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Researchers Build Models Using Machine Learning Technique to Enhance Predictions of COVID-19 Outcomes

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Mount Sinai researchers have published one of the first studies using a machine learning technique called “federated learning” to examine electronic health records to better predict how COVID-19 patients will progress. The study was published in the Journal of Medical Internet Research – Medical Informatics on January 27.
The researchers said the emerging technique holds promise to create more robust machine learning models that extend beyond a single health system without compromising patient privacy. These models, in turn, can help triage patients and improve the quality of their care.
Federated learning is a technique that trains an algorithm across multiple devices or servers holding local data samples but avoids clinical data aggregation, which is undesirable for reasons including patient privacy issues. Mount Sinai researchers implemented and assessed federated learning models using data from electronic health records at five separate hospitals ....

Benjamin Glicksberg , Mount Sinai Clinical Intelligence Center , Health System , Icahn School Of Medicine At Mount Sinai , Genomic Sciences , Journal Of Medical Internet Research , Department Of Genetics , Mount Sinai , Medical Internet Research , Medical Informatics , Assistant Professor , Icahn School , Hasso Plattner Institute , Digital Health , Mount Sinai Clinical Intelligence , Akhil Vaid , Machine Learning , ஏற்ற சினை மருத்துவ உளவுத்துறை மையம் , ஆரோக்கியம் அமைப்பு , இக்ஹ்ன் பள்ளி ஆஃப் மருந்து இல் ஏற்ற சினை , இதழ் ஆஃப் மருத்துவ இணையதளம் ஆராய்ச்சி , துறை ஆஃப் ஜெநெடிக்ஸ் , ஏற்ற சினை , மருத்துவ இணையதளம் ஆராய்ச்சி , மருத்துவ தகவல் , உதவியாளர் ப்ரொஃபெஸர் ,

Mount Sinai researchers build models using machine learning technique to enhance predictions of COVID-19 outcomes

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Mount Sinai researchers have published one of the first studies using a machine learning technique called federated learning to examine electronic health records to better predict how COVID-19 patients will progress. The study was published in the
The researchers said the emerging technique holds promise to create more robust machine learning models that extend beyond a single health system without compromising patient privacy. These models, in turn, can help triage patients and improve the quality of their care.
Federated learning is a technique that trains an algorithm across multiple devices or servers holding local data samples but avoids clinical data aggregation, which is undesirable for reasons including patient privacy issues. Mount Sinai researchers implemented and assessed federated learning models using data from electronic health records at five separate hospitals within the Health System to predict mortality in COVID-19 patients. They compared ....

New York , United States , Long Island , Benjamin Glicksberg , Health System , Mount Sinai Clinical Intelligence Center , Icahn School Of Medicine At Mount Sinai , Genomic Sciences , Mount Sinai Health System , Journal Of Medical Internet Research , Icahn School Of Medicine , Department Of Genetics , Mount Sinai , Medical Internet Research , Assistant Professor , Icahn School , Hasso Plattner Institute , Digital Health , Mount Sinai Clinical Intelligence , Akhil Vaid , Mount Sinai Health , New York City , Mount Sinai Hospital , World Report , Medical Schools , Sinai Health System ,

Mount Sinai researchers build models using machine learning technique to enhance predictions of COVID-19 outcomes

Mount Sinai researchers have published one of the first studies using federated learning to examine electronic health records to better predict how COVID-19 patients will progress. ....

New York , United States , Long Island , Benjamin Glicksberg , Health System , Mount Sinai Clinical Intelligence Center , Icahn School Of Medicine At Mount Sinai , Genomic Sciences , Mount Sinai Health System , Journal Of Medical Internet Research , Icahn School Of Medicine , Department Of Genetics , Mount Sinai , Medical Internet Research , Assistant Professor , Icahn School , Hasso Plattner Institute , Digital Health , Mount Sinai Clinical Intelligence , Akhil Vaid , New York City , Mount Sinai Hospital , World Report , Medical Schools , Sinai Health System , Medicine Health ,