AIMC Topic:
Databases, Factual
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Predicting sepsis with a recurrent neural network using the MIMIC III database.
Computers in biology and medicine
Aug 20, 2019
OBJECTIVE: Predicting sepsis onset with a recurrent neural network and performance comparison with InSight - a previously proposed algorithm for the prediction of sepsis onset.
Significance of Data Selection in Deep Learning for Reliable Binding Mode Prediction of Ligands in the Active Site of CYP3A4.
Chemical & pharmaceutical bulletin
Aug 17, 2019
For rational drug design, it is essential to predict the binding mode of protein-ligand complexes. Although various machine learning-based models have been reported that use convolutional neural networks (deep learning) to predict binding modes from ...
Automatic Pulmonary Nodule Detection in CT Scans Using Convolutional Neural Networks Based on Maximum Intensity Projection.
IEEE transactions on medical imaging
Aug 15, 2019
Accurate pulmonary nodule detection is a crucial step in lung cancer screening. Computer-aided detection (CAD) systems are not routinely used by radiologists for pulmonary nodule detection in clinical practice despite their potential benefits. Maximu...
A Lightweight API-Based Approach for Building Flexible Clinical NLP Systems.
Journal of healthcare engineering
Aug 15, 2019
Natural language processing (NLP) has become essential for secondary use of clinical data. Over the last two decades, many clinical NLP systems were developed in both academia and industry. However, nearly all existing systems are restricted to speci...
Artificial Intelligence Approach To Investigate the Longevity Drug.
The journal of physical chemistry letters
Aug 14, 2019
Longevity is a very important and interesting topic, and has been demonstrated to be related to longevity. We combined network pharmacology, machine learning, deep learning, and molecular dynamics (MD) simulation to investigate potent lead drugs. Re...
Algorithms
Databases, Factual
Molecular Docking Simulation
Drug Discovery
Artificial Intelligence
Receptor, Insulin
Receptor, IGF Type 1
Antigens, CD
Ligands
Inhibitory Concentration 50
Binding Sites
Thermodynamics
Protein Interaction Maps
Medicine, Chinese Traditional
Protein Binding
Signal Transduction
Klotho Proteins
Glucuronidase
Deep learning-based electroencephalography analysis: a systematic review.
Journal of neural engineering
Aug 14, 2019
CONTEXT: Electroencephalography (EEG) is a complex signal and can require several years of training, as well as advanced signal processing and feature extraction methodologies to be correctly interpreted. Recently, deep learning (DL) has shown great ...
Boundary-Weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation.
IEEE transactions on medical imaging
Aug 13, 2019
Accurate segmentation of the prostate from magnetic resonance (MR) images provides useful information for prostate cancer diagnosis and treatment. However, automated prostate segmentation from 3D MR images faces several challenges. The lack of clear ...
Multi-Task Deep Model With Margin Ranking Loss for Lung Nodule Analysis.
IEEE transactions on medical imaging
Aug 12, 2019
Lung cancer is the leading cause of cancer deaths worldwide and early diagnosis of lung nodule is of great importance for therapeutic treatment and saving lives. Automated lung nodule analysis requires both accurate lung nodule benign-malignant class...
Automatic diagnosis of fungal keratitis using data augmentation and image fusion with deep convolutional neural network.
Computer methods and programs in biomedicine
Aug 9, 2019
BACKGROUND AND OBJECTIVES: Fungal keratitis is caused by inflammation of the cornea that results from infection by fungal organisms. The lack of an early effective diagnosis often results in serious complications even blindness. Confocal microscopy i...
Automated detection of diabetic subject using pre-trained 2D-CNN models with frequency spectrum images extracted from heart rate signals.
Computers in biology and medicine
Aug 9, 2019
In this study, a deep-transfer learning approach is proposed for the automated diagnosis of diabetes mellitus (DM), using heart rate (HR) signals obtained from electrocardiogram (ECG) data. Recent progress in deep learning has contributed significant...
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