Cancer adjuvant chemotherapy strategic classification by artificial neural network with gene expression data: An example for non-small cell lung cancer.

Purpose: Adjuvant chemotherapy (ACT) is used after surgery to prevent recurrence or metastases. However, ACT for non-small cell lung cancer (NSCLC) is still controversial. This study aimed to develop prediction models to distinguish who is suitable for ACT (ACT-benefit) and who should avoid ACT (ACT-futile) in NSCLC.

Risk classification of cancer survival using ANN with gene expression data from multiple laboratories.

Numerous cancer studies have combined gene expression experiments and clinical survival data to predict the prognosis of patients of specific gene types. However, most results of these studies were data dependent and were not suitable for other data sets. This study performed cross-laboratory validations for the cancer patient data from 4 hospitals.

Trend analysis and future development of Taiwan electronic medical records.

The aim of this study was to validate a specially designed electronic medical records (EMRs) questionnaire for use in Taiwan. Published reviews of national trends and EMRs characteristics from seven countries in the Americas, Oceania, Europe, and Asia were used to design the Google-based document. This questionnaire is intended for use by medical institutions, government health units, manufacturers, academic institutions, and the public, and may be administered by information officers, non-IT staff (physicians, nurses, policymakers, vendors), and even people.