AIMC Topic: Disease Progression

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Discovery of Parkinson's disease states and disease progression modelling: a longitudinal data study using machine learning.

The Lancet. Digital health Jul 29, 2021
BACKGROUND: Parkinson's disease is heterogeneous in symptom presentation and progression. Increased understanding of both aspects can enable better patient management and improve clinical trial design. Previous approaches to modelling Parkinson's dis...
Biological Variation, Individual Dopamine Agents Biological Variation, Population Longitudinal Studies Parkinson Disease Models, Statistical Humans Machine Learning Female Aged Male Middle Aged Disease Progression
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Attention-Guided Deep Neural Network With Multi-Scale Feature Fusion for Liver Vessel Segmentation.

IEEE journal of biomedical and health informatics Jul 27, 2021
Liver vessel segmentation is fast becoming a key instrument in the diagnosis and surgical planning of liver diseases. In clinical practice, liver vessels are normally manual annotated by clinicians on each slice of CT images, which is extremely labor...
Humans Neural Networks, Computer Disease Progression Image Processing, Computer-Assisted Liver Attention
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Outcome-Oriented Deep Temporal Phenotyping of Disease Progression.

IEEE transactions on bio-medical engineering Jul 16, 2021
Chronic diseases evolve slowly throughout a patient's lifetime creating heterogeneous progression patterns that make clinical outcomes remarkably varied across individual patients. A tool capable of identifying temporal phenotypes based on the patien...
Neural Networks, Computer Forecasting Phenotype Disease Progression Humans
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Efficient Source Camera Identification with Diversity-Enhanced Patch Selection and Deep Residual Prediction.

Sensors (Basel, Switzerland) Jul 9, 2021
Source camera identification has long been a hot topic in the field of image forensics. Besides conventional feature engineering algorithms developed based on studying the traces left upon shooting, several deep-learning-based methods have also emerg...
Humans Neural Networks, Computer Algorithms Disease Progression Image Processing, Computer-Assisted
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The cardiovascular phenotype of Chronic Obstructive Pulmonary Disease (COPD): Applying machine learning to the prediction of cardiovascular comorbidities.

Respiratory medicine Jul 7, 2021
BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous group of lung conditions that are challenging to diagnose and treat. As the presence of comorbidities often exacerbates this scenario, the characterization of patients with C...
Humans Machine Learning Phenotype Retrospective Studies Prevalence Comorbidity Cluster Analysis Pulmonary Disease, Chronic Obstructive Male Cardiovascular Diseases Disease Progression Female Aged Aged, 80 and over
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Prediction of skin disease using a new cytological taxonomy based on cytology and pathology with deep residual learning method.

Scientific reports Jul 2, 2021
With the development of artificial intelligence, technique improvement of the classification of skin disease is addressed. However, few study concerned on the current classification system of International Classification of Diseases, Tenth Revision (...
Skin Diseases Humans Deep Learning Neural Networks, Computer Skin Artificial Intelligence Cytodiagnosis Disease Progression
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Characterizing the Clinical Features and Atrophy Patterns of -Related Frontotemporal Dementia With Disease Progression Modeling.

Neurology Jun 22, 2021
BACKGROUND AND OBJECTIVE: Mutations in the gene cause frontotemporal dementia (FTD). Most previous studies investigating the neuroanatomical signature of mutations have grouped all different mutations together and shown an association with focal at...
tau Proteins Middle Aged Mutation Female Atrophy Disease Progression Frontotemporal Dementia Aged Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Adult Humans Neuroimaging Male Machine Learning Brain
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Progress, challenges and global approaches to rare diseases.

Acta paediatrica (Oslo, Norway : 1992) Jun 19, 2021
Rare diseases occur globally at every stage of life. Patients, families and caregivers have many unmet medical and social needs leading to extraordinary psychosocial and economic burdens. Efforts to improve diagnostic capabilities and to develop ther...
Disease Progression United States Caregivers Rare Diseases Humans Artificial Intelligence
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Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.

Nature biomedical engineering Jun 15, 2021
Regular screening for the early detection of common chronic diseases might benefit from the use of deep-learning approaches, particularly in resource-poor or remote settings. Here we show that deep-learning models can be used to identify chronic kidn...
Image Interpretation, Computer-Assisted Neural Networks, Computer Metadata Prospective Studies Photography Fundus Oculi Female Blood Glucose Body Weight Male Glomerular Filtration Rate Middle Aged ROC Curve Humans Retina Body Mass Index Disease Progression Diabetes Mellitus, Type 2 Area Under Curve Deep Learning Body Height Renal Insufficiency, Chronic
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A Pilot Study on Automatic Three-Dimensional Quantification of Barrett's Esophagus for Risk Stratification and Therapy Monitoring.

Gastroenterology Jun 8, 2021
BACKGROUND & AIMS: Barrett's epithelium measurement using widely accepted Prague C&M classification is highly operator dependent. We propose a novel methodology for measuring this risk score automatically. The method also enables quantification of th...
Esophageal Mucosa Humans Female Reproducibility of Results Risk Factors Imaging, Three-Dimensional Treatment Outcome Barrett Esophagus Aged Disease Progression Predictive Value of Tests Automation Male Image Interpretation, Computer-Assisted Severity of Illness Index Risk Assessment Esophagogastric Junction Deep Learning Esophagoscopy Pilot Projects
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