AIMC Topic: Disease Progression

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Cross-modal fusion of brain imaging and clinical data for Parkinson's disease progression prediction.

PloS one
BACKGROUND: Machine learning shows great potential in science but struggles with complex, high-dimensional multi-omics data. PD progression is long, diagnosed mainly by clinical signs. This paper proposes a novel decision fusion method to improve the...

Subtyping schizophrenia via machine learning by using structural neuroimaging.

Translational psychiatry
Schizophrenia is a heterogeneous disorder with diverse clinical presentations and neuroanatomical alterations. Despite recent advances, we still lack a working hypothesis for the pathophysiology of schizophrenia. One reason might be the heterogeneous...

The application of artificial intelligence-based algorithms in predicting the progression of keratoconus: a systematic review.

International ophthalmology
PURPOSE: To conduct a systematic review of studies examining the use of artificial intelligence (AI) algorithms in predicting the progression of keratoconus (KCN).

Assessing the accuracy of survival machine learning and traditional statistical models for Alzheimer's disease prediction over time: a study on the ADNI cohort.

BMC medical research methodology
BACKGROUND: Mild cognitive impairment (MCI) represents a transitional stage to Alzheimer's disease (AD), making progression prediction crucial for timely intervention. Predictive models integrating clinical, laboratory, and survival data can enhance ...

Deep learning algorithm for predicting rapid progression of abdominal aortic aneurysm by integrating CT images and clinical features.

Scientific reports
Abdominal aortic aneurysm (AAA) progression carries a significant rupture risk, demanding accurate prediction models beyond traditional methods that rely on limited clinical parameters and often overlook complex factor interplay. We aimed to enhance ...

Artificial intelligence-driven diagnosis for age-related macular degeneration bridging pathology and engineering: a survey.

International ophthalmology
Age-related macular degeneration (AMD) is the primary reason for severe visual impairments, making early diagnosis critically important. This paper provides a comprehensive review of the methods used to support screening and diagnostic decisions, foc...

An MRI-based radiomics framework for early identification and progression stratification in knee osteoarthritis: data from the osteoarthritis initiative.

BMC musculoskeletal disorders
OBJECTIVES: To develop a cascaded machine learning model based on MRI radiomics features from cartilage and subchondral bone to predict the incidence and progression of knee osteoarthritis (KOA), thereby addressing the need for early intervention in ...

Multi-omics and machine learning identify FN1 and ALDH2 as diagnostic biomarkers and therapeutic targets in early and late diabetic kidney disease.

Renal failure
Diabetic kidney disease (DKD), the leading cause of end-stage kidney disease worldwide, demands deeper molecular characterization to improve clinical management. This study employed an integrated multi-omics approach to identify stage-specific biomar...

The prognostic value of POD24 for multiple myeloma: a comprehensive analysis based on traditional statistics and machine learning.

BMC cancer
BACKGROUND: In multiple myeloma, progression within 24 months (POD24) is a strong adverse prognostic factor. However, its impact on overall survival (OS) remains underexplored through machine learning.