Results 181 to 190 of about 618,088 (242)

Prognostic Impact of Metastasis Timing in Metastatic Gastrointestinal Stromal Tumors: A Multicenter Retrospective Cohort Study

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Gastrointestinal stromal tumors (GISTs) commonly metastasize to the liver and peritoneum. Metastases may be detected synchronously at the time of initial diagnosis or develop metachronously after curative‐intent resection. Nonetheless, the prognostic significance of metastasis timing in advanced GIST remains unclear.
Kunihiko Kawai   +9 more
wiley   +1 more source

Cardiovascular Comorbidities and Advanced Chronic Kidney Disease in Hospitalized Patients with Multiple Myeloma: A Single-Center Retrospective Cohort Study. [PDF]

open access: yesDiseases
Bălăceanu LA   +7 more
europepmc   +1 more source

Prediction of Long‐Term Prognosis in Patients With Hepatocellular Carcinoma Using the National Clinical Database Risk Calculator

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
This study aimed to determine the value of the National Clinical Database (NCD) risk calculator in predicting surgical outcomes and long‐term prognosis in patients undergoing resection for hepatocellular carcinoma (HCC). We retrospectively analyzed data from 210 patients with HCC who underwent initial hepatic resection, assessing the relationship ...
Mariko Tsukagoshi   +8 more
wiley   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

open access: yesAdvanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

open access: yesAdvanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik   +6 more
wiley   +1 more source

Model analisis camel untuk memprediksi financial distress pada sektor perbankan yang go public

open access: yesJurnal Akuntansi dan Auditing Indonesia, 2018
Etty M. Nasser, Tatik Aryati
doaj  

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