AIMC Topic: Deep Learning

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Identification of Atrial Fibrillation With Single-Lead Mobile ECG During Normal Sinus Rhythm Using Deep Learning.

Journal of Korean medical science
BACKGROUND: The acquisition of single-lead electrocardiogram (ECG) from mobile devices offers a more practical approach to arrhythmia detection. Using artificial intelligence for atrial fibrillation (AF) identification enhances screening efficiency. ...

Comparison of Sysmex XN-V body fluid mode and deep-learning-based quantification with manual techniques for total nucleated cell count and differential count for equine bronchoalveolar lavage samples.

BMC veterinary research
BACKGROUND: Bronchoalveolar lavage (BAL) is a diagnostic method for the assessment of the lower respiratory airway health status in horses. Differential cell count and sometimes also total nucleated cell count (TNCC) are routinely measured by time-co...

A systematic analysis of deep learning in genomics and histopathology for precision oncology.

BMC medical genomics
BACKGROUND: Digitized histopathological tissue slides and genomics profiling data are available for many patients with solid tumors. In the last 5 years, Deep Learning (DL) has been broadly used to extract clinically actionable information and biolog...

Deep learning-based diffusion tensor image generation model: a proof-of-concept study.

Scientific reports
This study created an image-to-image translation model that synthesizes diffusion tensor images (DTI) from conventional diffusion weighted images, and validated the similarities between the original and synthetic DTI. Thirty-two healthy volunteers we...

Deep-WET: a deep learning-based approach for predicting DNA-binding proteins using word embedding techniques with weighted features.

Scientific reports
DNA-binding proteins (DBPs) play a significant role in all phases of genetic processes, including DNA recombination, repair, and modification. They are often utilized in drug discovery as fundamental elements of steroids, antibiotics, and anticancer ...

Deep learning algorithm-based multimodal MRI radiomics and pathomics data improve prediction of bone metastases in primary prostate cancer.

Journal of cancer research and clinical oncology
PURPOSE: Bone metastasis is a significant contributor to morbidity and mortality in advanced prostate cancer, and early diagnosis is challenging due to its insidious onset. The use of machine learning to obtain prognostic information from pathologica...

ENVINet5 deep learning change detection framework for the estimation of agriculture variations during 2012-2023 with Landsat series data.

Environmental monitoring and assessment
Remote sensing is one of the most important methods for analysing the multitemporal changes over a certain period. As a cost-effective way, remote sensing allows the long-term analysis of agricultural land by collecting satellite imagery from differe...

The use of deep learning integrating image recognition in language analysis technology in secondary school education.

Scientific reports
This work aims to investigate the application of advanced deep learning algorithms and image recognition technologies to enhance language analysis tools in secondary education, with the goal of providing educators with more effective resources and su...

Interactive content-based image retrieval with deep learning for CT abdominal organ recognition.

Physics in medicine and biology
Recognizing the most relevant seven organs in an abdominal computed tomography (CT) slice requires sophisticated knowledge. This study proposed automatically extracting relevant features and applying them in a content-based image retrieval (CBIR) sys...

Interactive segmentation of medical images using deep learning.

Physics in medicine and biology
Medical image segmentation algorithms based on deep learning have achieved good segmentation results in recent years, but they require a large amount of labeled data. When performing pixel-level labeling on medical images, labeling a target requires ...