AIMC Topic: Deep Learning

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A deep CNN approach to decode motor preparation of upper limbs from time-frequency maps of EEG signals at source level.

Neural networks : the official journal of the International Neural Network Society
A system that can detect the intention to move and decode the planned movement could help all those subjects that can plan motion but are unable to implement it. In this paper, motor planning activity is investigated by using electroencephalographic ...

A deep learning approach for the blind logP prediction in SAMPL6 challenge.

Journal of computer-aided molecular design
Water octanol partition coefficient serves as a measure for the lipophilicity of a molecule and is important in the field of drug discovery. A novel method for computational prediction of logarithm of partition coefficient (logP) has been developed u...

Learning deformable registration of medical images with anatomical constraints.

Neural networks : the official journal of the International Neural Network Society
Deformable image registration is a fundamental problem in the field of medical image analysis. During the last years, we have witnessed the advent of deep learning-based image registration methods which achieve state-of-the-art performance, and drast...

A preliminary attempt to visualize nigrosome 1 in the substantia nigra for Parkinson's disease at 3T: An efficient susceptibility map-weighted imaging (SMWI) with quantitative susceptibility mapping using deep neural network (QSMnet).

Medical physics
PURPOSE: Visibility of nigrosome 1 in the substantia nigra (SN) is used as an MR imaging biomarker for Parkinson's disease. Because of lower susceptibility induced tissue contrast and SNR visualization of the SN pars compacta (SNPC) using conventiona...

SurgAI: deep learning for computerized laparoscopic image understanding in gynaecology.

Surgical endoscopy
BACKGROUND: In laparoscopy, the digital camera offers surgeons the opportunity to receive support from image-guided surgery systems. Such systems require image understanding, the ability for a computer to understand what the laparoscope sees. Image u...

Monitoring and detecting faults in wastewater treatment plants using deep learning.

Environmental monitoring and assessment
Wastewater treatment plants use many sensors to control energy consumption and discharge quality. These sensors produce a vast amount of data which can be efficiently monitored by automatic systems. Consequently, several different statistical and lea...

Combining deep learning with token selection for patient phenotyping from electronic health records.

Scientific reports
Artificial intelligence provides the opportunity to reveal important information buried in large amounts of complex data. Electronic health records (eHRs) are a source of such big data that provide a multitude of health related clinical information a...

Development and Evaluation of a Deep Learning System for Screening Retinal Hemorrhage Based on Ultra-Widefield Fundus Images.

Translational vision science & technology
PURPOSE: To develop and evaluate a deep learning (DL) system for retinal hemorrhage (RH) screening using ultra-widefield fundus (UWF) images.

Deep Learning for Natural Language Processing in Radiology-Fundamentals and a Systematic Review.

Journal of the American College of Radiology : JACR
PURPOSE: Natural language processing (NLP) enables conversion of free text into structured data. Recent innovations in deep learning technology provide improved NLP performance. We aimed to survey deep learning NLP fundamentals and review radiology-r...