Deep convolutional neural network algorithm for the automatic segmentation of oral potentially malignant disorders and oral cancers.

This study aimed to develop an algorithm to automatically segment the oral potentially malignant diseases (OPMDs) and oral cancers (OCs) of all oral subsites with various deep convolutional neural network applications. A total of 510 intraoral images of OPMDs and OCs were collected over 3 years (2006-2009). All images were confirmed both with patient records and histopathological reports.

MDS-associated somatic mutations and clonal hematopoiesis are common in idiopathic cytopenias of undetermined significance.

Establishing a diagnosis in patients suspected of having a myelodysplastic syndrome (MDS) can be challenging and could be informed by the identification of somatic mutations. We performed a prospective study to examine the frequency and types of mutations encountered in 144 patients with unexplained cytopenias. Based on bone marrow findings, 17% were diagnosed with MDS, 15% with idiopathic cytopenias of undetermined significance (ICUS) and some evidence of dysplasia, and 69% with ICUS and no dysplasia.