AIMC Topic: Neural Networks, Computer

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DeepAffinity: interpretable deep learning of compound-protein affinity through unified recurrent and convolutional neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Drug discovery demands rapid quantification of compound-protein interaction (CPI). However, there is a lack of methods that can predict compound-protein affinity from sequences alone with high applicability, accuracy and interpretability.

Biological sequence modeling with convolutional kernel networks.

Bioinformatics (Oxford, England)
MOTIVATION: The growing number of annotated biological sequences available makes it possible to learn genotype-phenotype relationships from data with increasingly high accuracy. When large quantities of labeled samples are available for training a mo...

Extending a Knowledge-Based System with Learning Capacity.

Studies in health technology and informatics
Informal caregivers often complain about missing knowledge. A knowledge-based personalized educational system is developed, which provides caregiving relatives with the information needed. Yet, evaluation against domain experts indicated, that parts ...

Magnetic Resonance Fingerprinting Reconstruction Using Recurrent Neural Networks.

Studies in health technology and informatics
Magnetic Resonance Fingerprinting (MRF) is an imaging technique acquiring unique time signals for different tissues. Although the acquisition is highly accelerated, the reconstruction time remains a problem, as the state-of-the-art template matching ...

[Chapter 6. Hybridisation of networks.].

Journal international de bioethique et d'ethique des sciences
Prompted by the digital revolution, the hybridisation of networks, terrestrial and on satellites, opens the door to a world of convergences, dominated by the Internet of Objects and the development of artificial intelligence.

Sound source ranging using a feed-forward neural network trained with fitting-based early stopping.

The Journal of the Acoustical Society of America
When a feed-forward neural network (FNN) is trained for acoustic source ranging in an ocean waveguide, it is difficult evaluating the FNN ranging accuracy of unlabeled test data. The label is the distance between source and receiver array. A fitting-...

Clinical Data Extraction and Normalization of Cyrillic Electronic Health Records Via Deep-Learning Natural Language Processing.

JCO clinical cancer informatics
PURPOSE: A substantial portion of medical data is unstructured. Extracting data from unstructured text presents a barrier to advancing clinical research and improving patient care. In addition, ongoing studies have been focused predominately on the E...

A new and efficient numerical method for the fractional modeling and optimal control of diabetes and tuberculosis co-existence.

Chaos (Woodbury, N.Y.)
The main objective of this research is to investigate a new fractional mathematical model involving a nonsingular derivative operator to discuss the clinical implications of diabetes and tuberculosis coexistence. The new model involves two distinct p...

Taylor and Gradient Descent-Based Actor Critic Neural Network for the Classification of Privacy Preserved Medical Data.

Big data
Classification of the privacy preserved medical data is the domain of the researchers as it stirs the importance behind hiding the sensitive data from the third-party authenticator. Ensuring the privacy of the medical records and using the disease pr...