AIMC Topic: ROC Curve

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Overall survival prediction in glioblastoma multiforme patients from volumetric, shape and texture features using machine learning.

Surgical oncology
Glioblastoma multiforme (GBM) are aggressive brain tumors, which lead to poor overall survival (OS) of patients. OS prediction of GBM patients provides useful information for surgical and treatment planning. Radiomics research attempts at predicting ...

Using predicate and provenance information from a knowledge graph for drug efficacy screening.

Journal of biomedical semantics
BACKGROUND: Biomedical knowledge graphs have become important tools to computationally analyse the comprehensive body of biomedical knowledge. They represent knowledge as subject-predicate-object triples, in which the predicate indicates the relation...

Machine Learning and Primary Total Knee Arthroplasty: Patient Forecasting for a Patient-Specific Payment Model.

The Journal of arthroplasty
BACKGROUND: Value-based and patient-specific care represent 2 critical areas of focus that have yet to be fully reconciled by today's bundled care model. Using a predictive naïve Bayesian model, the objectives of this study were (1) to develop a mach...

Parkinson's Disease Diagnosis via Joint Learning From Multiple Modalities and Relations.

IEEE journal of biomedical and health informatics
Parkinson's disease (PD) is a neurodegenerative progressive disease that mainly affects the motor systems of patients. To slow this disease deterioration, early and accurate diagnosis of PD is an effective way, which alleviates mental and physical su...

A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia.

Journal of neuroscience methods
BACKGROUND: Technological advances are enabling us to collect multimodal datasets at an increasing depth and resolution while with decreasing labors. Understanding complex interactions among multimodal datasets, however, is challenging.

Support Vector Machines and logistic regression to predict temporal artery biopsy outcomes.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: Support vector machines (SVM) is a newer statistical method that has been reported to be advantageous to traditional logistic regression for clinical classification. We determine if SVM can better predict the results of temporal artery bio...

Decision Support System for Seizure Onset Zone Localization Based on Channel Ranking and High-Frequency EEG Activity.

IEEE journal of biomedical and health informatics
Interictal high-frequency oscillations (HFO) are a promising biomarker that can help define the seizure onset zone (SOZ) and predict the surgical outcome after the epilepsy surgery. The utility of HFO in planning the surgery, though, is unclear. Reas...

Methodological variations in lagged regression for detecting physiologic drug effects in EHR data.

Journal of biomedical informatics
We studied how lagged linear regression can be used to detect the physiologic effects of drugs from data in the electronic health record (EHR). We systematically examined the effect of methodological variations ((i) time series construction, (ii) tem...