AIMC Topic: Early Diagnosis

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Early Diagnosis of Retinal Blood Vessel Damage via Deep Learning-Powered Collective Intelligence Models.

Computational and mathematical methods in medicine
Early diagnosis of retinal diseases such as diabetic retinopathy has had the attention of many researchers. Deep learning through the introduction of convolutional neural networks has become a prominent solution for image-related tasks such as classi...

Rule extraction from biased random forest and fuzzy support vector machine for early diagnosis of diabetes.

Scientific reports
Due to concealed initial symptoms, many diabetic patients are not diagnosed in time, which delays treatment. Machine learning methods have been applied to increase the diagnosis rate, but most of them are black boxes lacking interpretability. Rule ex...

Deep learning architectures for Parkinson's disease detection by using multi-modal features.

Computers in biology and medicine
BACKGROUND: The use of multi-modal features for improving the diagnosing accuracy of Parkinson's disease (PD) is still under consideration.

Hybrid and Deep Learning Approach for Early Diagnosis of Lower Gastrointestinal Diseases.

Sensors (Basel, Switzerland)
Every year, nearly two million people die as a result of gastrointestinal (GI) disorders. Lower gastrointestinal tract tumors are one of the leading causes of death worldwide. Thus, early detection of the type of tumor is of great importance in the s...

A classification for complex imbalanced data in disease screening and early diagnosis.

Statistics in medicine
Imbalanced classification has drawn considerable attention in the statistics and machine learning literature. Typically, traditional classification methods often perform poorly when a severely skewed class distribution is observed, not to mention und...

Early diagnosis of Alzheimer's disease based on deep learning: A systematic review.

Computers in biology and medicine
BACKGROUND: The improvement of health indicators and life expectancy, especially in developed countries, has led to population growth and increased age-related diseases, including Alzheimer's disease (AD). Thus, the early detection of AD is valuable ...

Early Diagnosis of Acute Ischemic Stroke by Brain Computed Tomography Perfusion Imaging Combined with Head and Neck Computed Tomography Angiography on Deep Learning Algorithm.

Contrast media & molecular imaging
The purpose of the research was to discuss the application values of deep learning algorithm-based computed tomography perfusion (CTP) imaging combined with head and neck computed tomography angiography (CTA) in the diagnosis of ultra-early acute isc...

Prediction models for early diagnosis of actinomycotic osteomyelitis of the jaw using machine learning techniques: a preliminary study.

BMC oral health
BACKGROUND: This study aimed to develop and validate five machine learning models designed to predict actinomycotic osteomyelitis of the jaw. Furthermore, this study determined the relative importance of the predictive variables for actinomycotic ost...

Exploiting exercise electrocardiography to improve early diagnosis of atrial fibrillation with deep learning neural networks.

Computers in biology and medicine
Atrial fibrillation (AF) is the most common type of sustained arrhythmia. It results from abnormal irregularities in the electrical performance of the atria, and may cause heart thrombosis, stroke, arterial disease, thromboembolism, and heart failure...

Artificial intelligence assessment for early detection and prediction of renal impairment using electrocardiography.

International urology and nephrology
PURPOSE: Although renal failure is a major healthcare burden globally and the cornerstone for preventing its irreversible progression is an early diagnosis, an adequate and noninvasive tool to screen renal impairment (RI) reliably and economically do...