AIMC Topic: Neural Networks, Computer

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Evaluation of Neoadjuvant Chemoradiotherapy Response in Rectal Cancer Using MR Images and Deep Learning Neural Networks.

Current medical imaging
INTRODUCTION: The aim of the study was to develop deep-learning neural networks to guide treatment decisions and for the accurate evaluation of tumor response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer using magnetic resonance (MR) imag...

Prostate Segmentation in MRI Images using Transfer Learning based Mask RCNN.

Current medical imaging
INTRODUCTION: The second highest cause of death among males is Prostate Cancer (PCa) in America. Over the globe, it's the usual case in men, and the annual PCa ratio is very surprising. Identical to other prognosis and diagnostic medical systems, dee...

A Dynamic Context Encoder Network for Liver Tumor Segmentation.

Current medical imaging
BACKGROUND: Accurate segmentation of liver tumor regions in medical images is of great significance for clinical diagnosis and the planning of surgical treatments. Recent advancements in machine learning have shown that convolutional neural networks ...

Multi-Modal Sleep Stage Classification With Two-Stream Encoder-Decoder.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sleep staging serves as a fundamental assessment for sleep quality measurement and sleep disorder diagnosis. Although current deep learning approaches have successfully integrated multimodal sleep signals, enhancing the accuracy of automatic sleep st...

Research on prediction and evaluation algorithm of sports athletes performance based on neural network.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: The Ultimate Fighting Championship (UFC) stands as a prominent global platform for professional mixed martial arts, captivating audiences worldwide. With its continuous growth and globalization efforts, UFC events have garnered significan...

Eichner classification based on panoramic X-ray images using deep learning: A pilot study.

Bio-medical materials and engineering
BACKGROUND: Research using panoramic X-ray images using deep learning has been progressing in recent years. There is a need to propose methods that can classify and predict from image information.

FDB-Net: Fusion double branch network combining CNN and transformer for medical image segmentation.

Journal of X-ray science and technology
BACKGROUND: The rapid development of deep learning techniques has greatly improved the performance of medical image segmentation, and medical image segmentation networks based on convolutional neural networks and Transformer have been widely used in ...

Graph Neural Networks with Multi-features for Predicting Cocrystals using APIs and Coformers Interactions.

Current medicinal chemistry
INTRODUCTION: Active pharmaceutical ingredients (APIs) have gained direct pharmaceutical interest, along with their in vitro properties, and thus utilized as auxiliary solid dosage forms upon FDA guidance and approval on pharmaceutical cocrystals whe...

Design and Stability Analysis of an Adaptive Neuro-Fuzzy Inference System (ANFIS)-Based Pacemaker Controller in MATLAB Simulink.

Journal of long-term effects of medical implants
We present the design and stability analysis of an adaptive neuro-fuzzy inference system (ANFIS)-based controller of a pacemaker in MATLAB Simulink. ANFIS uses learning and speed properties of fuzzy and neural networks. Based on body states and prepr...

Connectome-based schizophrenia prediction using structural connectivity - Deep Graph Neural Network(sc-DGNN).

Journal of X-ray science and technology
BACKGROUND: Connectome is understanding the complex organization of the human brain's structural and functional connectivity is essential for gaining insights into cognitive processes and disorders.