep learning algorithm. We performed learning using the sample type and vital status of patients with stomach cancer and verified the results. We obtained an accuracy of 95.96% for sample type and 50.51% for vital status. Despite overfitting owing to the limited number of patients, relatively accurate results for sample type were obtained. This approach can be used to predict the prognosis of stomach cancer, which has many types and underlying causes.

Purpose: The purpose of this study was to understand and describe the experiences of stomach cancer patients in South Korea. Methods: Secondary analysis of qualitative data was designed. The data were analyzed via the Phenomenological Method, using the data of 12 stomach cancer patients, from the original data collected by narrative interviews in 2013. Results: Seven theme clusters emerged from the analysis. Beginning with: ‘Facing Life Threats from Cancer,’ this describes how the participants experience between cancer diagnosis and treatments. ‘Crossing the Boundary between Life and Death’ deals with desperate struggle to overcome medical treatments, such as gastrectomy and chemotherapy, while ‘Adjusting to Weakened Body’ illustrates the continuous daily struggle to follow dietary treatments after operation. ‘Dilemmas in Interpersonal Relationships’ illustrates the sensitivity of relationships from the cancer stigma, with predicaments rising in collective dining situations. ‘Encountering: Hidden Me, Inside Me’ describes changes in values of life and a matured self. ‘Supporters for Hope’ illustrates driving forces to keep hope alive in everyday lives. Lastly, ‘Happiness of Everyday Life Rescued from Misery’ describes how life turned into blessings from cancer after all. Conclusion: The results of this study would help oncology professionals to develop patient-centered cancer survivorship interventions, by understanding and gaining insights about the lived experience of stomach cancer patients.