Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Mar 11, 2021
Multiple sclerosis and neuromyelitis optica spectrum disorders are both neuroinflammatory diseases and have overlapping clinical manifestations. We developed a convolutional neural network model that differentiates between the two based on magnetic r...
International journal of medical informatics
Mar 11, 2021
BACKGROUND: Despite the increasing number of studies in breast cancer survival prediction, there is little attention put toward deceased patients and their survival lengths. Moreover, developing a model that is both accurate and interpretable remains...
We developed machine learning (ML) algorithms to predict abnormal tau accumulation among patients with prodromal AD. We recruited 64 patients with prodromal AD using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Supervised ML approa...
BACKGROUND: Contemporary deep learning approaches show cutting-edge performance in a variety of complex prediction tasks. Nonetheless, the application of deep learning in healthcare remains limited since deep learning methods are often considered as ...
OBJECTIVES: To build and validate random forest (RF) models for the classification of bone tumors based on the conventional radiographic features of the lesion and patients' clinical characteristics, and identify the most essential features for the c...
PURPOSE: To develop convolutional neural network (CNN) models for differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) and predicting histopathological grade of HCC.
BACKGROUND: A frameless stereotactic robot-assisted system allows stereoelectroencephalography (SEEG) electrodes to span multiple lobes. As the angularity and length are increased, maintaining accuracy of the electrodes becomes more challenging. The ...
BACKGROUND: Early diagnosis of severe acute pancreatitis (SAP) is essential to minimize its mortality and improve prognosis. We aimed to develop an accurate and applicable machine learning predictive model based on routine clinical testing results fo...
Osteosarcoma is the most common bone malignancy, with the highest incidence in children and adolescents. Survival rate prediction is important for improving prognosis and planning therapy. However, there is still no prediction model with a high accur...
The pharmacokinetic variability of lamotrigine (LTG) plays a significant role in its dosing requirements. Our goal here was to use noninvasive clinical parameters to predict the dose-adjusted concentrations (C/D ratio) of LTG based on machine learnin...
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