AIMC Topic: Humans

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Automatic recognition of bladder tumours using deep learning technology and its clinical application.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Bladder cancer is a kind of tumors with a high recurrence rate. The improvement of the cure rate and prognosis of bladder tumor depends on the accurate recognition of bladder tumor under the cystoscope.

HDAC3i-Finder: A Machine Learning-based Computational Tool to Screen for HDAC3 Inhibitors.

Molecular informatics
Histone deacetylase 3 (HDAC3) is a potential drug target for treatment of human diseases such as cancer, chronic inflammation, neurodegenerative diseases and diabetes. Machine learning (ML) as an essential cheminformatics approach has been widely use...

Learning sparse and meaningful representations through embodiment.

Neural networks : the official journal of the International Neural Network Society
How do humans acquire a meaningful understanding of the world with little to no supervision or semantic labels provided by the environment? Here we investigate embodiment with a closed loop between action and perception as one key component in this p...

Mobile Health (mHealth) Viral Diagnostics Enabled with Adaptive Adversarial Learning.

ACS nano
Deep-learning (DL)-based image processing has potential to revolutionize the use of smartphones in mobile health (mHealth) diagnostics of infectious diseases. However, the high variability in cellphone image data acquisition and the common need for l...

ProxIQA: A Proxy Approach to Perceptual Optimization of Learned Image Compression.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The use of l (p = 1,2) norms has largely dominated the measurement of loss in neural networks due to their simplicity and analytical properties. However, when used to assess the loss of visual information, these simple norms are not very consistent w...

Deep learning with noise-to-noise training for denoising in SPECT myocardial perfusion imaging.

Medical physics
PURPOSE: Post-reconstruction filtering is often applied for noise suppression due to limited data counts in myocardial perfusion imaging (MPI) with single-photon emission computed tomography (SPECT). We study a deep learning (DL) approach for denoisi...

Artificial Intelligence, Machine Learning and Calculation of Intraocular Lens Power.

Klinische Monatsblatter fur Augenheilkunde
BACKGROUND AND PURPOSE: In the last decade, artificial intelligence and machine learning algorithms have been more and more established for the screening and detection of diseases and pathologies, as well as for describing interactions between measur...

Application of artificial neural networks to predict the COVID-19 outbreak.

Global health research and policy
BACKGROUND: Millions of people have been infected worldwide in the COVID-19 pandemic. In this study, we aim to propose fourteen prediction models based on artificial neural networks (ANN) to predict the COVID-19 outbreak for policy makers.