AI Medical Compendium Topic:
Diagnosis, Computer-Assisted

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Real-time Inference and Detection of Disruptive EEG Networks for Epileptic Seizures.

Scientific reports
Recent studies in brain science and neurological medicine paid a particular attention to develop machine learning-based techniques for the detection and prediction of epileptic seizures with electroencephalogram (EEG). As a noninvasive monitoring met...

Development of a machine learning-based multimode diagnosis system for lung cancer.

Aging
As an emerging technology, artificial intelligence has been applied to identify various physical disorders. Here, we developed a three-layer diagnosis system for lung cancer, in which three machine learning approaches including decision tree C5.0, ar...

Using X-ray images and deep learning for automated detection of coronavirus disease.

Journal of biomolecular structure & dynamics
Coronavirus is still the leading cause of death worldwide. There are a set number of COVID-19 test units accessible in emergency clinics because of the expanding cases daily. Therefore, it is important to implement an automatic detection and classifi...

Combining gene expression profiling and machine learning to diagnose B-cell non-Hodgkin lymphoma.

Blood cancer journal
Non-Hodgkin B-cell lymphomas (B-NHLs) are a highly heterogeneous group of mature B-cell malignancies. Their classification thus requires skillful evaluation by expert hematopathologists, but the risk of error remains higher in these tumors than in ma...

SS-SWT and SI-CNN: An Atrial Fibrillation Detection Framework for Time-Frequency ECG Signal.

Journal of healthcare engineering
Atrial fibrillation is the most common arrhythmia and is associated with high morbidity and mortality from stroke, heart failure, myocardial infarction, and cerebral thrombosis. Effective and rapid detection of atrial fibrillation is critical to redu...

A computer-aided diagnosis system for brain magnetic resonance imaging images using a novel differential feature neural network.

Computers in biology and medicine
To improve the performance of brain tumor diagnosis, numerous automatic brain tumor diagnosis systems that use machine learning technologies have been proposed. However, most current systems ignore the structural symmetry of brain magnetic resonance ...

Automatic Grading System for Diabetic Retinopathy Diagnosis Using Deep Learning Artificial Intelligence Software.

Current eye research
: To describe the development and validation of an artificial intelligence-based, deep learning algorithm (DeepDR) for the detection of diabetic retinopathy (DR) in retinal fundus photographs. : Five hundred fundus images, which had detailed labellin...

Novel artificial intelligence system increases the detection of prostate cancer in whole slide images of core needle biopsies.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Prostate cancer (PrCa) is the second most common cancer among men in the United States. The gold standard for detecting PrCa is the examination of prostate needle core biopsies. Diagnosis can be challenging, especially for small, well-differentiated ...

Cross-Subject Seizure Detection in EEGs Using Deep Transfer Learning.

Computational and mathematical methods in medicine
Electroencephalography (EEG) plays an import role in monitoring the brain activities of patients with epilepsy and has been extensively used to diagnose epilepsy. Clinically reading tens or even hundreds of hours of EEG recordings is very time consum...

Endoscopic three-categorical diagnosis of Helicobacter pylori infection using linked color imaging and deep learning: a single-center prospective study (with video).

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Helicobacter pylori (H. pylori) eradication is required to reduce incidence related to gastric cancer. Recently, it was found that even after the successful eradication of H. pylori, an increased, i.e., moderate, risk of gastric cancer pe...