AIMC Topic: Deep Learning

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A novel adaptive cubic quasi-Newton optimizer for deep learning based medical image analysis tasks, validated on detection of COVID-19 and segmentation for COVID-19 lung infection, liver tumor, and optic disc/cup.

Medical physics
BACKGROUND: Most of existing deep learning research in medical image analysis is focused on networks with stronger performance. These networks have achieved success, while their architectures are complex and even contain massive parameters ranging fr...

Deep learning-based neural networks for day-ahead power load probability density forecasting.

Environmental science and pollution research international
Energy efficiency is crucial to greenhouse gas (GHG) emission pathways reported by the Intergovernmental Panel on Climate Change. Electrical overload frequently occurs and causes unwanted outages in distribution networks, which reduces energy utiliza...

Predictive gamma passing rate of 3D detector array-based volumetric modulated arc therapy quality assurance for prostate cancer via deep learning.

Physical and engineering sciences in medicine
To predict the gamma passing rate (GPR) of the three-dimensional (3D) detector array-based volumetric modulated arc therapy (VMAT) quality assurance (QA) for prostate cancer using a convolutional neural network (CNN) with the 3D dose distribution. On...

Multi-Objective Location and Mapping Based on Deep Learning and Visual Slam.

Sensors (Basel, Switzerland)
Simultaneous localization and mapping (SLAM) technology can be used to locate and build maps in unknown environments, but the constructed maps often suffer from poor readability and interactivity, and the primary and secondary information in the map ...

A Robust End-to-End Deep Learning-Based Approach for Effective and Reliable BTD Using MR Images.

Sensors (Basel, Switzerland)
Detection of a brain tumor in the early stages is critical for clinical practice and survival rate. Brain tumors arise in multiple shapes, sizes, and features with various treatment options. Tumor detection manually is challenging, time-consuming, an...

EnsembleSplice: ensemble deep learning model for splice site prediction.

BMC bioinformatics
BACKGROUND: Identifying splice site regions is an important step in the genomic DNA sequencing pipelines of biomedical and pharmaceutical research. Within this research purview, efficient and accurate splice site detection is highly desirable, and a ...

Using domain knowledge for robust and generalizable deep learning-based CT-free PET attenuation and scatter correction.

Nature communications
Despite the potential of deep learning (DL)-based methods in substituting CT-based PET attenuation and scatter correction for CT-free PET imaging, a critical bottleneck is their limited capability in handling large heterogeneity of tracers and scanne...

Monkeypox Virus Detection Using Pre-trained Deep Learning-based Approaches.

Journal of medical systems
Monkeypox virus is emerging slowly with the decline of COVID-19 virus infections around the world. People are afraid of it, thinking that it would appear as a pandemic like COVID-19. As such, it is crucial to detect them earlier before widespread com...

A deep learning approach to real-time volumetric measurements without image reconstruction for cardiovascular magnetic resonance.

Physiological measurement
Cardiovascular magnetic resonance (CMR) can measure ventricular volumes for the quantitative assessment of cardiac function in clinical cardiology. Conventionally, CMR volumetric measurements require image reconstruction and segmentation. There are l...

Design of Political Online Teaching Based on Artificial Speech Recognition and Deep Learning.

Computational intelligence and neuroscience
With the emergence of the information age, computers have entered the homes of ordinary people and have become essential daily appliances for people. The integration of people and computers has become more popular and in-depth. Based on this situatio...