AIMC Topic: Aged

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A radiomics approach based on support vector machine using MR images for preoperative lymph node status evaluation in intrahepatic cholangiocarcinoma.

Theranostics
: Accurate lymph node (LN) status evaluation for intrahepatic cholangiocarcinoma (ICC) patients is essential for surgical planning. This study aimed to develop and validate a prediction model for preoperative LN status evaluation in ICC patients. : A...

A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection.

IEEE transactions on medical imaging
Glaucoma is one of the leading causes of irreversible vision loss. Many approaches have recently been proposed for automatic glaucoma detection based on fundus images. However, none of the existing approaches can efficiently remove high redundancy in...

Application of artificial neural network model in diagnosis of Alzheimer's disease.

BMC neurology
BACKGROUND: Alzheimer's disease has become a public health crisis globally due to its increasing incidence. The purpose of this study was to establish an early warning model using artificial neural network (ANN) for early diagnosis of AD and to explo...

Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization.

PloS one
PURPOSE: To develop and validate a classifier system for prediction of prostate cancer (PCa) Gleason score (GS) using radiomics and texture features of T2-weighted imaging (T2w), diffusion weighted imaging (DWI) acquired using high b values, and T2-m...

Development of Big Data Predictive Analytics Model for Disease Prediction using Machine learning Technique.

Journal of medical systems
Now days, health prediction in modern life becomesvery much essential. Big data analysis plays a crucial role to predict future status of healthand offerspreeminenthealth outcome to people. Heart disease is a prevalent disease cause's death around th...

Identifying incident dementia by applying machine learning to a very large administrative claims dataset.

PloS one
Alzheimer's disease and related dementias (ADRD) are highly prevalent conditions, and prior efforts to develop predictive models have relied on demographic and clinical risk factors using traditional logistical regression methods. We hypothesized tha...

Cortical graph neural network for AD and MCI diagnosis and transfer learning across populations.

NeuroImage. Clinical
Combining machine learning with neuroimaging data has a great potential for early diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, it remains unclear how well the classifiers built on one population can predict MCI/...