arterial hypertension
PulseAugur coverage of arterial hypertension — every cluster mentioning arterial hypertension across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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New AI system mimics human driving behavior using memory models
Researchers have developed a novel Neuro-Memory Fuzzy Inference System (NeMeFIS) designed to mimic human-like car following behavior in vehicles. This hierarchical machine learning architecture differentiates between ac…
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New HRL Framework Integrates Patient Preferences into Chronic Disease Treatment Planning
Researchers have developed a new hierarchical reinforcement learning framework called Patient-Centered Factored-Action Hierarchical Option-Critic (FAHOC). This framework aims to improve treatment planning for patients w…
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AI analyzes mammograms to detect heart disease in women
Researchers have developed an AI model capable of detecting heart disease in women by analyzing routine mammograms. This breakthrough could transform breast cancer screening into a dual-purpose tool, identifying cardiov…
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AI models perpetuate disease stereotypes, study finds
AI language models are reinforcing harmful stereotypes by disproportionately associating certain diseases with specific demographics and genders. A study from Australia found that models frequently link conditions like …
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GenFAR framework learns generalized brain representations from 49,246 MRIs
Researchers have developed GenFAR, a novel deep learning framework designed to create generalized, clinically informed feature representations from brain MRIs. This modular architecture was trained on a large dataset of…
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AI framework reveals pathways linking social disadvantage to cardiometabolic disease
Researchers have developed a novel AI-driven framework to explore the complex links between socioeconomic disadvantage, psychosocial factors, and cardiometabolic multimorbidity. By integrating diverse data types includi…
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Machine learning models accelerate chronic disease estimation in US small areas
Researchers have developed machine learning models to address the lag in small-area estimation (SAE) of chronic diseases. By learning the relationship between frequently updated area-level predictors and existing SAE ou…
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New CGMD framework improves hypertension prediction using graph-mediated distillation
Researchers have developed a novel framework called Clinical Graph-Mediated Distillation (CGMD) to improve hypertension prediction from retinal fundus images. This method addresses the challenge of limited paired MRI an…
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AI-first models offer new path for rural healthcare beyond hospitals
Rural healthcare in the United States faces a critical challenge due to its hospital-centric architecture, which is ill-suited for the needs of rural communities. A significant number of rural hospitals are at risk of c…
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New CardioMeta framework improves multi-disease prediction with calibrated probabilities
Researchers have developed CardioMeta, a new multi-task framework designed for the joint prediction of diabetes, hypertension, and cardiovascular disease. This framework aims to improve upon existing machine learning mo…
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AI and wearables enhance hypertension management and risk prediction
A recent publication titled "Management of Hypertension in the Digital Era" explores the integration of artificial intelligence, wearable blood pressure devices, and remote monitoring. These technologies facilitate cont…