AIMC Topic: Deep Learning

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Ultrasound Deep Learning for Wall Segmentation and Near-Wall Blood Flow Measurement.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Studies of medical flow imaging have technical limitations for accurate analysis of blood flow dynamics and vessel wall interaction at arteries. We propose a new deep learning-based boundary detection and compensation (DL-BDC) technique in ultrasound...

Progressive learning: A deep learning framework for continual learning.

Neural networks : the official journal of the International Neural Network Society
Continual learning is the ability of a learning system to solve new tasks by utilizing previously acquired knowledge from learning and performing prior tasks without having significant adverse effects on the acquired prior knowledge. Continual learni...

A high-throughput system combining microfluidic hydrogel droplets with deep learning for screening the antisolvent-crystallization conditions of active pharmaceutical ingredients.

Lab on a chip
Crystallization of active pharmaceutical ingredients (APIs) is a crucial process in the pharmaceutical industry due to its great impact in drug efficacy. However, conventional approaches for screening the optimal crystallization conditions of APIs ar...

Predicting conversion to wet age-related macular degeneration using deep learning.

Nature medicine
Progression to exudative 'wet' age-related macular degeneration (exAMD) is a major cause of visual deterioration. In patients diagnosed with exAMD in one eye, we introduce an artificial intelligence (AI) system to predict progression to exAMD in the ...

A Deep Neural Network for the Rapid Prediction of X-ray Absorption Spectra.

The journal of physical chemistry. A
X-ray spectroscopy delivers strong impact across the physical and biological sciences by providing end users with highly detailed information about the electronic and geometric structure of matter. To decode this information in challenging cases, , ...

Industry 4.0 Lean Shopfloor Management Characterization Using EEG Sensors and Deep Learning.

Sensors (Basel, Switzerland)
Achieving the shift towards Industry 4.0 is only feasible through the active integration of the shopfloor into the transformation process. Several shopfloor management (SM) systems can aid this conversion. They form two major factions. The first incl...

Interpretable Learning Approaches in Resting-State Functional Connectivity Analysis: The Case of Autism Spectrum Disorder.

Computational and mathematical methods in medicine
Deep neural networks have recently been applied to the study of brain disorders such as autism spectrum disorder (ASD) with great success. However, the internal logics of these networks are difficult to interpret, especially with regard to how specif...

Deep learning for dermatologists: Part I. Fundamental concepts.

Journal of the American Academy of Dermatology
Artificial intelligence is generating substantial interest in the field of medicine. One form of artificial intelligence, deep learning, has led to rapid advances in automated image analysis. In 2017, an algorithm demonstrated the ability to diagnose...