Features predicting unresectability in hepatoblastoma
نویسندگان
چکیده
منابع مشابه
CA724 is a novel factor for predicting the unresectability in pancreatic adenocarcinoma.
This study aimed to assess the relationship between serum CA724 levels and the unresectability of pancreatic adenocarcinoma. A total of 302 patients with pancreatic adenocarcinoma were analyzed for the potential association between serum CA724 levels and the unresectability of pancreatic adenocarcinoma. Serum CA724 levels in patients with unresectable pancreatic adenocarcinoma were remarkably h...
متن کاملinfantile hepatic hemangioendothelioma in comparison with hepatoblastoma in children: clinical and ultrasound features
conclusions the clinical features are effective indicators for distinguishing ihh from hbl, and the spectral doppler may be a useful adjunct parameter for differential diagnosis. objectives to study the clinical manifestations and the ultrasound features of the pediatric patients for distinguishing ihh from hbl. patients and methods between 2002 and 2012, thirteen children with ihh and 38 child...
متن کاملCase Series of Hepatoblastoma
Background: In the past 20 years, a dramatic improvement in the prognosis of patients with hepatoblastoma (HB)has been achieved by combining surgery and chemotherapy in several national and international trials.Materials and Methods: Four children ( 3 girl and 1 boy) aged 34 days, 4 months, 13 months, and 1 year with meanage of 6.53 (±5.15) months were presented to our center from 2002 to 2009 ...
متن کاملInfantile Hepatic Hemangioendothelioma in Comparison with Hepatoblastoma in Children: Clinical and Ultrasound Features
BACKGROUND Infantile hepatic hemangioendothelioma (IHH) and hepatoblastoma (HBL) are respectively the most common benign and malignant liver tumors in children. OBJECTIVES To study the clinical manifestations and the ultrasound features of the pediatric patients for distinguishing IHH from HBL. PATIENTS AND METHODS Between 2002 and 2012, thirteen children with IHH and 38 children with HBL u...
متن کاملPredicting Crime Using Spatial Features
Our study aims to build a machine learning model for crime prediction using geospatial features for different categories of crime. The reverse geocoding technique is applied to retrieve open street map (OSM) spatial data. This study also proposes finding hotpoints extracted from crime hotspots area found by Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN). A sp...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Cancer
سال: 2007
ISSN: 0008-543X,1097-0142
DOI: 10.1002/cncr.22876