AIMC Topic: Deep Learning

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AI Based Monitoring of Different Risk Levels in COVID-19 Context.

Sensors (Basel, Switzerland)
COVID-19 was responsible for devastating social, economic, and political effects all over the world. Although the health authorities imposed restrictions provided relief and assisted with trying to return society to normal life, it is imperative to m...

Automated segmentation of metal stent and bioresorbable vascular scaffold in intravascular optical coherence tomography images using deep learning architectures.

Physics in medicine and biology
Percutaneous coronary intervention (PCI) with stent placement is a treatment effective for coronary artery diseases. Intravascular optical coherence tomography (OCT) with high resolution is used clinically to visualize stent deployment and restenosis...

Online public opinion evaluation through the functional resonance analysis method and deep analysis.

PloS one
A conventional model of public opinion analysis is no longer suitable when the internet is the primary arena of information dissemination. Thus, a more practical approach is urgently needed to deal with this dynamic and complicated phenomenon of prop...

Deep learning-based whole-heart segmentation in 4D contrast-enhanced cardiac CT.

Computers in biology and medicine
Automatic cardiac chamber and left ventricular (LV) myocardium segmentation over the cardiac cycle significantly extends the utilization of contrast-enhanced cardiac CT, potentially enabling in-depth assessment of cardiac function. Therefore, we eval...

BEMD-3DCNN-based method for COVID-19 detection.

Computers in biology and medicine
The coronavirus outbreak continues to spread around the world and no one knows when it will stop. Therefore, from the first day of the identification of the virus in Wuhan, China, scientists have launched numerous research projects to understand the ...

Computer-assisted mitotic count using a deep learning-based algorithm improves interobserver reproducibility and accuracy.

Veterinary pathology
The mitotic count (MC) is an important histological parameter for prognostication of malignant neoplasms. However, it has inter- and intraobserver discrepancies due to difficulties in selecting the region of interest (MC-ROI) and in identifying or cl...

Deep learning for retention time prediction in reversed-phase liquid chromatography.

Journal of chromatography. A
Retention time prediction in high-performance liquid chromatography (HPLC) is the subject of many studies since it can improve the identification of unknown molecules in untargeted profiling using HPLC coupled with high-resolution mass spectrometry. ...

Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies.

Journal of biomedical informatics
OBJECTIVE: Temporal electronic health records (EHRs) contain a wealth of information for secondary uses, such as clinical events prediction and chronic disease management. However, challenges exist for temporal data representation. We therefore sough...

Model-Driven Deep Learning Method for Pancreatic Cancer Segmentation Based on Spiral-Transformation.

IEEE transactions on medical imaging
Pancreatic cancer is a lethal malignant tumor with one of the worst prognoses. Accurate segmentation of pancreatic cancer is vital in clinical diagnosis and treatment. Due to the unclear boundary and small size of cancers, it is challenging to both m...

False Ceiling Deterioration Detection and Mapping Using a Deep Learning Framework and the Teleoperated Reconfigurable 'Falcon' Robot.

Sensors (Basel, Switzerland)
Periodic inspection of false ceilings is mandatory to ensure building and human safety. Generally, false ceiling inspection includes identifying structural defects, degradation in Heating, Ventilation, and Air Conditioning (HVAC) systems, electrical ...