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View article: Comprehensive aortic stenosis characterization using multi-view deep learning
Comprehensive aortic stenosis characterization using multi-view deep learning Open
Background and Aims: Accurate assessment of aortic stenosis (AS) requires integration of both structural and functional information characterized by visual traits as well as quantitation of gradients. Existing artificial intelligence (AI) …
View article: Medical Image De-Identification Benchmark Challenge
Medical Image De-Identification Benchmark Challenge Open
The de-identification (deID) of protected health information (PHI) and personally identifiable information (PII) is a fundamental requirement for sharing medical images, particularly through public repositories, to ensure compliance with p…
View article: EchoNet-Quality: Denoising Echocardiograms via Deep Generative Modeling of Ultrasound Noise
EchoNet-Quality: Denoising Echocardiograms via Deep Generative Modeling of Ultrasound Noise Open
Echocardiography (echo), or cardiac ultrasound, is the most widely used imaging modality for cardiac form and function due to its relatively low cost, rapid acquisition time, and non-invasive nature. However, ultrasound acquisitions are of…
View article: Artificial intelligence automation of echocardiographic measurements
Artificial intelligence automation of echocardiographic measurements Open
Background Accurate measurement of echocardiographic parameters is crucial for the diagnosis of cardiovascular disease and tracking of change over time, however manual assessment is time-consuming and can be imprecise. Artificial intellige…
View article: A Multimodal Sleep Foundation Model Developed with 500K Hours of Sleep Recordings for Disease Predictions
A Multimodal Sleep Foundation Model Developed with 500K Hours of Sleep Recordings for Disease Predictions Open
Sleep is a fundamental biological process with profound implications for physical and mental health, yet our understanding of its complex patterns and their relationships to a broad spectrum of diseases remains limited. While polysomnograp…
View article: EchoPrime: A Multi-Video View-Informed Vision-Language Model for Comprehensive Echocardiography Interpretation
EchoPrime: A Multi-Video View-Informed Vision-Language Model for Comprehensive Echocardiography Interpretation Open
Echocardiography is the most widely used cardiac imaging modality, capturing ultrasound video data to assess cardiac structure and function. Artificial intelligence (AI) in echocardiography has the potential to streamline manual tasks and …
View article: SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals
SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals Open
Sleep is a complex physiological process evaluated through various modalities recording electrical brain, cardiac, and respiratory activities. We curate a large polysomnography dataset from over 14,000 participants comprising over 100,000 …
View article: Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study
Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study Open
National Heart, Lung, and Blood Institute.
View article: Deep Learning for Transesophageal Echocardiography View Classification
Deep Learning for Transesophageal Echocardiography View Classification Open
Transesophageal echocardiography (TEE) imaging is a vital monitoring and diagnostic tool used during all major cardiac surgeries, guiding perioperative diagnoses, surgical decision-making, and hemodynamic evaluation in real-time. A key lim…
View article: Confounders mediate AI prediction of demographics in medical imaging
Confounders mediate AI prediction of demographics in medical imaging Open
Deep learning has been shown to accurately assess “hidden” phenotypes from medical imaging beyond traditional clinician interpretation. Using large echocardiography datasets from two healthcare systems, we test whether it is possible to pr…
View article: Deep Learning Discovery of Demographic Biomarkers in Echocardiography
Deep Learning Discovery of Demographic Biomarkers in Echocardiography Open
Deep learning has been shown to accurately assess 'hidden' phenotypes and predict biomarkers from medical imaging beyond traditional clinician interpretation of medical imaging. Given the black box nature of artificial intelligence (AI) mo…
View article: Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality
Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality Open
Background. Pre-operative risk assessments used in clinical practice are limited in their ability to identify risk for post-operative mortality. We hypothesize that electrocardiograms contain hidden risk markers that can help prognosticate…
View article: AI-enabled in silico immunohistochemical characterization for Alzheimer's disease
AI-enabled in silico immunohistochemical characterization for Alzheimer's disease Open
We develop a deep learning approach, in silico immunohistochemistry (IHC), which takes routinely collected histochemical-stained samples as input and computationally generates virtual IHC slide images. We apply in silico IHC to Alzheimer's…
View article: High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy With Cardiovascular Deep Learning
High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy With Cardiovascular Deep Learning Open
In this cohort study, the deep learning model accurately identified subtle changes in LV wall geometric measurements and the causes of hypertrophy. Unlike with human experts, the deep learning workflow is fully automated, allowing for repr…
View article: CloudPred: Predicting Patient Phenotypes From Single-cell RNA-seq
CloudPred: Predicting Patient Phenotypes From Single-cell RNA-seq Open
Single-cell RNA sequencing (scRNA-seq) has the potential to provide powerful, high-resolution signatures to inform disease prognosis and precision medicine. This paper takes an important first step towards this goal by developing an interp…
View article: High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning
High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning Open
Left ventricular hypertrophy (LVH) results from chronic remodeling caused by a broad range of systemic and cardiovascular disease including hypertension, aortic stenosis, hypertrophic cardiomyopathy, and cardiac amyloidosis. Early detectio…
View article: Deep Learning Prediction of Biomarkers from Echocardiogram Videos
Deep Learning Prediction of Biomarkers from Echocardiogram Videos Open
Laboratory blood testing is routinely used to assay biomarkers to provide information on physiologic state beyond what clinicians can evaluate from interpreting medical imaging. We hypothesized that deep learning interpretation of echocard…
View article: The Diversity–Innovation Paradox in Science
The Diversity–Innovation Paradox in Science Open
Significance By analyzing data from nearly all US PhD recipients and their dissertations across three decades, this paper finds demographically underrepresented students innovate at higher rates than majority students, but their novel cont…
View article: Super-resolved spatial transcriptomics by deep data fusion
Super-resolved spatial transcriptomics by deep data fusion Open
In situ RNA capturing has made it possible to record histology and spatial gene expression from the same tissue section. Here, we introduce a method that combines data from both modalities to infer super-resolved full-transcriptome express…
View article: Interpretable AI for beat-to-beat cardiac function assessment
Interpretable AI for beat-to-beat cardiac function assessment Open
Accurate assessment of cardiac function is crucial for diagnosing cardiovascular disease 1 , screening for cardiotoxicity 2,3 , and deciding clinical management in patients with critical illness 4 . However human assessment of cardiac func…