AIMC Topic: Deep Learning

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EDLM: Ensemble Deep Learning Model to Detect Mutation for the Early Detection of Cholangiocarcinoma.

Genes
The most common cause of mortality and disability globally right now is cholangiocarcinoma, one of the worst forms of cancer that may affect people. When cholangiocarcinoma develops, the DNA of the bile duct cells is altered. Cholangiocarcinoma claim...

A survey on automatic generation of medical imaging reports based on deep learning.

Biomedical engineering online
Recent advances in deep learning have shown great potential for the automatic generation of medical imaging reports. Deep learning techniques, inspired by image captioning, have made significant progress in the field of diagnostic report generation. ...

Single-frame deep-learning super-resolution microscopy for intracellular dynamics imaging.

Nature communications
Single-molecule localization microscopy (SMLM) can be used to resolve subcellular structures and achieve a tenfold improvement in spatial resolution compared to that obtained by conventional fluorescence microscopy. However, the separation of single-...

Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images.

PloS one
Deep learning technology has been used in the medical field to produce devices for clinical practice. Deep learning methods in cytology offer the potential to enhance cancer screening while also providing quantitative, objective, and highly reproduci...

Automated 3-dimensional MRI segmentation for the posterosuperior rotator cuff tear lesion using deep learning algorithm.

PloS one
INTRODUCTION: Rotator cuff tear (RCT) is a challenging and common musculoskeletal disease. Magnetic resonance imaging (MRI) is a commonly used diagnostic modality for RCT, but the interpretation of the results is tedious and has some reliability issu...

A deep learning analysis of body kinematics during magnetically tethered flight.

Journal of neurogenetics
Flying rely on their vision to detect visual objects and adjust their flight course. Despite their robust fixation on a dark, vertical bar, our understanding of the underlying visuomotor neural circuits remains limited, in part due to difficulties i...

Vision-based food nutrition estimation via RGB-D fusion network.

Food chemistry
With the development of deep learning technology, vision-based food nutrition estimation is gradually entering the public view for its advantage in accuracy and efficiency. In this paper, we designed one RGB-D fusion network, which integrated multimo...

Rapid and precise detection of cancers via label-free SERS and deep learning.

Analytical and bioanalytical chemistry
Early, express, and reliable detection of cancer can provide a favorable prognosis and decrease mortality. Tumor biomarkers have been proven to be closely related to tumor occurrence and development. Conventional tumor biomarker detection based on ge...

Virtual Screening of Nrf2 Dietary-Derived Agonists and Safety by a New Deep-Learning Model and Verified and .

Journal of agricultural and food chemistry
Nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is an essential regulatory target of antioxidants, but the lack of Nrf2 active site information has hindered discovery of new Nrf2 agonists from food-derived compounds by large-scale virtual screenin...

Development of a deep learning system to detect glaucoma using macular vertical optical coherence tomography scans of myopic eyes.

Scientific reports
Myopia is one of the risk factors for glaucoma, making accurate diagnosis of glaucoma in myopic eyes particularly important. However, diagnosis of glaucoma in myopic eyes is challenging due to the frequent associations of distorted optic disc and dis...