AIMC Topic: Algorithms

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Multitask Learning and Reinforcement Learning for Personalized Dialog Generation: An Empirical Study.

IEEE transactions on neural networks and learning systems
Open-domain dialog generation, which is a crucial component of artificial intelligence, is an essential and challenging problem. In this article, we present a personalized dialog system, which leverages the advantages of multitask learning and reinfo...

Diagnostic value of deep learning reconstruction for radiation dose reduction at abdominal ultra-high-resolution CT.

European radiology
OBJECTIVES: We evaluated lower dose (LD) hepatic dynamic ultra-high-resolution computed tomography (U-HRCT) images reconstructed with deep learning reconstruction (DLR), hybrid iterative reconstruction (hybrid-IR), or model-based IR (MBIR) in compari...

Constraints on Hebbian and STDP learned weights of a spiking neuron.

Neural networks : the official journal of the International Neural Network Society
We analyse mathematically the constraints on weights resulting from Hebbian and STDP learning rules applied to a spiking neuron with weight normalisation. In the case of pure Hebbian learning, we find that the normalised weights equal the promotion p...

A machine learning-based framework for diagnosis of COVID-19 from chest X-ray images.

Interdisciplinary sciences, computational life sciences
Corona virus disease (COVID-19) acknowledged as a pandemic by the WHO and mankind all over the world is vulnerable to this virus. Alternative tools are needed that can help in diagnosis of the coronavirus. Researchers of this article investigated the...

Over-fitting suppression training strategies for deep learning-based atrial fibrillation detection.

Medical & biological engineering & computing
Nowadays, deep learning-based models have been widely developed for atrial fibrillation (AF) detection in electrocardiogram (ECG) signals. However, owing to the inevitable over-fitting problem, classification accuracy of the developed models severely...

Modified multiscale weighted permutation entropy and optimized support vector machine method for rolling bearing fault diagnosis with complex signals.

ISA transactions
The rolling bearing vibration signals are complex, non-linear, and non-stationary, it is difficult to extract the sensitive features and diagnose faults by conventional signal processing methods. This paper focuses on the sensitive features extractio...

Integrated meta-analysis and machine learning approach identifies acyl-CoA thioesterase with other novel genes responsible for biofilm development in Staphylococcus aureus.

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
Biofilm forming Staphylococcus aureus is a major threat to the health-care industry. It is important to understand the differences between planktonic and biofilm growth forms in the pathogen since conventional treatments targeting the planktonic form...

sgRNACNN: identifying sgRNA on-target activity in four crops using ensembles of convolutional neural networks.

Plant molecular biology
We proposed an ensemble convolutional neural network model to identify sgRNA high on-target activity in four crops and we used one-hot encoding and k-mers for sequence encoding. As an important component of the CRISPR/Cas9 system, single-guide RNA (s...

Fully end-to-end deep-learning-based diagnosis of pancreatic tumors.

Theranostics
Artificial intelligence can facilitate clinical decision making by considering massive amounts of medical imaging data. Various algorithms have been implemented for different clinical applications. Accurate diagnosis and treatment require reliable an...

Feature extraction of EEG signals based on functional data analysis and its application to recognition of driver fatigue state.

Physiological measurement
OBJECTIVE: Our objective is to study how to obtain features which can reflect the continuity and internal dynamic changes of electroencephalography (EEG) signals and study an effective method for fatigued driving state recognition based on the obtain...