Publications by authors named "Hosuk Ryou"
Myeloproliferative neoplasms are stem cell-driven cancers associated with a large burden of morbidity and mortality. Most patients present with early-stage disease, but a substantial proportion progress to myelofibrosis or secondary leukemia, advanced cancers with a poor prognosis and high symptom burden. Currently, it remains difficult to predict progression, and therapies that reliably prevent or reverse fibrosis are lacking.
View Article and Find Full Text PDFThe diagnosis of myeloproliferative neoplasms (MPN) requires the integration of clinical, morphological, genetic and immunophenotypic findings. Recently, there has been a transformation in our understanding of the cellular and molecular mechanisms underlying disease initiation and progression in MPN. This has been accompanied by the widespread application of high-resolution quantitative molecular techniques.
View Article and Find Full Text PDFArticle Synopsis
- Grading fibrosis in myeloproliferative neoplasms (MPN) is key for disease classification and patient monitoring, but current systems are limited and don’t capture all sample variations.
- A new machine learning method called Continuous Indexing of Fibrosis (CIF) was developed using bone marrow samples, significantly improving the detection and classification of fibrosis in MPNs.
- CIF shows high accuracy in distinguishing between essential thrombocythemia and pre-fibrotic myelofibrosis, and it may also help identify patients at risk of disease progression, which could refine future MPN studies.
The first trimester fetal ultrasound scan is important to confirm fetal viability, to estimate the gestational age of the fetus, and to detect fetal anomalies early in pregnancy. First trimester ultrasound images have a different appearance than for the second trimester scan, reflecting the different stage of fetal development. There is limited literature on automation of image-based assessment for this earlier trimester, and most of the literature is focused on one specific fetal anatomy.
View Article and Find Full Text PDFEstimation of body temperature rhythm based on heart activity parameters in daily life.
Annu Int Conf IEEE Eng Med Biol Soc
November 2015
Body temperature contains valuable health related information such as circadian rhythm and menstruation cycle. Also, it was discovered from previous studies that body temperature rhythm in daily life is related with sleep disorders and cognitive performances. However, monitoring body temperature with existing devices during daily life is not easy because they are invasive, intrusive, or expensive.
View Article and Find Full Text PDF