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Isocitrate dehydrogenase 1 (IDH1) mutation status is an independent favourable prognostic factor for glioblastoma (GBM) and is usually determined by sequencing or immunohistochemistry. An accurate prediction of IDH1 mutation status via noninvasive methods helps establish the appropriate treatment strategy. We aimed to predict IDH1 mutation status using quantitative radiomic data in patients with GBM.
This article was published in the following journal.
Name: World neurosurgery
Isocitrate dehydrogenase (IDH) and 1p19q codeletion status are importantin providing prognostic information as well as prediction of treatment response in gliomas. Accurate determination of the IDH mu...
For decades, our ability to predict suicide has remained at near-chance levels. Machine learning has recently emerged as a promising tool for advancing suicide science, particularly in the domain of s...
The prevalence of metabolic syndrome (MS) in the nonobese population is not low. However, the identification and risk mitigation of MS are not easy in this population. We aimed to develop an MS predic...
Prognostic modelling using standard methods is well-established, particularly for predicting risk of single diseases. Machine-learning may offer potential to explore outcomes of even greater complexit...
While machine learning approaches may enhance prediction ability, little is known about their utility in emergency department (ED) triage.
The investigators propose to develop and evaluate a hospital department-specific machine learning based clinical decision support (CDS) system for early sepsis prediction, focused on impro...
This trial develops a non invasive diagnostic approach of IDH1 mutated gliomas combining mutation detection from free plasmatic DNA, D-2HG dosage in urine samples, and D-2HG detection by B...
This research study is studying a drug as a possible treatment for IDH1-mutant myeloid neoplasms. -The drug involved in this study is ivosidenib (AG-120)
A Study of Ivosidenib or Enasidenib in Combination With Induction Therapy and Consolidation Therapy, Followed by Maintenance Therapy in Patients With Newly Diagnosed Acute Myeloid Leukemia or Myedysplastic Syndrome EB2, With an IDH1 or IDH2 Mutation, Resp
AML and MDS-EB2 are malignancies of the bone marrow. The standard treatment for these diseases is chemotherapy. Patients participating have a special type of this disease because the leuke...
The purpose of this Phase I, multicenter study is to evaluate the safety, pharmacokinetics, pharmacodynamics and clinical activity of AG-881 in advanced hematologic malignancies that harbo...
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of unlabeled paired input-output training (sample) data.
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of labeled paired input-output training (sample) data.
SUPERVISED MACHINE LEARNING algorithm which learns to assign labels to objects from a set of training examples. Examples are learning to recognize fraudulent credit card activity by examining hundreds or thousands of fraudulent and non-fraudulent credit card activity, or learning to make disease diagnosis or prognosis based on automatic classification of microarray gene expression profiles drawn from hundreds or thousands of samples.
A type of ARTIFICIAL INTELLIGENCE that enable COMPUTERS to independently initiate and execute LEARNING when exposed to new data.
Usually refers to the use of mathematical models in the prediction of learning to perform tasks based on the theory of probability applied to responses; it may also refer to the frequency of occurrence of the responses observed in the particular study.
DNA sequencing is the process of determining the precise order of nucleotides within a DNA molecule. During DNA sequencing, the bases of a small fragment of DNA are sequentially identified from signals emitted as each fragment is re-synthesized from a ...