3260 papers • 126 benchmarks • 313 datasets
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These leaderboards are used to track progress in blood-pressure-estimation
Use these libraries to find blood-pressure-estimation models and implementations
MIMIC-III (‘Medical Information Mart for Intensive Care’) is a large, single-center database comprising information relating to patients admitted to critical care units at a large tertiary care hospital. Data includes vital signs, medications, laboratory measurements, observations and notes charted by care providers, fluid balance, procedure codes, diagnostic codes, imaging reports, hospital length of stay, survival data, and more. The database supports applications including academic and industrial research, quality improvement initiatives, and higher education coursework. Design Type(s) data integration objective Measurement Type(s) Demographics • clinical measurement • intervention • Billing • Medical History Dictionary • Pharmacotherapy • clinical laboratory test • medical data Technology Type(s) Electronic Medical Record • Medical Record • Electronic Billing System • Medical Coding Process Document • Free Text Format Factor Type(s) Sample Characteristic(s) Homo sapiens Design Type(s) data integration objective Measurement Type(s) Demographics • clinical measurement • intervention • Billing • Medical History Dictionary • Pharmacotherapy • clinical laboratory test • medical data Technology Type(s) Electronic Medical Record • Medical Record • Electronic Billing System • Medical Coding Process Document • Free Text Format Factor Type(s) Sample Characteristic(s) Homo sapiens Machine-accessible metadata file describing the reported data (ISA-Tab format)
The application of the domain-adversarial training neural network (DANN) method on the authors' multitask learning (MTL) blood pressure estimation model, allowing for knowledge transfer between subjects, improves training with minimal data and reduces RMSE in comparison to the best baseline models.
This work presents an end-to-end deep learning solution, BP-Net, that uses PPG waveform to estimate Systolic BP, Mean Average Pressure (MAP), and Diastolic BP (DBP) through intermediate continuous Arterial BP (ABP) waveform.
The feasibility of leveraging brain BIOZ for BP estimation is explored and a novel cuff-less BP estimation approach called BrainZ-BP is proposed, which can be applied in the brain BIOZ-based ICP monitoring scenario to monitor BP simultaneously.
The results show that this relationship extends beyond heart rate and blood pressure, demonstrating the feasibility of hypertension detection with generalization, and the utilized transform using convolution kernels outperforms the methods proposed in the previous studies and state-of-the-art deep learning models.
Adding a benchmark result helps the community track progress.