AIMC Topic: Humans

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Identifying ADHD-Related Abnormal Functional Connectivity with a Graph Convolutional Neural Network.

Neural plasticity
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that is characterized by inattention, hyperactivity, and impulsivity. The neural mechanisms underlying ADHD remain inadequately understood, and current approaches...

Analysis of Bladder Cancer Staging Prediction Using Deep Residual Neural Network, Radiomics, and RNA-Seq from High-Definition CT Images.

Genetics research
Bladder cancer has recently seen an alarming increase in global diagnoses, ascending as a predominant cause of cancer-related mortalities. Given this pressing scenario, there is a burgeoning need to identify effective biomarkers for both the diagnosi...

Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study.

American journal of otolaryngology
OBJECTIVE: To develop a multi-instance learning (MIL) based artificial intelligence (AI)-assisted diagnosis models by using laryngoscopic images to differentiate benign and malignant vocal fold leukoplakia (VFL).

A simple and effective convolutional operator for node classification without features by graph convolutional networks.

PloS one
Graph neural networks (GNNs), with their ability to incorporate node features into graph learning, have achieved impressive performance in many graph analysis tasks. However, current GNNs including the popular graph convolutional network (GCN) cannot...

Deep multiple instance learning versus conventional deep single instance learning for interpretable oral cancer detection.

PloS one
The current medical standard for setting an oral cancer (OC) diagnosis is histological examination of a tissue sample taken from the oral cavity. This process is time-consuming and more invasive than an alternative approach of acquiring a brush sampl...

Radiation dose estimation with multiple artificial neural networks in dicentric chromosome assay.

International journal of radiation biology
PURPOSE: The dicentric chromosome assay (DCA), often referred to as the 'gold standard' in radiation dose estimation, exhibits significant challenges as a consequence of its labor-intensive nature and dependency on expert knowledge. Existing automate...

Automatic Vehicle Fueling System using PLC Controlled Robotic Arm - A Simulation Design.

F1000Research
The objective of this research is to simulate an automatic fuelling system using a PLC LogixPro simulation. The system includes the "FASS" concept, which is Fast, Accurate, Safe and Simple, to allow car users to have an efficient fuel filling system....

Integrating Machine Learning in Metabolomics: A Path to Enhanced Diagnostics and Data Interpretation.

Small methods
Metabolomics, leveraging techniques like NMR and MS, is crucial for understanding biochemical processes in pathophysiological states. This field, however, faces challenges in metabolite sensitivity, data complexity, and omics data integration. Recent...