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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 18.

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 at five separate hospitals within the Health System to predict mortality in COVID-19 patients. They compared the performance of a federated against ones built using data from each hospital separately, referred to as local models. After training their models on a federated network and testing the data of local models at each hospital, the researchers found the federated models demonstrated enhanced predictive power and outperformed local models at most of the hospitals.

“Machine learning models in often require diverse and large-scale data to be robust and translatable outside the patient population they were trained on,” said the study’s corresponding author, Benjamin Glicksberg, Ph.D., Assistant Professor of Genetics and Genomic Sciences at the Icahn School of Medicine at Mount Sinai, and member of the Hasso Plattner Institute for Digital Health at Mount Sinai and the Mount Sinai Clinical Intelligence Center. “Federated learning is gaining traction within the biomedical space as a way for models to learn from many sources without

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Quick facts on metastatic breast cancer

Metastatic breast cancer starts in the breast but then spreads to other parts of the body. For example, it could spread to the bones or the lungs. It’s also referred to as stage 4 or advanced breast cancer. It is the most severe form of the disease. 

Although rates of recovery from metastatic breast cancer are lower than for other forms of cancer, the number of U.S. women living with the disease is growing. New treatments can lessen symptoms and keep the cancer from spreading further, helping women live longer.

A recent study from the National Cancer Institute found:

  • In 2020, an estimated 168,000 women in the U.S. are living with metastatic breast cancer.
  • The five-year survival rate of women diagnosed with metastatic breast cancer is increasing, especially among women aged 15 to 39.
  • About one-third of women diagnosed with metastatic breast cancer have lived with it for five or more years.
  • Some women may live 10 or more years after being diagnosed.

More research is needed to address the health care needs of women who live with this condition, according to the study.

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