AIMC Topic: Deep Learning

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An interpretable multi-task system for clinically applicable COVID-19 diagnosis using CXR.

Journal of X-ray science and technology
BACKGROUND: With the emergence of continuously mutating variants of coronavirus, it is urgent to develop a deep learning model for automatic COVID-19 diagnosis at early stages from chest X-ray images. Since laboratory testing is time-consuming and re...

Automatic Localization and Identification of Thoracic Diseases from Chest X-rays with Deep Learning.

Current medical imaging
BACKGROUND: There are numerous difficulties in using deep learning to automatically locate and identify diseases in chest X-rays (CXR). The most prevailing two are the lack of labeled data of disease locations and poor model transferability between d...

Deep learning-based prediction of heart failure rehospitalization during 6, 12, 24-month follow-ups in patients with acute myocardial infarction.

Health informatics journal
Heart failure is a clinical syndrome that occurs when the heart is too weak or stiff and cannot pump enough blood that our body needs. It is one of the most expensive diseases due to frequent hospitalizations and emergency room visits. Reducing unnec...

Pattern Classification for Ovarian Tumors by Integration of Radiomics and Deep Learning Features.

Current medical imaging
BACKGROUND: Ovarian tumor is a common female genital tumor, among which malignant tumors have a poor prognosis. The survival rate of 70% of patients with ovarian cancer is less than 5 years, while benign ovarian tumor is better, so the early diagnosi...

Predicting antibody binders and generating synthetic antibodies using deep learning.

mAbs
The antibody drug field has continually sought improvements to methods for candidate discovery and engineering. Historically, most such methods have been laboratory-based, but informatics methods have recently started to make an impact. Deep learning...

Inferring Cell-type-specific Genes of Lung Cancer Based on Deep Learning.

Current gene therapy
BACKGROUND: Lung cancer is cancer with the highest incidence in the world, and there is obvious heterogeneity within its tumor. The emergence of single-cell sequencing technology allows researchers to obtain cell-type-specific expression genes at the...

[Discrimination of Chin Electromyography in REM Sleep Behavior Disorder Using Deep Learning].

Nihon eiseigaku zasshi. Japanese journal of hygiene
OBJECTIVE: The confirmation of abnormal behavior during video monitoring in polysomnography (PSG) and the frequency of rapid eye movement (REM) sleep without atonia (RWA) during REM sleep based on physiological indicators are essential diagnostic cri...

Leukemia classification using the deep learning method of CNN.

Journal of X-ray science and technology
BACKGROUND: Processing Low-Intensity Medical Images (LI-MI) is difficult as outcomes are varied when it comes to manual examination, which is also a time-consuming process.