AIMC Topic: Disease Progression
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A Transcriptomics-Based Machine Learning Model Discriminating Mild Cognitive Impairment and the Prediction of Conversion to Alzheimer's Disease.
Cells
Nov 19, 2024
The clinical spectrum of Alzheimer's disease (AD) ranges dynamically from asymptomatic and mild cognitive impairment (MCI) to mild, moderate, or severe AD. Although a few disease-modifying treatments, such as lecanemab and donanemab, have been develo...
DAPNet: multi-view graph contrastive network incorporating disease clinical and molecular associations for disease progression prediction.
BMC medical informatics and decision making
Nov 19, 2024
BACKGROUND: Timely and accurate prediction of disease progress is crucial for facilitating early intervention and treatment for various chronic diseases. However, due to the complicated and longitudinal nature of disease progression, the capacity and...
Artificial intelligence in assessing progression of age-related macular degeneration.
Eye (London, England)
Nov 18, 2024
The human population is steadily growing with increased life expectancy, impacting the prevalence of age-dependent diseases, including age-related macular degeneration (AMD). Health care systems are confronted with an increasing burden with rising pa...
Predicting Asthma Exacerbations Using Machine Learning Models.
Advances in therapy
Nov 18, 2024
INTRODUCTION: Although clinical, functional, and biomarker data predict asthma exacerbations, newer approaches providing high accuracy of prognosis are needed for real-world decision-making in asthma. Machine learning (ML) leverages mathematical and ...
Machine-learning methodologies to predict disease progression in chronic hepatitis B in Africa.
Hepatology communications
Nov 15, 2024
BACKGROUND: Little is known about the determinants of disease progression among African patients with chronic HBV infection.
A machine learning model for predicting worsening renal function using one-year time series data in patients with type 2 diabetes.
Journal of diabetes investigation
Nov 13, 2024
BACKGROUND AND AIMS: To prevent end-stage renal disease caused by diabetic kidney disease, we created a predictive model for high-risk patients using machine learning.
Unveiling the utility of artificial intelligence for prediction, diagnosis, and progression of diabetic kidney disease: an evidence-based systematic review and meta-analysis.
Current medical research and opinion
Nov 13, 2024
OBJECTIVE: The purpose of this study was to conduct a systematic investigation of the potential of artificial intelligence (AI) models in the prediction, detection of diagnostic biomarkers, and progression of diabetic kidney disease (DKD). In additio...
Predicting paediatric asthma exacerbations with machine learning: a systematic review with meta-analysis.
European respiratory review : an official journal of the European Respiratory Society
Nov 13, 2024
BACKGROUND: Asthma exacerbations in children pose a significant burden on healthcare systems and families. While traditional risk assessment tools exist, artificial intelligence (AI) offers the potential for enhanced prediction models.
Predicting craniofacial fibrous dysplasia growth status: an exploratory study of a hybrid radiomics and deep learning model based on computed tomography images.
Oral surgery, oral medicine, oral pathology and oral radiology
Nov 12, 2024
OBJECTIVE: This study aimed to develop 3 models based on computed tomography (CT) images of patients with craniofacial fibrous dysplasia (CFD): a radiomics model (Model Rad), a deep learning (DL) model (Model DL), and a hybrid radiomics and DL model ...
A Novel Management Challenge in Age-Related Macular Degeneration: Artificial Intelligence and Expert Prediction of Geographic Atrophy.
Ophthalmology. Retina
Nov 9, 2024
PURPOSE: The progression of geographic atrophy (GA) secondary to age-related macular degeneration is highly variable among individuals. Prediction of the progression is critical to identify patients who will benefit most from the first treatments cur...
Fundus Oculi
Macular Degeneration
Disease Management
Fluorescein Angiography
Follow-Up Studies
Visual Acuity
Tomography, Optical Coherence
Geographic Atrophy
Humans
Prospective Studies
Male
Artificial Intelligence
Female
Middle Aged
Algorithms
Aged
Disease Progression
Aged, 80 and over
Deep Learning
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