AIMC Topic: Neural Networks, Computer

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Jaya Ant lion optimization-driven Deep recurrent neural network for cancer classification using gene expression data.

Medical & biological engineering & computing
Cancer is one of the deadly diseases prevailing worldwide and the patients with cancer are rescued only when the cancer is detected at the very early stage. Early detection of cancer is essential as, in the final stage, the chance of survival is limi...

Adaptive SNN for Anthropomorphic Finger Control.

Sensors (Basel, Switzerland)
Anthropomorphic hands that mimic the smoothness of human hand motions should be controlled by artificial units of high biological plausibility. Adaptability is among the characteristics of such control units, which provides the anthropomorphic hand w...

Statistical and Machine Learning Models for Classification of Human Wear and Delivery Days in Accelerometry Data.

Sensors (Basel, Switzerland)
Accelerometers are increasingly being used in biomedical research, but the analysis of accelerometry data is often complicated by both the massive size of the datasets and the collection of unwanted data from the process of delivery to study particip...

Using CNN and HHT to Predict Blood Pressure Level Based on Photoplethysmography and Its Derivatives.

Biosensors
According to the WTO, there were 1.13 billion hypertension patients worldwide in 2015. The WTO encouraged people to check the blood pressure regularly because a large amount of patients do not have any symptoms. However, traditional cuff measurement ...

Accessory pathway analysis using a multimodal deep learning model.

Scientific reports
Cardiac accessory pathways (APs) in Wolff-Parkinson-White (WPW) syndrome are conventionally diagnosed with decision tree algorithms; however, there are problems with clinical usage. We assessed the efficacy of the artificial intelligence model using ...

A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks.

Scientific reports
Breast cancer is currently the second most common cause of cancer-related death in women. Presently, the clinical benchmark in cancer diagnosis is tissue biopsy examination. However, the manual process of histopathological analysis is laborious, time...

The whole is greater than its parts: ensembling improves protein contact prediction.

Scientific reports
The prediction of amino acid contacts from protein sequence is an important problem, as protein contacts are a vital step towards the prediction of folded protein structures. We propose that a powerful concept from deep learning, called ensembling, c...

A graph neural network framework for causal inference in brain networks.

Scientific reports
A central question in neuroscience is how self-organizing dynamic interactions in the brain emerge on their relatively static structural backbone. Due to the complexity of spatial and temporal dependencies between different brain areas, fully compreh...

Automated detection and segmentation of thoracic lymph nodes from CT using 3D foveal fully convolutional neural networks.

BMC medical imaging
BACKGROUND: In oncology, the correct determination of nodal metastatic disease is essential for patient management, as patient treatment and prognosis are closely linked to the stage of the disease. The aim of the study was to develop a tool for auto...

Current and emerging artificial intelligence applications for pediatric abdominal imaging.

Pediatric radiology
Artificial intelligence (AI) uses computers to mimic cognitive functions of the human brain, allowing inferences to be made from generally large datasets. Traditional machine learning (e.g., decision tree analysis, support vector machines) and deep l...