AIMC Topic: Disease Progression
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CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer's disease.
BMC geriatrics
Feb 26, 2025
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder that significantly impacts health care worldwide, particularly among the elderly population. The accurate classification of AD stages is essential for slowing disease progression an...
Prediction of clinical deterioration within one year in chronic obstructive pulmonary disease using the systemic coagulation-inflammation index: a retrospective study employing multiple machine learning method.
PeerJ
Feb 25, 2025
BACKGROUND: Inflammatory response and the coagulation system are pivotal in the pathogenesis of clinical deterioration in chronic obstructive pulmonary disease (COPD), prompting us to hypothesize that the systemic coagulation-inflammation (SCI) index...
Regional Cerebral Atrophy Contributes to Personalized Survival Prediction in Amyotrophic Lateral Sclerosis: A Multicentre, Machine Learning, Deformation-Based Morphometry Study.
Annals of neurology
Feb 22, 2025
OBJECTIVE: Accurate personalized survival prediction in amyotrophic lateral sclerosis is essential for effective patient care planning. This study investigates whether grey and white matter changes measured by magnetic resonance imaging can improve i...
Towards realistic simulation of disease progression in the visual cortex with CNNs.
Scientific reports
Feb 19, 2025
Convolutional neural networks (CNNs) and mammalian visual systems share architectural and information processing similarities. We leverage these parallels to develop an in-silico CNN model simulating diseases affecting the visual system. This model a...
AI-facilitated home monitoring for cystic fibrosis exacerbations across pediatric and adult populations.
Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
Feb 18, 2025
BACKGROUND: AI-aided home stethoscopes offer the opportunity of continuous remote monitoring of cystic fibrosis (CF) patients, reducing the need for clinic visits.
Hybrid multi-modality multi-task learning for forecasting progression trajectories in subjective cognitive decline.
Neural networks : the official journal of the International Neural Network Society
Feb 15, 2025
While numerous studies strive to exploit the complementary potential of MRI and PET using learning-based methods, the effective fusion of the two modalities remains a tricky problem due to their inherently distinctive properties. In addition, current...
Deep learning for detecting and early predicting chronic obstructive pulmonary disease from spirogram time series.
NPJ systems biology and applications
Feb 15, 2025
Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung condition characterized by airflow obstruction. Current diagnostic methods primarily rely on identifying prominent features in spirometry (Volume-Flow time series) to detect COPD, but the...
Progression-Free Survival Prediction Performance of ChatGPT: Analysis With Real Life Data in Early and Locally Advanced Prostate Cancer.
The Prostate
Feb 13, 2025
OBJECTIVE: To evaluate the progression-free survival (PFS) time in patients with early-stage and locally advanced prostate cancer and to compare the estimates provided by ChatGPT with actual survival data.
A quantitatively interpretable model for Alzheimer's disease prediction using deep counterfactuals.
NeuroImage
Feb 13, 2025
Deep learning (DL) for predicting Alzheimer's disease (AD) has provided timely intervention in disease progression yet still demands attentive interpretability to explain how their DL models make definitive decisions. Counterfactual reasoning has rec...
Prediction of cognitive conversion within the Alzheimer's disease continuum using deep learning.
Alzheimer's research & therapy
Feb 13, 2025
BACKGROUND: Early diagnosis and accurate prognosis of cognitive decline in Alzheimer's disease (AD) is important to timely assignment to optimal treatment modes. We aimed to develop a deep learning model to predict cognitive conversion to guide re-as...
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