AI Medical Compendium Topic:
Diagnosis, Computer-Assisted

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A speckle-tracking strain-based artificial neural network model to differentiate cardiomyopathy type.

Scandinavian cardiovascular journal : SCJ
In heart failure, invasive angiography is often employed to differentiate ischaemic from non-ischaemic cardiomyopathy. We aim to examine the predictive value of echocardiographic strain features alone and in combination with other features to differ...

Clinical-learning versus machine-learning for transdiagnostic prediction of psychosis onset in individuals at-risk.

Translational psychiatry
Predicting the onset of psychosis in individuals at-risk is based on robust prognostic model building methods including a priori clinical knowledge (also termed clinical-learning) to preselect predictors or machine-learning methods to select predicto...

Prediction of Breast Cancer from Imbalance Respect Using Cluster-Based Undersampling Method.

Journal of healthcare engineering
To overcome the two-class imbalanced problem existing in the diagnosis of breast cancer, a hybrid of K-means and Boosted C5.0 (K-Boosted C5.0) is proposed which is based on undersampling. K-means is utilized to select the informative samples near the...

An expert system for brain tumor detection: Fuzzy C-means with super resolution and convolutional neural network with extreme learning machine.

Medical hypotheses
Super-resolution, which is one of the trend issues of recent times, increases the resolution of the images to higher levels. Increasing the resolution of a vital image in terms of the information it contains such as brain magnetic resonance image (MR...

Cascaded deep convolutional encoder-decoder neural networks for efficient liver tumor segmentation.

Medical hypotheses
Liver and hepatic tumor segmentation remains a challenging problem in Computer Tomography (CT) images analysis due to its shape variation and vague boundary. The general hypothesis says that deep learning methods produce improved results on medical i...

An Effective LSTM Recurrent Network to Detect Arrhythmia on Imbalanced ECG Dataset.

Journal of healthcare engineering
To reduce the high mortality rate from cardiovascular disease (CVD), the electrocardiogram (ECG) beat plays a significant role in computer-aided arrhythmia diagnosis systems. However, the complex variations and imbalance of ECG beats make this a chal...

DCCMED-Net: Densely connected and concatenated multi Encoder-Decoder CNNs for retinal vessel extraction from fundus images.

Medical hypotheses
Recent studies have shown that convolutional neural networks (CNNs) can be more accurate, efficient and even deeper on their training if they include direct connections from the layers close to the input to those close to the output in order to trans...