AIMC Topic: Neural Networks, Computer

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Graph-Based Disease Prediction in Neuroimaging: Investigating the Impact of Feature Selection.

Advances in experimental medicine and biology
In biomedical machine learning, data often appear in the form of graphs. Biological systems such as protein interactions and ecological or brain networks are instances of applications that benefit from graph representations. Geometric deep learning i...

Spiking Neural Networks and Mathematical Models.

Advances in experimental medicine and biology
Neural networks are applied in various scientific fields such as medicine, engineering, pharmacology, etc. Investigating operations of neural networks refers to estimating the relationship among single neurons and their contributions to the network a...

A Data-Driven Approach to Predicting Tablet Properties after Accelerated Test Using Raw Material Property Database and Machine Learning.

Chemical & pharmaceutical bulletin
The purpose of this study was to develop a model for predicting tablet properties after an accelerated test and to determine whether molecular descriptors affect tablet properties. Tablets were prepared using 81 types of active pharmaceutical ingredi...

Dual-domain fusion deep convolutional neural network for low-dose CT denoising.

Journal of X-ray science and technology
BACKGROUND: In view of the underlying health risks posed by X-ray radiation, the main goal of the present research is to achieve high-quality CT images at the same time as reducing x-ray radiation. In recent years, convolutional neural network (CNN) ...

Deep convolutional neural network based hyperspectral brain tissue classification.

Journal of X-ray science and technology
BACKGROUND: Hyperspectral brain tissue imaging has been recently utilized in medical research aiming to study brain science and obtain various biological phenomena of the different tissue types. However, processing high-dimensional data of hyperspect...

Development of a GCN-based model to predict in vitro phototoxicity from the chemical structure and HOMO-LUMO gap.

The Journal of toxicological sciences
The interaction between sunlight and drugs can lead to phototoxicity in patients who have received such drugs. Phototoxicity assessment is a regulatory requirement globally and one of the main toxicity screening steps in the early stages of drug disc...

Neural networks prediction of the protein-ligand binding affinity with circular fingerprints.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Protein-ligand binding affinity is of significant importance in structure-based drug design. Recently, the development of machine learning techniques has provided an efficient and accurate way to predict binding affinity. However, the pre...

FNSAM: Image super-resolution using a feedback network with self-attention mechanism.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: High-resolution (HR) magnetic resonance imaging (MRI) provides rich pathological information which is of great significance in diagnosis and treatment of brain lesions. However, obtaining HR brain MRI images comes at the cost of extending...

Evaluation of deep learning methods for early gastric cancer detection using gastroscopic images.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: A timely diagnosis of early gastric cancer (EGC) can greatly reduce the death rate of patients. However, the manual detection of EGC is a costly and low-accuracy task. The artificial intelligence (AI) method based on deep learning is cons...

Artificial Intelligence: An Emerging Intellectual Sword for Battling Carcinomas.

Current pharmaceutical biotechnology
Artificial Intelligence (AI) is a branch of computer science that deals with mathematical algorithms to mimic the abilities and intellectual work performed by the human brain. Nowadays, AI is being effectively utilized in addressing difficult healthc...