AI Medical Compendium Journal:
Combinatorial chemistry & high throughput screening

Showing 21 to 30 of 68 articles

Predicting Drug-Target Affinity Based on Recurrent Neural Networks and Graph Convolutional Neural Networks.

Combinatorial chemistry & high throughput screening
BACKGROUND: Drug development requires a lot of money and time, and the outcome of the challenge is unknown. So, there is an urgent need for researchers to find a new approach that can reduce costs. Therefore, the identification of drug-target interac...

On m-polar Diophantine Fuzzy N-soft Set with Applications.

Combinatorial chemistry & high throughput screening
INTRODUCTION: In this paper, we present a novel hybrid model m-polar Diophantine fuzzy N-soft set and define its operations.

Privacy-preserving Collaborative Training for Medical Image Analysis Based on Multi-Blockchain.

Combinatorial chemistry & high throughput screening
BACKGROUND: As artificial intelligence and big data analysis develop rapidly, data privacy, especially patient medical data privacy, is getting more and more attention.

Diagnosis of Alzheimer's Disease Based on Deeply-Fused Nets.

Combinatorial chemistry & high throughput screening
AIM AND OBJECTIVE: Fast and accurate diagnosis of Alzheimer's disease is very important for the care and further treatment of patients. Along with the development of deep learning, impressive progress has also been made in the automatic diagnosis of ...

An E-nose and Convolution Neural Network based Recognition Method for Processed Products of Crataegi Fructus.

Combinatorial chemistry & high throughput screening
BACKGROUND: The manual identification of Fructus Crataegi processed products is inefficient and unreliable. Therefore, efficient identification of the Fructus Crataegis' processed products is important.

Lung Nodule Detection using Convolutional Neural Networks with Transfer Learning on CT Images.

Combinatorial chemistry & high throughput screening
AIM AND OBJECTIVE: Lung nodule detection is critical in improving the five-year survival rate and reducing mortality for patients with lung cancer. Numerous methods based on Convolutional Neural Networks (CNNs) have been proposed for lung nodule dete...

Identification of 2'-O-methylation Site by Investigating Multi-feature Extracting Techniques.

Combinatorial chemistry & high throughput screening
BACKGROUND: RNA methylation is a reversible post-transcriptional modification involving numerous biological processes. Ribose 2'-O-methylation is part of RNA methylation. It has shown that ribose 2'-O-methylation plays an important role in immune rec...

Recognizing Proteins with Binding Function in Elymus nutans Based on Machine Learning Methods.

Combinatorial chemistry & high throughput screening
BACKGROUND: We research the binding function proteins in Elymus nutans. Recognition for proteins is essential for study of biology. Machine learning methods have been widely used for the prediction of proteins.