AIMC Topic: Disease Progression
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Monitoring multiple sclerosis: digital and fluid phase biomarkers.
Current opinion in neurology
Mar 28, 2025
PURPOSE OF REVIEW: Monitoring of disease activity and treatment response in multiple sclerosis (MS) currently relies on the integration of qualitative clinical and radiological data that is of limited predictive value. An array of quantitative digita...
Machine Learning Identification of Patient Phenoclusters in Aortic Regurgitation.
JACC. Cardiovascular imaging
Mar 26, 2025
BACKGROUND: Current treatment paradigms assume aortic regurgitation (AR) patients to be a homogenous population, but varied courses of disease progression and outcomes are observed clinically.
Decision Support Techniques
Phenotype
Prognosis
Retrospective Studies
Female
Reproducibility of Results
Risk Factors
Aged
Humans
Machine Learning
United States
Aortic Valve
Unsupervised Machine Learning
Risk Assessment
Predictive Value of Tests
Disease Progression
Adult
Severity of Illness Index
Sex Factors
Male
Time Factors
Aortic Valve Insufficiency
Ventricular Function, Left
Magnetic Resonance Imaging, Cine
Middle Aged
Predicting rheumatoid arthritis progression from seronegative undifferentiated arthritis using machine learning: a deep learning model trained on the KURAMA cohort and externally validated with the ANSWER cohort.
Arthritis research & therapy
Mar 26, 2025
BACKGROUND: Undifferentiated arthritis (UA) often develops into rheumatoid arthritis (RA), but predicting disease progression from seronegative UA remains challenging because seronegative RA often does not meet the classification criteria. This study...
Nutritional predictors of lymphatic filariasis progression: Insights from a machine learning approach.
PloS one
Mar 26, 2025
Lymphatic filariasis (LF) is a mosquito-borne neglected tropical disease that causes disfiguring of the affected extremities, often leading to permanent disability and stigma. Described as a disease of poverty, the impact of socioeconomic indicators ...
Neuropsychological tests and machine learning: identifying predictors of MCI and dementia progression.
Aging clinical and experimental research
Mar 12, 2025
BACKGROUND: Early prediction of progression in dementia is of major importance for providing patients with adequate clinical care, with considerable impact on the organization of the whole healthcare system.
Unsupervised machine learning identifies biomarkers of disease progression in post-kala-azar dermal leishmaniasis in Sudan.
PLoS neglected tropical diseases
Mar 11, 2025
BACKGROUND: Post-kala-azar dermal leishmaniasis (PKDL) appears as a rash in some individuals who have recovered from visceral leishmaniasis caused by Leishmania donovani. Today, basic knowledge of this neglected disease and how to predict its progres...
Machine Learning Models Integrating Dietary Indicators Improve the Prediction of Progression from Prediabetes to Type 2 Diabetes Mellitus.
Nutrients
Mar 8, 2025
: Diet plays an important role in preventing and managing the progression from prediabetes to type 2 diabetes mellitus (T2DM). This study aims to develop prediction models incorporating specific dietary indicators and explore the performance in T2DM ...
A comprehensive approach to anticipating the progression of mild cognitive impairment.
Brain research
Mar 6, 2025
The immersive experience provided by our approach empowers researchers with an intuitive exploration of brain structures. Within the brain's central nervous system, encompassing both white and gray matter, symptoms associated with Alzheimer's disease...
GDF15, EGF, and Neopterin in Assessing Progression of Pediatric Chronic Kidney Disease Using Artificial Intelligence Tools-A Pilot Study.
International journal of molecular sciences
Mar 6, 2025
Cell-mediated immunity and chronic inflammation are hallmarks of chronic kidney disease (CKD). Growth differentiation factor 15 (GDF15) is a marker of inflammation and an integrative signal in stress conditions. Epidermal growth factor (EGF) is a tub...
Using machine learning to predict deterioration of symptoms in COPD patients within a telemonitoring program.
Scientific reports
Feb 27, 2025
COPD exacerbations have a profound clinical impact on patients. Accurately predicting these events could help healthcare professionals take proactive measures to mitigate their impact. For over a decade, telEPOC, a telehealthcare program, has collect...
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