AIMC Topic: Algorithms

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An artificial intelligence algorithm that identifies middle turbinate pneumatisation (concha bullosa) on sinus computed tomography scans.

The Journal of laryngology and otology
OBJECTIVE: Convolutional neural networks are a subclass of deep learning or artificial intelligence that are predominantly used for image analysis and classification. This proof-of-concept study attempts to train a convolutional neural network algori...

In Silico Prediction of Metabolic Epoxidation for Drug-like Molecules via Machine Learning Methods.

Molecular informatics
Epoxidation is one of the reactions in drug metabolism. Since epoxide metabolites would bind with proteins or DNA covalently, drugs should avoid epoxidation metabolism in the body. Due to the instability of epoxide, it is difficult to determine epoxi...

The Effect of Resampling on Data-imbalanced Conditions for Prediction towards Nuclear Receptor Profiling Using Deep Learning.

Molecular informatics
In toxicity evaluation based on the nuclear receptor signalling pathway, in silico prediction tools are used for the detection of the early stages of long-term toxicities, the prioritization of newly synthesized chemicals and the acquisition of the s...

The power of deep learning to ligand-based novel drug discovery.

Expert opinion on drug discovery
INTRODUCTION: Deep discriminative and generative neural-network models are becoming an integral part of the modern approach to ligand-based novel drug discovery. The variety of different architectures of neural networks, the methods of their training...

Smartphone as a monitoring tool for bipolar disorder: a systematic review including data analysis, machine learning algorithms and predictive modelling.

International journal of medical informatics
BACKGROUND: Bipolar disorder (BD) is a chronic illness with a high recurrence rate. Smartphones can be a useful tool for detecting prodromal symptoms of episode recurrence (through real-time monitoring) and providing options for early intervention be...

Kernel Granger Causality Based on Back Propagation Neural Network Fuzzy Inference System on fMRI Data.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Granger causality (GC) is one of the most popular measures to investigate causality influence among brain regions and has been achieved significant results for exploring brain networks based on functional magnetic resonance imaging (fMRI). However, t...

Improve Aggressive Driver Recognition Using Collision Surrogate Measurement and Imbalanced Class Boosting.

International journal of environmental research and public health
Real-time recognition of risky driving behavior and aggressive drivers is a promising research domain, thanks to powerful machine learning algorithms and the big data provided by in-vehicle and roadside sensors. However, since the occurrence of aggre...

Deep Joint Spatiotemporal Network (DJSTN) for Efficient Facial Expression Recognition.

Sensors (Basel, Switzerland)
Understanding a person's feelings is a very important process for the affective computing. People express their emotions in various ways. Among them, facial expression is the most effective way to present human emotional status. We propose efficient ...

Extracting Structured Genotype Information from Free-Text HLA Reports Using a Rule-Based Approach.

Journal of Korean medical science
BACKGROUND: Human leukocyte antigen (HLA) typing is important for transplant patients to prevent a severe mismatch reaction, and the result can also support the diagnosis of various disease or prediction of drug side effects. However, such secondary ...

What is AI? Applications of artificial intelligence to dermatology.

The British journal of dermatology
In the past, the skills required to make an accurate dermatological diagnosis have required exposure to thousands of patients over many years. However, in recent years, artificial intelligence (AI) has made enormous advances, particularly in the area...