AIMC Topic: Humans

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VEGA is an interpretable generative model for inferring biological network activity in single-cell transcriptomics.

Nature communications
Deep learning architectures such as variational autoencoders have revolutionized the analysis of transcriptomics data. However, the latent space of these variational autoencoders offers little to no interpretability. To provide further biological ins...

Dynamic memory to alleviate catastrophic forgetting in continual learning with medical imaging.

Nature communications
Medical imaging is a central part of clinical diagnosis and treatment guidance. Machine learning has increasingly gained relevance because it captures features of disease and treatment response that are relevant for therapeutic decision-making. In cl...

An automated liver segmentation in liver iron concentration map using fuzzy c-means clustering combined with anatomical landmark data.

BMC medical imaging
BACKGROUND: To estimate median liver iron concentration (LIC) calculated from magnetic resonance imaging, excluded vessels of the liver parenchyma region were defined manually. Previous works proposed the automated method for excluding vessels from t...

An Agent-based Decision Support for a Vaccination Campaign.

Journal of medical systems
We explore the Covid-19 diffusion with an agent-based model of an Italian region with a population on a scale of 1:1000. We also simulate different vaccination strategies. From a decision support system perspective, we investigate the adoption of art...

Automatic radiotherapy delineation quality assurance on prostate MRI with deep learning in a multicentre clinical trial.

Physics in medicine and biology
Volume delineation quality assurance (QA) is particularly important in clinical trial settings where consistent protocol implementation is required, as outcomes will affect future as well current patients. Currently, where feasible, this is conducted...

COVID-19 Mortality Prediction From Deep Learning in a Large Multistate Electronic Health Record and Laboratory Information System Data Set: Algorithm Development and Validation.

Journal of medical Internet research
BACKGROUND: COVID-19 is caused by the SARS-CoV-2 virus and has strikingly heterogeneous clinical manifestations, with most individuals contracting mild disease but a substantial minority experiencing fulminant cardiopulmonary symptoms or death. The c...

A Novel Medical Image Denoising Method Based on Conditional Generative Adversarial Network.

Computational and mathematical methods in medicine
Medical image quality is highly relative to clinical diagnosis and treatment, leading to a popular research topic of medical image denoising. Image denoising based on deep learning methods has attracted considerable attention owing to its excellent a...

Compensated Fuzzy Neural Network-Based Music Teaching Ability Assessment Model.

Computational intelligence and neuroscience
College is the main place to carry out music teaching, and it is important to assess the music teaching ability in college effectively. Based on this, this paper firstly analyzes the necessity of music teaching ability assessment and briefly summariz...

Research on Information Visualization Graphic Design Teaching Based on DBN Algorithm.

Computational intelligence and neuroscience
With the advent of the era of big data, how to quickly obtain effective information and efficiently disseminate information technology has become the most popular topic. Studies have shown that the ability of the human brain to process data and infor...

Heller myotomy perforation: robotic visualization decreases perforation rate and revisional surgery is a perforation risk.

Journal of robotic surgery
Minimally invasive surgery (MIS) has improved surgical access to the foregut. While the benefits of MIS versus open surgery are well accepted, the relative benefits of laparoscopic versus robotic approaches continue to be debated. Procedure-specific ...