AI Medical Compendium Journal:
Medical hypotheses

Showing 11 to 20 of 20 articles

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...

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...

A new approach for brain tumor diagnosis system: Single image super resolution based maximum fuzzy entropy segmentation and convolutional neural network.

Medical hypotheses
Magnetic resonance imaging (MRI) images can be used to diagnose brain tumors. Thanks to these images, some methods have so far been proposed in order to distinguish between benign and malignant brain tumors. Many systems attempting to define these tu...

Is it possible to detect cerebral dominance via EEG signals by using deep learning?

Medical hypotheses
Each brain hemisphere is dominant for certain functions such as speech. The determination of speech laterality prior to surgery is of paramount importance for accurate risk prediction. In this study, we aimed to determine speech laterality via EEG si...

A deep learning-based decision support system for diagnosis of OSAS using PTT signals.

Medical hypotheses
Sleep disorders, which negatively affect an individual's daily quality of life, are a common problem for most of society. The most dangerous sleep disorder is obstructive sleep apnea syndrome (OSAS), which manifests itself during sleep and can cause ...

Versatility of fuzzy logic in chronic diseases: A review.

Medical hypotheses
The review aims at providing current state of evidence in the field of medicine with fuzzy logic for diagnosing diseases. Literature reveals that fuzzy logic has been used effectively in medicine. Different types of methodologies have been applied to...

Rapid and accurate intraoperative pathological diagnosis by artificial intelligence with deep learning technology.

Medical hypotheses
Frozen section is widely used for intraoperative pathological diagnosis (IOPD), which is essential for intraoperative decision making. However, frozen section suffers from some drawbacks, such as time consuming and high misdiagnosis rate. Recently, a...

Biodegradable microrobots for targeting cell delivery.

Medical hypotheses
These days, cell delivery is considered a potential method for treatment of many genetic diseases or tissue regeneration applications. In conventional cell delivery methods, cells are encapsulated in or cultured on biocompatible polymers. However, th...

Immediate hemodynamic changes after revascularization of complete infrarenal aortic occlusion: A classic issue revisited.

Medical hypotheses
Chronic total occlusion of the infrarenal aorta (CTOA) is a rare disease, characterized by severe impairment of limb perfusion. It is advocated that revascularization may improve survival rates, presumably due to improved cardiovascular performance; ...