AIMC Topic: Deep Learning

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PrUb-EL: A hybrid framework based on deep learning for identifying ubiquitination sites in Arabidopsis thaliana using ensemble learning strategy.

Analytical biochemistry
Identification of ubiquitination sites is central to many biological experiments. Ubiquitination is a kind of post-translational protein modification (PTM). It is a key mechanism for increasing protein diversity and plays a vital role in regulating c...

A hierarchical machine learning model based on Glioblastoma patients' clinical, biomedical, and image data to analyze their treatment plans.

Computers in biology and medicine
AIM OF STUDY: Glioblastoma Multiforme (GBM) is an aggressive brain cancer in adults that kills most patients in the first year due to ineffective treatment. Different clinical, biomedical, and image data features are needed to analyze GBM, increasing...

A general deep learning framework for neuron instance segmentation based on Efficient UNet and morphological post-processing.

Computers in biology and medicine
Recent studies have demonstrated the superiority of deep learning in medical image analysis, especially in cell instance segmentation, a fundamental step for many biological studies. However, the excellent performance of the neural networks requires ...

Mining Data Impressions From Deep Models as Substitute for the Unavailable Training Data.

IEEE transactions on pattern analysis and machine intelligence
Pretrained deep models hold their learnt knowledge in the form of model parameters. These parameters act as "memory" for the trained models and help them generalize well on unseen data. However, in absence of training data, the utility of a trained m...

Skin Lesion Classification on Imbalanced Data Using Deep Learning with Soft Attention.

Sensors (Basel, Switzerland)
Today, the rapid development of industrial zones leads to an increased incidence of skin diseases because of polluted air. According to a report by the American Cancer Society, it is estimated that in 2022 there will be about 100,000 people suffering...

DPProm: A Two-Layer Predictor for Identifying Promoters and Their Types on Phage Genome Using Deep Learning.

IEEE journal of biomedical and health informatics
With the number of phage genomes increasing, it is urgent to develop new bioinformatics methods for phage genome annotation. Promoter, a DNA region, is important for gene transcriptional regulation. In the era of post-genomics, the availability of da...

Symmetry-Aware Deep Learning for Cerebral Ventricle Segmentation With Intra-Ventricular Hemorrhage.

IEEE journal of biomedical and health informatics
Cerebral ventricles are one of the prominent structures in the brain, segmenting which can provide rich information for brain-related disease diagnosis. Unfortunately, cerebral ventricle segmentation in complex clinical cases, such as in the coexiste...

DDCNN: A Deep Learning Model for AF Detection From a Single-Lead Short ECG Signal.

IEEE journal of biomedical and health informatics
With the popularity of the wireless body sensor network, real-time and continuous collection of single-lead electrocardiogram (ECG) data becomes possible in a convenient way. Data mining from the collected single-lead ECG waves has therefore aroused ...

A Fully Deep Learning Paradigm for Pneumoconiosis Staging on Chest Radiographs.

IEEE journal of biomedical and health informatics
Pneumoconiosis staging has been a very challenging task, both for certified radiologists and computer-aided detection algorithms. Although deep learning has shown proven advantages in the detection of pneumoconiosis, it remains challenging in pneumoc...

A Deep Learning Method for Breast Cancer Classification in the Pathology Images.

IEEE journal of biomedical and health informatics
Breast cancer is the most common female cancer in the world, and it poses a huge threat to women's health. There is currently promising research concerning its early diagnosis using deep learning methodologies. However, some commonly used Convolution...