AIMC Topic: Disease Progression
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Attention-Guided 3D CNN With Lesion Feature Selection for Early Alzheimer's Disease Prediction Using Longitudinal sMRI.
IEEE journal of biomedical and health informatics
Jan 7, 2025
Predicting the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is critical for early intervention. Towards this end, various deep learning models have been applied in this domain, typically relying on structural magnetic ...
Predicting rapid progression in knee osteoarthritis: a novel and interpretable automated machine learning approach, with specific focus on young patients and early disease.
Annals of the rheumatic diseases
Jan 2, 2025
OBJECTIVES: To facilitate the stratification of patients with osteoarthritis (OA) for new treatment development and clinical trial recruitment, we created an automated machine learning (autoML) tool predicting the rapid progression of knee OA over a ...
A deep learning-based ADRPPA algorithm for the prediction of diabetic retinopathy progression.
Scientific reports
Dec 30, 2024
As an alternative to assessments performed by human experts, artificial intelligence (AI) is currently being used for screening fundus images and monitoring diabetic retinopathy (DR). Although AI models can provide quasi-clinician diagnoses, they rar...
Anatomy-centred deep learning improves generalisability and progression prediction in radiographic sacroiliitis detection.
RMD open
Dec 23, 2024
PURPOSE: To examine whether incorporating anatomy-centred deep learning can improve generalisability and enable prediction of disease progression.
Machine Learning Driven by Magnetic Resonance Imaging for the Classification of Alzheimer Disease Progression: Systematic Review and Meta-Analysis.
JMIR aging
Dec 23, 2024
BACKGROUND: To diagnose Alzheimer disease (AD), individuals are classified according to the severity of their cognitive impairment. There are currently no specific causes or conditions for this disease.
CT-based clinical-radiomics model to predict progression and drive clinical applicability in locally advanced head and neck cancer.
European radiology
Dec 20, 2024
BACKGROUND: Definitive chemoradiation is the primary treatment for locally advanced head and neck carcinoma (LAHNSCC). Optimising outcome predictions requires validated biomarkers, since TNM8 and HPV could have limitations. Radiomics may enhance risk...
Explainable machine learning on clinical features to predict and differentiate Alzheimer's progression by sex: Toward a clinician-tailored web interface.
Journal of the neurological sciences
Dec 19, 2024
Alzheimer's disease (AD), the most common neurodegenerative disorder world-wide, presents sex-specific differences in its manifestation and progression, necessitating personalized diagnostic approaches. Current procedures are often costly and invasiv...
Machine learning models predict the progression of long-term renal insufficiency in patients with renal cancer after radical nephrectomy.
BMC nephrology
Dec 18, 2024
BACKGROUND: Chronic Kidney Disease (CKD) is a common severe complication after radical nephrectomy in patients with renal cancer. The timely and accurate prediction of the long-term progression of renal function post-surgery is crucial for early inte...
Machine learning-based selection of immune cell markers in osteosarcoma: prognostic determination and validation of CLK1 in disease progression.
Frontiers in immunology
Dec 17, 2024
INTRODUCTION: Osteosarcoma (OS) is a malignancy of the bone that mainly afflicts younger individuals. Despite existing treatment approaches, patients with metastatic or recurrent disease generally face poor prognoses. A greater understanding of the t...
DNA Copy Number Variations
Protein Serine-Threonine Kinases
Disease Progression
Female
Lymphocytes, Tumor-Infiltrating
Cell Line, Tumor
Humans
Tumor Microenvironment
Osteosarcoma
Gene Expression Regulation, Neoplastic
Machine Learning
Biomarkers, Tumor
Cell Proliferation
Bone Neoplasms
Prognosis
Male
Protein-Tyrosine Kinases
L-MAE: Longitudinal masked auto-encoder with time and severity-aware encoding for diabetic retinopathy progression prediction.
Computers in biology and medicine
Dec 16, 2024
Pre-training strategies based on self-supervised learning (SSL) have demonstrated success as pretext tasks for downstream tasks in computer vision. However, while SSL methods are often domain-agnostic, their direct application to medical imaging is c...
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