AIMC Topic: Neural Networks, Computer

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Improving the detection of hypo-vascular liver metastases in multiphase contrast-enhanced CT with slice thickness less than 5 mm using DenseNet.

Radiography (London, England : 1995)
INTRODUCTION: Thinner slices are more susceptible in detecting small lesions but suffer from higher statistical fluctuation. This work aimed to reduce image noise in multiphase contrast-enhanced CT reconstructed with slice thickness thinner than the ...

Coarse-Grained Crystal Graph Neural Networks for Reticular Materials Design.

Journal of chemical information and modeling
Reticular materials, including metal-organic frameworks and covalent organic frameworks, combine the relative ease of synthesis and an impressive range of applications in various fields from gas storage to biomedicine. Diverse properties arise from t...

Artificial intelligence in tongue diagnosis: classification of tongue lesions and normal tongue images using deep convolutional neural network.

BMC medical imaging
OBJECTIVE: This study aims to classify tongue lesion types using tongue images utilizing Deep Convolutional Neural Networks (DCNNs).

scFSNN: a feature selection method based on neural network for single-cell RNA-seq data.

BMC genomics
While single-cell RNA sequencing (scRNA-seq) allows researchers to analyze gene expression in individual cells, its unique characteristics like over-dispersion, zero-inflation, high gene-gene correlation, and large data volume with many features pose...

Segmentation-based cardiomegaly detection based on semi-supervised estimation of cardiothoracic ratio.

Scientific reports
The successful integration of neural networks in a clinical setting is still uncommon despite major successes achieved by artificial intelligence in other domains. This is mainly due to the black box characteristic of most optimized models and the un...

Deep model predictive control of gene expression in thousands of single cells.

Nature communications
Gene expression is inherently dynamic, due to complex regulation and stochastic biochemical events. However, the effects of these dynamics on cell phenotypes can be difficult to determine. Researchers have historically been limited to passive observa...

PMF-CNN: parallel multi-band fusion convolutional neural network for SSVEP-EEG decoding.

Biomedical physics & engineering express
Steady-state visual evoked potential (SSVEP) is a key technique of electroencephalography (EEG)-based brain-computer interfaces (BCI), which has been widely applied to neurological function assessment and postoperative rehabilitation. However, accura...

Feasibility and validity of using deep learning to reconstruct 12-lead ECG from three‑lead signals.

Journal of electrocardiology
BACKGROUND: In the field of mobile health, portable dynamic electrocardiogram (ECG) monitoring devices often have a limited number of lead electrodes due to considerations, such as portability and battery life. This situation leads to a contradiction...

Predicting 30-day unplanned hospital readmission after revision total knee arthroplasty: machine learning model analysis of a national patient cohort.

Medical & biological engineering & computing
Revision total knee arthroplasty (TKA) is associated with a higher risk of readmission than primary TKA. Identifying individual patients predisposed to readmission can facilitate proactive optimization and increase care efficiency. This study develop...