AIMC Topic: Algorithms

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GSTCNet: Gated spatio-temporal correlation network for stroke mortality prediction.

Mathematical biosciences and engineering : MBE
Stroke continues to be the most common cause of death in China. It has great significance for mortality prediction for stroke patients, especially in terms of analyzing the complex interactions between non-negligible factors. In this paper, we presen...

Automated medical literature screening using artificial intelligence: a systematic review and meta-analysis.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We aim to investigate the application and accuracy of artificial intelligence (AI) methods for automated medical literature screening for systematic reviews.

A two-step method for paroxysmal atrial fibrillation event detection based on machine learning.

Mathematical biosciences and engineering : MBE
Detection of atrial fibrillation (AF) events is significant for early clinical diagnosis and appropriate intervention. However, in existing detection algorithms for paroxysmal AF (AFp), the location of AF starting and ending points in AFp is not conc...

Detection of weak micro-scratches on aspherical lenses using a Gabor neural network and transfer learning.

Applied optics
Surface defect detection is a crucial step in ensuring the quality of lenses. One method to check for surface defects is to use an optical system integrated with an industrial camera to magnify and highlight the position of a defect on the surface of...

Temporal convolution network with a dual attention mechanism for φ-OTDR event classification.

Applied optics
We propose a hybrid model named channel attention based temporal convolutional network combined with spatial attention and bidirectional long short-term memory network (ATCN-SA-BiLSTM) for phase sensitive optical time domain reflectometry signal reco...

A Multicenter Clinical Study of the Automated Fundus Screening Algorithm.

Translational vision science & technology
PURPOSE: To evaluate the effectiveness of automated fundus screening software in detecting eye diseases by comparing the reported results against those given by human experts.

DEMO2: Assemble multi-domain protein structures by coupling analogous template alignments with deep-learning inter-domain restraint prediction.

Nucleic acids research
Most proteins in nature contain multiple folding units (or domains). The revolutionary success of AlphaFold2 in single-domain structure prediction showed potential to extend deep-learning techniques for multi-domain structure modeling. This work pres...

LOMETS3: integrating deep learning and profile alignment for advanced protein template recognition and function annotation.

Nucleic acids research
Deep learning techniques have significantly advanced the field of protein structure prediction. LOMETS3 (https://zhanglab.ccmb.med.umich.edu/LOMETS/) is a new generation meta-server approach to template-based protein structure prediction and function...

T-S fuzzy observer-based adaptive tracking control for biological system with stage structure.

Mathematical biosciences and engineering : MBE
In this paper, the T-S fuzzy observer-based adaptive tracking control of the biological system with stage structure is studied. First, a biological model with stage structure is established, and its stability at the equilibrium points is analyzed. Co...

Multi-Expert Deep Networks for Multi-Disease Detection in Retinal Fundus Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic diagnosis of eye diseases from retinal fundus images is quite challenging. Common public datasets include images of subjects with multiple diseases with uneven distribution of labels. Rare diseases are especially challenging due to their un...