AIMC Topic: Diagnosis, Computer-Assisted

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A Parkinson's Auxiliary Diagnosis Algorithm Based on a Hyperparameter Optimization Method of Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Parkinson's disease is a common mental disease in the world, especially in the middle-aged and elderly groups. Today, clinical diagnosis is the main diagnostic method of Parkinson's disease, but the diagnosis results are not ideal, especially in the ...

Deep learning-based computer-aided detection of ultrasound in breast cancer diagnosis: A systematic review and meta-analysis.

Clinical radiology
PURPOSE: The aim of this meta-analysis was to assess the diagnostic performance of deep learning (DL) and ultrasound in breast cancer diagnosis. Additionally, we categorized the included studies into two subgroups: B-mode ultrasound diagnostic subgro...

Graph Embedded Ensemble Deep Randomized Network for Diagnosis of Alzheimer's Disease.

IEEE/ACM transactions on computational biology and bioinformatics
Randomized shallow/deep neural networks with closed form solution avoid the shortcomings that exist in the back propagation (BP) based trained neural networks. Ensemble deep random vector functional link (edRVFL) network utilize the strength of two g...

Federated Learning Empowered Real-Time Medical Data Processing Method for Smart Healthcare.

IEEE/ACM transactions on computational biology and bioinformatics
Computer-aided diagnosis (CAD) has always been an important research topic for applying artificial intelligence in smart healthcare. Sufficient medical data are one of the most critical factors in CAD research. However, medical data are usually obtai...

Ensemble Deep Random Vector Functional Link Network Using Privileged Information for Alzheimer's Disease Diagnosis.

IEEE/ACM transactions on computational biology and bioinformatics
Alzheimer's disease (AD) is a progressive brain disorder. Machine learning models have been proposed for the diagnosis of AD at early stage. Recently, deep learning architectures have received quite a lot attention. Most of the deep learning architec...

Application of artificial intelligence in cancer diagnosis and tumor nanomedicine.

Nanoscale
Cancer is a major health concern due to its high incidence and mortality rates. Advances in cancer research, particularly in artificial intelligence (AI) and deep learning, have shown significant progress. The swift evolution of AI in healthcare, esp...

Rationale and design of the artificial intelligence scalable solution for acute myocardial infarction (ASSIST) study.

Journal of electrocardiology
BACKGROUND: Acute coronary syndrome (ACS), specifically ST-segment elevation myocardial infarction is a major cause of morbidity and mortality throughout Europe. Diagnosis in the acute setting is mainly based on clinical symptoms and physician's inte...

Linked Color Imaging with Artificial Intelligence Improves the Detection of Early Gastric Cancer.

Digestive diseases (Basel, Switzerland)
INTRODUCTION: Esophagogastroduodenoscopy is the most important tool to detect gastric cancer (GC). In this study, we developed a computer-aided detection (CADe) system to detect GC with white light imaging (WLI) and linked color imaging (LCI) modes a...

A novel graph neural network method for Alzheimer's disease classification.

Computers in biology and medicine
Alzheimer's disease (AD) is a chronic neurodegenerative disease. Early diagnosis are very important to timely treatment and delay the progression of the disease. In the past decade, many computer-aided diagnostic (CAD) algorithms have been proposed f...

A novel universal deep learning approach for accurate detection of epilepsy.

Medical engineering & physics
Epilepsy claims the lives of many people, so researchers strive to build highly accurate diagnostic models. One of the limitations of obtaining high accuracy is the scarcity of Electroencephalography (EEG) data and the fact that they are from differe...