AIMC Topic: Machine Learning

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Evaluation of text-to-gesture generation model using convolutional neural network.

Neural networks : the official journal of the International Neural Network Society
Conversational gestures have a crucial role in realizing natural interactions with virtual agents and robots. Data-driven approaches, such as deep learning and machine learning, are promising in constructing the gesture generation model, which automa...

Collision Cross Section Calculations to Aid Metabolite Annotation.

Journal of the American Society for Mass Spectrometry
The interpretation of ion mobility coupled to mass spectrometry (IM-MS) data to predict unknown structures is challenging and depends on accurate theoretical estimates of the molecular ion collision cross section (CCS) against a buffer gas in a low o...

Introducing a Chemically Intuitive Core-Substituent Fingerprint Designed to Explore Structural Requirements for Effective Similarity Searching and Machine Learning.

Molecules (Basel, Switzerland)
Fingerprint (FP) representations of chemical structure continue to be one of the most widely used types of molecular descriptors in chemoinformatics and computational medicinal chemistry. One often distinguishes between two- and three-dimensional (2D...

SLEAP: A deep learning system for multi-animal pose tracking.

Nature methods
The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation in tools to quantify natural animal behavior. While advances in deep learning and computer vision have enabled markerless pose estimatio...

A Survey of End-to-End Driving: Architectures and Training Methods.

IEEE transactions on neural networks and learning systems
Autonomous driving is of great interest to industry and academia alike. The use of machine learning approaches for autonomous driving has long been studied, but mostly in the context of perception. In this article, we take a deeper look on the so-cal...

Design and Implementation of Advanced Machine Learning Management and Its Impact on Better Healthcare Services: A Multiple Regression Analysis Approach (MRAA).

Computational and mathematical methods in medicine
In the current information and technology era, business enterprises are focusing in performing the process effectively by reducing the waiting time in completing the work, reduce latency and deploy the resources effectively so as to service the patie...

Combining biomedical knowledge graphs and text to improve predictions for drug-target interactions and drug-indications.

PeerJ
Biomedical knowledge is represented in structured databases and published in biomedical literature, and different computational approaches have been developed to exploit each type of information in predictive models. However, the information in struc...

Structure Guided Deep Neural Network for Unsupervised Active Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Unsupervised active learning has become an active research topic in the machine learning and computer vision communities, whose goal is to choose a subset of representative samples to be labeled in an unsupervised setting. Most of existing approaches...

Machine learning approach to identify adverse events in scientific biomedical literature.

Clinical and translational science
Monitoring the occurrence of adverse events in the scientific literature is a mandatory process in drug marketing surveillance. This is a very time-consuming and complex task to fulfill the compliance and, most importantly, to ensure patient safety. ...

Statistical and machine learning methods to study human CD4 T cell proteome profiles.

Immunology letters
Mass spectrometry proteomics has become an important part of modern immunology, making major contributions to understanding protein expression levels, subcellular localizations, posttranslational modifications, and interactions in various immune cell...