AIMC Topic: Neural Networks, Computer

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A medical disease assisted diagnosis method based on lightweight fuzzy SZGWO-ELM neural network model.

Scientific reports
The application of neural network model in intelligent diagnosis usually encounters challenges such as continuous adjustment of network parameters and significant cost in training the network facing numerous complex physiological data. To address thi...

B cell epitope prediction by capturing spatial clustering property of the epitopes using graph attention network.

Scientific reports
Knowledge of B cell epitopes is critical to vaccine design, diagnostics, and therapeutics. As experimental validation for epitopes is time-consuming and costly, many in silico tools have been developed to computationally predict the B cell epitopes. ...

A novel benign and malignant classification model for lung nodules based on multi-scale interleaved fusion integrated network.

Scientific reports
One of the precursors of lung cancer is the presence of lung nodules, and accurate identification of their benign or malignant nature is important for the long-term survival of patients. With the development of artificial intelligence, deep learning ...

Predictive analytics of complex healthcare systems using deep learning based disease diagnosis model.

Scientific reports
Cancer is a life-threatening disease resulting from a genetic disorder and a range of metabolic anomalies. In particular, lung and colon cancer (LCC) are among the major causes of death and disease in humans. The histopathological diagnoses are criti...

Teaching deep networks to see shape: Lessons from a simplified visual world.

PLoS computational biology
Deep neural networks have been remarkably successful as models of the primate visual system. One crucial problem is that they fail to account for the strong shape-dependence of primate vision. Whereas humans base their judgements of category membersh...

Improving drug-target interaction prediction through dual-modality fusion with InteractNet.

Journal of bioinformatics and computational biology
In the drug discovery process, accurate prediction of drug-target interactions is crucial to accelerate the development of new drugs. However, existing methods still face many challenges in dealing with complex biomolecular interactions. To this end,...

Deep learning-based near-field effect correction method for Controlled Source Electromagnetic Method and application.

PloS one
Addressing the impact of near-field effects in the Controlled Source Electromagnetic Method(CSEM) has long been a focal point in the realm of geophysical exploration. Therefore, we propose a deep learning-based near-field correction method for contro...

Exploring machine learning algorithms in sickle cell disease patient data: A systematic review.

PloS one
This systematic review explores the application of machine learning (ML) algorithms in sickle cell disease (SCD), focusing on diagnosis and several clinical characteristics, such as early detection of organ failure, identification of drug dosage, and...

Grade prediction of lesions in cerebral white matter using a convolutional neural network.

PloS one
We established a diagnostic method for cerebral white matter lesions using MRI images and examined the relationship between the MRI images and the medical checkup data. There were approximately 25 MRI images for each patient's head, from the top of t...

Automated arrhythmia classification based on a pyramid dense connectivity layer and BiLSTM.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundDeep neural networks (DNNs) have recently been significantly applied to automatic arrhythmia classification. However, their classification accuracy still has room for improvement.ObjectivesThe aim of this study is to address the existing li...