0000000001262742
AUTHOR
J. Jankowski
Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural ne…
Highlights of the EORTC St. Gallen International Expert Consensus on the primary therapy of gastric, gastroesophageal and oesophageal cancer - differential treatment strategies for subtypes of early gastroesophageal cancer.
The 1st St. Gallen EORTC Gastrointestinal Cancer Conference 2012 Expert Panel clearly differentiated treatment and staging recommendations for the various gastroesophageal cancers. For locally advanced gastric cancer (>= PT3N+), the preferred treatment modality was pre- and postoperative chemotherapy. The majority of panel members would also treat T2N+ or even T2N0 tumours with a similar approach mainly because pretherapeutic staging was considered highly unreliable. It was agreed that adenocarcinoma of the gastroesophageal junction (AEG) is classified best according to Siewert et al. Preoperative radiochemotherapy (RCT) is the preferred treatment for AEG type I and II tumours. For AEG type…