AIMC Topic: Disease Progression
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Letter to the Editor Regarding "Prediction of Progressive Collapse in Osteoporotic Vertebral Fractures Using Conventional Statistics and Machine Learning".
Spine
Oct 31, 2023
Multi-Level Ethical Considerations of Artificial Intelligence Health Monitoring for People Living with Parkinson's Disease.
AJOB empirical bioethics
Oct 27, 2023
Artificial intelligence (AI) has garnered tremendous attention in health care, and many hope that AI can enhance our health system's ability to care for people with chronic and degenerative conditions, including Parkinson's Disease (PD). This paper r...
Predicting of diabetic retinopathy development stages of fundus images using deep learning based on combined features.
PloS one
Oct 20, 2023
The number of diabetic retinopathy (DR) patients is increasing every year, and this causes a public health problem. Therefore, regular diagnosis of diabetes patients is necessary to avoid the progression of DR stages to advanced stages that lead to b...
Distinct subtypes of spatial brain metabolism patterns in Alzheimer's disease identified by deep learning-based FDG PET clusters.
European journal of nuclear medicine and molecular imaging
Sep 22, 2023
PURPOSE: Alzheimer's disease (AD) is a heterogeneous disease that presents a broad spectrum of clinicopathologic profiles. To date, objective subtyping of AD independent of disease progression using brain imaging has been required. Our study aimed to...
Developing a Continuous Severity Scale for Macular Telangiectasia Type 2 Using Deep Learning and Implications for Disease Grading.
Ophthalmology
Sep 20, 2023
PURPOSE: Deep learning (DL) models have achieved state-of-the-art medical diagnosis classification accuracy. Current models are limited by discrete diagnosis labels, but could yield more information with diagnosis in a continuous scale. We developed ...
AI pitfalls and what not to do: mitigating bias in AI.
The British journal of radiology
Sep 12, 2023
Various forms of artificial intelligence (AI) applications are being deployed and used in many healthcare systems. As the use of these applications increases, we are learning the failures of these models and how they can perpetuate bias. With these n...
Automated prognosis of renal function decline in ADPKD patients using deep learning.
Zeitschrift fur medizinische Physik
Aug 21, 2023
An accurate prognosis of renal function decline in Autosomal Dominant Polycystic Kidney Disease (ADPKD) is crucial for early intervention. Current biomarkers used are height-adjusted total kidney volume (HtTKV), estimated glomerular filtration rate (...
Artificial intelligence for dementia drug discovery and trials optimization.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Aug 16, 2023
Drug discovery and clinical trial design for dementia have historically been challenging. In part these challenges have arisen from patient heterogeneity, length of disease course, and the tractability of a target for the brain. Applying big data ana...
Chronic thromboembolic pulmonary hypertension: realising the potential of multimodal management.
The Lancet. Respiratory medicine
Aug 14, 2023
Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare complication of acute pulmonary embolism. Important advances have enabled better understanding, characterisation, and treatment of this condition. Guidelines recommending systematic foll...
Machine Learning Approaches to the Prediction of Osteoarthritis Phenotypes and Outcomes.
Current rheumatology reports
Aug 10, 2023
PURPOSE OF REVIEW: Osteoarthritis (OA) is a complex heterogeneous disease with no effective treatments. Artificial intelligence (AI) and its subfield machine learning (ML) can be applied to data from different sources to (1) assist clinicians and pat...
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