AIMC Topic: Neural Networks, Computer

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Deep Neural Networks for Automated Outer Plexiform Layer Subsidence Detection on Retinal OCT of Patients With Intermediate AMD.

Translational vision science & technology
PURPOSE: The subsidence of the outer plexiform layer (OPL) is an important imaging biomarker on optical coherence tomography (OCT) associated with early outer retinal atrophy and a risk factor for progression to geographic atrophy in patients with in...

Convolutional neural network models applied to neuronal responses in macaque V1 reveal limited nonlinear processing.

Journal of vision
Computational models of the primary visual cortex (V1) have suggested that V1 neurons behave like Gabor filters followed by simple nonlinearities. However, recent work employing convolutional neural network (CNN) models has suggested that V1 relies o...

Deep-Learning Model for Tumor-Type Prediction Using Targeted Clinical Genomic Sequencing Data.

Cancer discovery
UNLABELLED: Tumor type guides clinical treatment decisions in cancer, but histology-based diagnosis remains challenging. Genomic alterations are highly diagnostic of tumor type, and tumor-type classifiers trained on genomic features have been explore...

Neural Architecture Search Using Covariance Matrix Adaptation Evolution Strategy.

Evolutionary computation
Evolution-based neural architecture search methods have shown promising results, but they require high computational resources because these methods involve training each candidate architecture from scratch and then evaluating its fitness, which resu...

Integration of autoencoder and graph convolutional network for predicting breast cancer drug response.

Journal of bioinformatics and computational biology
Breast cancer is the most prevalent type of cancer among women. The effectiveness of anticancer pharmacological therapy may get adversely affected by tumor heterogeneity that includes genetic and transcriptomic features. This leads to clinical varia...

Clinical named entity recognition for percutaneous coronary intervention surgical information with hybrid neural network.

The Review of scientific instruments
Percutaneous coronary intervention (PCI) has become a vital treatment approach for coronary artery disease, but the clinical data of PCI cannot be directly utilized due to its unstructured characteristics. The existing clinical named entity recogniti...

Osteoporotic Precise Screening Using Chest Radiography and Artificial Neural Network: The OPSCAN Randomized Controlled Trial.

Radiology
Background Diagnosing osteoporosis is challenging due to its often asymptomatic presentation, which highlights the importance of providing screening for high-risk populations. Purpose To evaluate the effectiveness of dual-energy x-ray absorptiometry ...

RELATIONAL DIMENSION VERSUS ARTIFICIAL INTELLIGENCE.

American journal of psychoanalysis
Thirty years ago, we proposed the similarity between the functioning of artificial intelligence and the human psyche, suggesting multiple parallels between the Freudian model proposed in the "Project for Psychology for Neurologists" and the connectio...

A novel deep learning framework for accurate melanoma diagnosis integrating imaging and genomic data for improved patient outcomes.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Melanoma is one of the most malignant forms of skin cancer, with a high mortality rate in the advanced stages. Therefore, early and accurate detection of melanoma plays an important role in improving patients' prognosis. Biopsy is the tra...

3D evaluation model of facial aesthetics based on multi-input 3D convolution neural networks for orthognathic surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Quantitative evaluation of facial aesthetics is an important but also time-consuming procedure in orthognathic surgery, while existing 2D beauty-scoring models are mainly used for entertainment with less clinical impact.