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Computer Methods and Programs in Biomedicine
Scopus
ISSN 0169-2607 · Elsevier BV · 14 artikel di indeks
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Artikel Jurnal
DeepXplainer: An interpretable deep learning based approach for lung cancer detection using explainable artificial intelligence
BACKGROUND AND OBJECTIVE: Artificial intelligence (AI) has several uses in the healthcare industry, some of which include healthcare management, medical forecasting, practical making of decisions, and diagnosis. AI technologies have reached human-like performance, but their use is limited since…
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Artikel Jurnal Teks lengkap
Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective
BACKGROUND AND OBJECTIVE: Diabetes mellitus is a metabolic disorder characterized by hyperglycemia, which results from the inadequacy of the body to secrete and respond to insulin. If not properly managed or diagnosed on time, diabetes can pose a risk to vital body organs such as the eyes, kidneys…
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Artikel Jurnal Teks lengkap
Computer-aided diagnosis for breast cancer classification using deep neural networks and transfer learning
BACKGROUND AND OBJECTIVE: Many developed and non-developed countries worldwide suffer from cancer-related fatal diseases. In particular, the rate of breast cancer in females increases daily, partially due to unawareness and undiagnosed at the early stages. A proper first breast cancer treatment can…
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Artikel Jurnal Teks lengkap
Medical deep learning—A systematic meta-review
Deep learning has remarkably impacted several different scientific disciplines over the last few years. For example, in image processing and analysis, deep learning algorithms were able to outperform other cutting-edge methods. Additionally, deep learning has delivered state-of-the-art results in…
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Artikel Jurnal Teks lengkap
TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning
BACKGROUND AND OBJECTIVE: Processing of medical images such as MRI or CT presents different challenges compared to RGB images typically used in computer vision. These include a lack of labels for large datasets, high computational costs, and the need of metadata to describe the physical properties…
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Artikel Jurnal Teks lengkap
Effects of dataset size and interactions on the prediction performance of logistic regression and deep learning models
BACKGROUND AND OBJECTIVE: Machine learning and deep learning models are very powerful in predicting the presence of a disease. To achieve good predictions, those models require a certain amount of data to train on, whereas this amount i) is generally limited and difficult to obtain; and, ii)…
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Artikel Jurnal Teks lengkap
CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images
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Artikel Jurnal Teks lengkap
COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios