ArticleNPJ digital medicine2020
Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging.
Article in NPJ digital medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 2 of them syntheses that pooled it.
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Who cites it
36 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial intelligence-based algorithms for the diagnosis of retinopathy of prematurity.The Cochrane database of systematic reviews · 2025Pooled it
- Artificial intelligence applied to musculoskeletal oncology: a systematic review.Skeletal radiology · 2022Pooled it
- Multimodal Deep Learning for Humphrey 24-2 Visual Field Prediction: Evaluating the Contribution of Fellow-Eye Information in Glaucoma and Ocular Hypertension.Journal of clinical medicine · 2026Article
- Symmetric Siamese Networks for Longitudinal Chest Radiograph Change Detection: A Leakage-Controlled Study on MIMIC-CXR.Tomography (Ann Arbor, Mich.) · 2026Article
- Artificial intelligence for postoperative plain radiographic assessment after reverse total shoulder arthroplasty: current evidence, clinical readiness, and limitations.Clinics in shoulder and elbow · 2026Article
- AFFUNet: adaptive feature fusion Transformer U-Net with joint loss function for medical image segmentation.Quantitative imaging in medicine and surgery · 2026Article
- Leveraging deep learning to infer continuous predictions from ordinal labels in medical imaging.PLOS digital health · 2026Article
- Artificial Intelligence Framework for Automated Facial Asymmetry Detection Using Key-Point Analysis and Neural Networks.Journal of imaging informatics in medicine · 2026Article
- XL-MSDigger: a deep learning-based, versatile solution for cross-linking mass spectrometry.Nature communications · 2026Article
- Predicting prognosis of patients with hepatitis B virus-related acute-on-chronic liver failure from longitudinal ultrasound images using a multi-task deep learning approach.Annals of medicine · 2025Article
- Longitudinal CE-MRI-based Siamese network with machine learning to predict tumor response in HCC after DEB-TACE.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Highly Accelerated Dual-Pose Medical Image Registration via Improved Differential Evolution.Sensors (Basel, Switzerland) · 2025Article
- Biomarker-Guided Imaging and AI-Augmented Diagnosis of Degenerative Joint Disease.Diagnostics (Basel, Switzerland) · 2025Review
- Siamese neural network-enhanced electrocardiography can re-identify anonymized healthcare data.European heart journal. Digital health · 2025Article
- Deep learning-based automatic ASPECTS calculation can improve diagnosis efficiency in patients with acute ischemic stroke: a multicenter study.European radiology · 2025Article
- A Novel Foundation Model-Based Framework for Multimodal Retinal Age Prediction.IEEE journal of translational engineering in health and medicine · 2025Article
- Unlocking the potential of artificial intelligence in electrocardiogram biometrics: age-related changes, anomaly detection, and data authenticity in mobile health platforms.European heart journal. Digital health · 2024Article
- Review
- The Objective Dementia Severity Scale Based on MRI with Contrastive Learning: A Whole Brain Neuroimaging Perspective.Sensors (Basel, Switzerland) · 2023Article
- Expanding Horizons: The Realities of CAD, the Promise of Artificial Intelligence, and Machine Learning's Role in Breast Imaging beyond Screening Mammography.Diagnostics (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Using medical images to evaluate disease severity and change over time is a routine and important task in clinical decision making. Grading systems are often used, but are unreliable as domain experts disagree on disease severity category thresholds. These discrete categories also do not reflect the underlying continuous spectrum of disease severity. To address these issues, we developed a convolutional Siamese neural network approach to evaluate disease severity at single time points and change between longitudinal patient visits on a continuous spectrum. We demonstrate this in two medical imaging domains: retinopathy of prematurity (ROP) in retinal photographs and osteoarthritis in knee radiographs. Our patient cohorts consist of 4861 images from 870 patients in the Imaging and Informatics in Retinopathy of Prematurity (i-ROP) cohort study and 10,012 images from 3021 patients in the Multicenter Osteoarthritis Study (MOST), both of which feature longitudinal imaging data. Multiple expert clinician raters ranked 100 retinal images and 100 knee radiographs from excluded test sets for severity of ROP and osteoarthritis, respectively. The Siamese neural network output for each image in comparison to a pool of normal reference images correlates with disease severity rank (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.