AIMC Topic: Deep Learning

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Automatic Identification of Breast Ultrasound Image Based on Supervised Block-Based Region Segmentation Algorithm and Features Combination Migration Deep Learning Model.

IEEE journal of biomedical and health informatics
Breast cancer is a high-incidence type of cancer for women. Early diagnosis plays a crucial role in the successful treatment of the disease and the effective reduction of deaths. In this paper, deep learning technology combined with ultrasound imagin...

Deep Transfer Learning and Radiomics Feature Prediction of Survival of Patients with High-Grade Gliomas.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Patient survival in high-grade glioma remains poor, despite the recent developments in cancer treatment. As new chemo-, targeted molecular, and immune therapies emerge and show promising results in clinical trials, image-based...

Performance of deep learning-based algorithm for detection of ileocolic intussusception on abdominal radiographs of young children.

Scientific reports
The purpose of this study was to develop and test the performance of a deep learning-based algorithm to detect ileocolic intussusception using abdominal radiographs of young children. For the training set, children (≤5 years old) who underwent abdomi...

EEG-based image classification via a region-level stacked bi-directional deep learning framework.

BMC medical informatics and decision making
BACKGROUND: As a physiological signal, EEG data cannot be subjectively changed or hidden. Compared with other physiological signals, EEG signals are directly related to human cortical activities with excellent temporal resolution. After the rapid dev...

Incorporating medical code descriptions for diagnosis prediction in healthcare.

BMC medical informatics and decision making
BACKGROUND: Diagnosis aims to predict the future health status of patients according to their historical electronic health records (EHR), which is an important yet challenging task in healthcare informatics. Existing diagnosis prediction approaches m...

Representation learning of genomic sequence motifs with convolutional neural networks.

PLoS computational biology
Although convolutional neural networks (CNNs) have been applied to a variety of computational genomics problems, there remains a large gap in our understanding of how they build representations of regulatory genomic sequences. Here we perform systema...

Gait Biomarkers Classification by Combining Assembled Algorithms and Deep Learning: Results of a Local Study.

Computational and mathematical methods in medicine
Machine learning, one of the core disciplines of artificial intelligence, is an approach whose main emphasis is analytical model building. In other words, machine learning enables an automaton to make its own decisions based on a previous training pr...

Conflict management in the fusion of complementary segmentations of deformed kidneys and nephroblastoma.

Medical image analysis
The fusion of multiple segmentations aims to improve their accuracy in order to make them exploitable. However, conflicts may appear. In this paper, two conflict-management models are proposed for the fusion of complementary segmentations. This confl...

Fog Computing Employed Computer Aided Cancer Classification System Using Deep Neural Network in Internet of Things Based Healthcare System.

Journal of medical systems
Computer assisted automatic smart pattern analysis of cancer affected pixel structure takes critical role in pre-interventional decision making for oral cancer treatment. Internet of Things (IoT) in healthcare systems is now emerging solution for mod...