AIMC Topic: Early Diagnosis

Clear Filters Showing 211 to 220 of 522 articles

Understanding the Pathophysiology of Mental Diseases and Early Diagnosis Thanks to Electrophysiological Tools: Some Insights and Empirical Facts.

Clinical EEG and neuroscience
. Neurophysiological tools remain indispensable instruments in the assessment of psychiatric disorders. These techniques are widely available, inexpensive and well tolerated, providing access to the assessment of brain functional alterations. In the ...

Artificial intelligence model for early detection of diabetes.

Biomedica : revista del Instituto Nacional de Salud
Introduction. Diabetes is a chronic disease characterized by a high blood glucose level. It can lead to complications that affect the quality of life and increase the costs of healthcare. In recent years, prevalence and mortality rates have increased...

A Deep Learning-Based Ensemble Method for Early Diagnosis of Alzheimer's Disease using MRI Images.

Neuroinformatics
Recently, the early diagnosis of Alzheimer's disease has gained major attention due to the growing prevalence of the disease and the resulting costs imposed on individuals and society. The main objective of this study was to propose an ensemble metho...

Artificial intelligence in early detection and prediction of pediatric/neonatal acute kidney injury: current status and future directions.

Pediatric nephrology (Berlin, Germany)
Acute kidney injury (AKI) has a significant impact on the short-term and long-term clinical outcomes of pediatric and neonatal patients, and it is imperative in these populations to mitigate the pathways leading to AKI and be prepared for early diagn...

Early Detection of Optic Nerve Changes on Optical Coherence Tomography Using Deep Learning for Risk-Stratification of Papilledema and Glaucoma.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society
BACKGROUND: The use of artificial intelligence is becoming more prevalence in medicine with numerous successful examples in ophthalmology. However, much of the work has been focused on replicating the works of ophthalmologists. Given the analytical p...

A Snapshot-Stacked Ensemble and Optimization Approach for Vehicle Breakdown Prediction.

Sensors (Basel, Switzerland)
Predicting breakdowns is becoming one of the main goals for vehicle manufacturers so as to better allocate resources, and to reduce costs and safety issues. At the core of the utilization of vehicle sensors is the fact that early detection of anomali...

A diabetes prediction model based on Boruta feature selection and ensemble learning.

BMC bioinformatics
BACKGROUND AND OBJECTIVE: As a common chronic disease, diabetes is called the "second killer" among modern diseases. Currently, there is no medical cure for diabetes. We can only rely on medication for auxiliary treatment. However, many diabetic pati...

Recent Research Progress of Surface-Enhanced Raman Scattering Dominated Analysis Strategies in Early Diagnosis of Diseases.

Chemistry, an Asian journal
Timely and powerful diagnostic means can achieve better therapeutic effects, reduce disease torment, and improve survival rate. As a powerful non-invasive spectroscopy technology, surface-enhanced Raman scattering (SERS) have testified to be a great ...

Imaging of early-stage osteoarthritis: the needs and challenges for diagnosis and classification.

Skeletal radiology
In an effort to boost the development of new management strategies for OA, there is currently a shift in focus towards the diagnosis and treatment of early-stage OA. It is important to distinguish diagnosis from classification of early-stage OA. Diag...

Revolutionizing the Early Detection of Alzheimer's Disease through Non-Invasive Biomarkers: The Role of Artificial Intelligence and Deep Learning.

Sensors (Basel, Switzerland)
Alzheimer's disease (AD) is now classified as a silent pandemic due to concerning current statistics and future predictions. Despite this, no effective treatment or accurate diagnosis currently exists. The negative impacts of invasive techniques and ...