AIMC Topic: Deep Learning

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A Deep-Learning Approach toward Rational Molecular Docking Protocol Selection.

Molecules (Basel, Switzerland)
While a plethora of different protein-ligand docking protocols have been developed over the past twenty years, their performances greatly depend on the provided input protein-ligand pair. In this study, we developed a machine-learning model that uses...

Using Artificial Intelligence for Pattern Recognition in a Sports Context.

Sensors (Basel, Switzerland)
Optimizing athlete's performance is one of the most important and challenging aspects of coaching. Physiological and positional data, often acquired using wearable devices, have been useful to identify patterns, thus leading to a better understanding...

Assessment of Generative Adversarial Networks Model for Synthetic Optical Coherence Tomography Images of Retinal Disorders.

Translational vision science & technology
PURPOSE: To assess whether a generative adversarial network (GAN) could synthesize realistic optical coherence tomography (OCT) images that satisfactorily serve as the educational images for retinal specialists, and the training datasets for the clas...

Same father, same face: Deep learning reveals selection for signaling kinship in a wild primate.

Science advances
Many animals rely on facial traits to recognize their kin; however, whether these traits have been selected specifically for this function remains unknown. Using deep learning for face recognition, we present the first evidence that interindividual f...

Deep learning architectures analysis for age-related macular degeneration segmentation on optical coherence tomography scans.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Aged people usually are more to be diagnosed with retinal diseases in developed countries. Retinal capillaries leakage into the retina swells and causes an acute vision loss, which is called age-related macular degeneration...

Synapse cell optimization and back-propagation algorithm implementation in a domain wall synapse based crossbar neural network for scalable on-chip learning.

Nanotechnology
On-chip learning in spin orbit torque driven domain wall synapse based crossbar fully connected neural network (FCNN) has been shown to be extremely efficient in terms of speed and energy, when compared to training on a conventional computing unit or...

Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis.

Proceedings of the National Academy of Sciences of the United States of America
Artificial intelligence (AI) systems for computer-aided diagnosis and image-based screening are being adopted worldwide by medical institutions. In such a context, generating fair and unbiased classifiers becomes of paramount importance. The research...

Non-invasive identification of swallows via deep learning in high resolution cervical auscultation recordings.

Scientific reports
High resolution cervical auscultation is a very promising noninvasive method for dysphagia screening and aspiration detection, as it does not involve the use of harmful ionizing radiation approaches. Automatic extraction of swallowing events in cervi...

Automatic Medical Code Assignment via Deep Learning Approach for Intelligent Healthcare.

IEEE journal of biomedical and health informatics
With the development of healthcare 4.0, there has been an explosion in the amount of data such as image, medical text, physiological signals, lab tests, etc. Among them, medical records provide a complete picture of the associated clinical events. Ho...

Dose image prediction for range and width verifications from carbon ion-induced secondary electron bremsstrahlung x-rays using deep learning workflow.

Medical physics
PURPOSE: Imaging of the secondary electron bremsstrahlung (SEB) x rays emitted during particle-ion irradiation is a promising method for beam range estimation. However, the SEB x-ray images are not directly correlated to the dose images. In addition,...