AIMC Topic: Early Diagnosis

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Artificial Intelligence in Eye Movements Analysis for Alzheimer's Disease Early Diagnosis.

Current Alzheimer research
As the world's population ages, Alzheimer's disease is currently the seventh most common cause of death globally; the burden is anticipated to increase, especially among middle-class and elderly persons. Artificial intelligence-based algorithms that ...

Unveiling New Strategies Facilitating the Implementation of Artificial Intelligence in Neuroimaging for the Early Detection of Alzheimer's Disease.

Journal of Alzheimer's disease : JAD
Alzheimer's disease (AD) is a chronic neurodegenerative disorder with a global impact. The past few decades have witnessed significant strides in comprehending the underlying pathophysiological mechanisms and developing diagnostic methodologies for A...

Neural Computation-Based Methods for the Early Diagnosis and Prognosis of Alzheimer's Disease Not Using Neuroimaging Biomarkers: A Systematic Review.

Journal of Alzheimer's disease : JAD
BACKGROUND: The growing number of older adults in recent decades has led to more prevalent geriatric diseases, such as strokes and dementia. Therefore, Alzheimer's disease (AD), as the most common type of dementia, has become more frequent too.

[Research progress of artificial intelligence technology in early diagnosis of sepsis].

Zhonghua wei zhong bing ji jiu yi xue
Sepsis is caused by infection, which can ultimately lead to multiple organ dysfunction and even life-threatening. Early recognition and early treatment can significantly improve the prognosis of sepsis patients. However, the effect of using a single ...

Hybrid CNN-LSTM for Predicting Diabetes: A Review.

Current diabetes reviews
BACKGROUND: Diabetes is a common and deadly chronic disease caused by high blood glucose levels that can cause heart problems, neurological damage, and other illnesses. Through the early detection of diabetes, patients can live healthier lives. Many ...

An Early Detection and Classification of Alzheimer's Disease Framework Based on ResNet-50.

Current medical imaging
OBJECTIVE: The objective of this study is to develop a more effective early detection system for Alzheimer's disease (AD) using a Deep Residual Network (ResNet) model by addressing the issue of convolutional layers in conventional Convolutional Neura...

Neuronetwork Approach in the Early Diagnosis of Depression.

Psychiatria Danubina
BACKGROUND: Depression is a common mental illness, with around 280 million people suffering from depression worldwide. At present, the main way to quantify the severity of depression is through psychometric scales, which entail subjectivity on the pa...

Using Artificial Intelligence for the Early Detection of Micro-Progression of Pressure Injuries in Hospitalized Patients: A Preliminary Nursing Perspective Evaluation.

Studies in health technology and informatics
This study established a predictive model for the early detection of micro-progression of pressure injuries (PIs) from the perspective of nurses. An easy and programing-free artificial intelligence modeling tool with professional evaluation capabilit...

Developing a Data Driven Approach for Early Detection of SIRS in Pediatric Intensive Care Using Automatically Labeled Training Data.

Studies in health technology and informatics
Critical care can benefit from analyzing data by machine learning approaches for supporting clinical routine and guiding clinical decision-making. Developing data-driven approaches for an early detection of systemic inflammatory response syndrome (SI...

Single-Examination Risk Prediction of Severe Retinopathy of Prematurity.

Pediatrics
BACKGROUND AND OBJECTIVES: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness. Screening and treatment reduces this risk, but requires multiple examinations of infants, most of whom will not develop severe disease. Previous wo...