Cargando…
Fusion of fully integrated analog machine learning classifier with electronic medical records for real-time prediction of sepsis onset
The objective of this work is to develop a fusion artificial intelligence (AI) model that combines patient electronic medical record (EMR) and physiological sensor data to accurately predict early risk of sepsis. The fusion AI model has two components—an on-chip AI model that continuously analyzes p...
Autores principales: | Sadasivuni, Sudarsan, Saha, Monjoy, Bhatia, Neal, Banerjee, Imon, Sanyal, Arindam |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8983688/ https://www.ncbi.nlm.nih.gov/pubmed/35383233 http://dx.doi.org/10.1038/s41598-022-09712-w |
Ejemplares similares
-
In-sensor neural network for high energy efficiency analog-to-information conversion
por: Sadasivuni, Sudarsan, et al.
Publicado: (2022) -
PATIENT-SPECIFIC COVID-19 RESOURCE UTILIZATION PREDICTION USING FUSION AI MODEL
por: Tariq, Amara, et al.
Publicado: (2021) -
Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines
por: Huang, Shih-Cheng, et al.
Publicado: (2020) -
Patient-specific COVID-19 resource utilization prediction using fusion AI model
por: Tariq, Amara, et al.
Publicado: (2021) -
Multimodal fusion with deep neural networks for leveraging CT imaging and electronic health record: a case-study in pulmonary embolism detection
por: Huang, Shih-Cheng, et al.
Publicado: (2020)