AIMC Topic: Neural Networks, Computer

Clear Filters Showing 28111 to 28120 of 31376 articles

Deep Learning-based Automated Knee Joint Localization in Radiographic Images Using Faster R-CNN.

Current medical imaging
BACKGROUND: Osteoarthritis is a condition that poses a risk to the knee joint, resulting in pain and impaired function. However, traditional knee X-ray evaluations using the Kellgren-Lawrence grading system have proven to be inefficient. These evalua...

Hybrid CNN-LSTM for Predicting Diabetes: A Review.

Current diabetes reviews
BACKGROUND: Diabetes is a common and deadly chronic disease caused by high blood glucose levels that can cause heart problems, neurological damage, and other illnesses. Through the early detection of diabetes, patients can live healthier lives. Many ...

Application of artificial intelligence for the classification of the clinical outcome and therapy in patients with viral infections: The case of COVID-19.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: With the end of the coronavirus disease 2019 (COVID-19) pandemic, it becomes intriguing to observe the impact of innovative digital technologies on the diagnosis and management of diseases, in order to improve clinical outcomes for patien...

Deep Learning for Predicting Gene Regulatory Networks: A Step-by-Step Protocol in R.

Methods in molecular biology (Clifton, N.J.)
Deep learning has emerged as a powerful tool for solving complex problems, including reconstruction of gene regulatory networks within the realm of biology. These networks consist of transcription factors and their associations with genes they regula...

Artificial Intelligence in ADME Property Prediction.

Methods in molecular biology (Clifton, N.J.)
Absorption, distribution, metabolism, excretion (ADME) are key properties of a small molecule that govern pharmacokinetic profiles and impact its efficacy and safety. Computational methods such as machine learning and artificial intelligence have gai...

Implementation and Efficient Analysis of Preprocessing Techniques in Deep Learning for Image Classification.

Current medical imaging
BACKGROUND: Deep learning models have recently been preferred to perform certain image-processing tasks. Recently, with the increasing radiation, heat, and poor lighting conditions, the raw image samples may contain noisy and ambiguous information.

An Early Detection and Classification of Alzheimer's Disease Framework Based on ResNet-50.

Current medical imaging
OBJECTIVE: The objective of this study is to develop a more effective early detection system for Alzheimer's disease (AD) using a Deep Residual Network (ResNet) model by addressing the issue of convolutional layers in conventional Convolutional Neura...

Graph-DTI: A New Model for Drug-target Interaction Prediction Based on Heterogenous Network Graph Embedding.

Current computer-aided drug design
BACKGROUND: In this study, we aimed to develop a new end-to-end learning model called Graph-Drug-Target Interaction (DTI), which integrates various types of information in the heterogeneous network data, and to explore automatic learning of the topol...

Learning technology for detection and grading of cancer tissue using tumour ultrasound images1.

Journal of X-ray science and technology
BACKGROUND: Early diagnosis of breast cancer is crucial to perform effective therapy. Many medical imaging modalities including MRI, CT, and ultrasound are used to diagnose cancer.

Predicting Antitumor Activity of Anthrapyrazole Derivatives using Advanced Machine Learning Techniques.

Current computer-aided drug design
BACKGROUND: Anthrapyrazoles are a new class of antitumor agents and successors to anthracyclines possessing a broad range of antitumor activity in various model tumors.