AIMC Topic: Disease Progression
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Machine Learning-Based Perivascular Space Volumetry in Alzheimer Disease.
Investigative radiology
Apr 23, 2024
OBJECTIVES: Impaired perivascular clearance has been suggested as a contributing factor to the pathogenesis of Alzheimer disease (AD). However, it remains unresolved when the anatomy of the perivascular space (PVS) is altered during AD progression. T...
Gait Alterations and Association With Worsening Knee Pain and Physical Function: A Machine Learning Approach With Wearable Sensors in the Multicenter Osteoarthritis Study.
Arthritis care & research
Apr 17, 2024
OBJECTIVE: The objective of this study was to identify gait alterations related to worsening knee pain and worsening physical function, using machine learning approaches applied to wearable sensor-derived data from a large observational cohort.
Deep Learning for Predicting Progression of Patellofemoral Osteoarthritis Based on Lateral Knee Radiographs, Demographic Data, and Symptomatic Assessments.
Methods of information in medicine
Apr 11, 2024
OBJECTIVE: In this study, we propose a novel framework that utilizes deep learning and attention mechanisms to predict the radiographic progression of patellofemoral osteoarthritis (PFOA) over a period of 7 years.
Predicting the conversion from clinically isolated syndrome to multiple sclerosis: An explainable machine learning approach.
Multiple sclerosis and related disorders
Apr 9, 2024
INTRODUCTION: Predicting the conversion of clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS) is critical to personalizing treatment planning and benefits for patients. The aim of this study is to develop an explainab...
A commentary on 'The use of multilayer perceptron and radial basis function: an artificial intelligence model to predict progression of oral cancer': correspondence.
International journal of surgery (London, England)
Apr 1, 2024
Towards the adoption of quantitative computed tomography in the management of interstitial lung disease.
European respiratory review : an official journal of the European Respiratory Society
Mar 27, 2024
The shortcomings of qualitative visual assessment have led to the development of computer-based tools to characterise and quantify disease on high-resolution computed tomography (HRCT) in patients with interstitial lung diseases (ILDs). Quantitative ...
Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer's disease in patients with mild cognitive symptoms.
Alzheimer's research & therapy
Mar 19, 2024
BACKGROUND: Predicting future Alzheimer's disease (AD)-related cognitive decline among individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) is an important task for healthcare. Structural brain imaging as measured by...
Predicting the onset of end-stage knee osteoarthritis over two- and five-years using machine learning.
Seminars in arthritis and rheumatism
Mar 16, 2024
OBJECTIVE: Identifying participants who will progress to advanced stage in knee osteoarthritis (KOA) trials remains a significant challenge. Current tools, relying on total knee replacements (TKR), fall short in reliability due to the extraneous fact...
Deep learning algorithms for predicting renal replacement therapy initiation in CKD patients: a retrospective cohort study.
BMC nephrology
Mar 14, 2024
BACKGROUND: Chronic kidney disease (CKD) requires accurate prediction of renal replacement therapy (RRT) initiation risk. This study developed deep learning algorithms (DLAs) to predict RRT risk in CKD patients by incorporating medical history and pr...
Automatic hip osteoarthritis grading with uncertainty estimation from computed tomography using digitally-reconstructed radiographs.
International journal of computer assisted radiology and surgery
Mar 12, 2024
PURPOSE: Progression of hip osteoarthritis (hip OA) leads to pain and disability, likely leading to surgical treatment such as hip arthroplasty at the terminal stage. The severity of hip OA is often classified using the Crowe and Kellgren-Lawrence (K...
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