The Power of AI and Pulmonology

Artificial intelligence (AI) is rapidly becoming an integral part of health care, and pulmonology is no exception. The lead article in this Specialty Report details how Mount Sinai is using generative AI to conduct in silico scans of millions of potential drugs each day to identify candidates for testing and validation. The goal is to facilitate the identification of safe, effective therapeutics for patients with invasive early-stage lung adenocarcinoma. It is only one of many applications we can expect for AI in our specialty.

Also in the area of lung cancer, we are investigating whether dupilumab, a monoclonal antibody used to treat moderate to severe asthma and multiple allergic conditions, also has the potential to shift the battle against non-small cell lung cancer, in the realm of both treatment and prevention.

Improved diagnostic yields for lung cancer and other conditions are made possible by robotic bronchoscopic cryobiopsy, which can reach smaller and more concealed lesions with much less pneumothorax risk than CT-guided needle biopsies.

Rich, centralized, up-to-the-minute data are key to standardizing and improving the quality of care. Mount Sinai’s new pulmonary dashboards draw from Mount Sinai’s Epic electronic health record and other systems to provide insights on clinical, operational, and research priorities through intuitive visualizations, making it easy to investigate factors such as disease state and patient outcomes.

Exposures to ambient and indoor pollution increase the risk of chronic respiratory diseases, and changes in weather conditions can precipitate exacerbations. To study this, we are blending highly detailed satellite data on temperature, humidity, and air pollution with patient medical records and hospital admission data to better understand the relationship between climate change and human health outcomes. These studies are being conducted in both New York City and Ghana, and we are excited to see what they yield.

In sleep medicine, two initiatives are exploring links between sleep and neurological disorders. We have shown that commonly used wrist actigraphy devices can accurately detect REM sleep behavior disorder, a known risk factor for diseases such as Parkinson’s or Lewy body dementia. A separate study aims to assess whether patients who are successfully treated for obstructive sleep apnea demonstrate a slower decline in cognitive function and lower levels of plasma Alzheimer’s disease biomarkers than those who are untreated.

Finally, we profile our fellowship program at The Mount Sinai Hospital, which is aimed at developing physician-scientists and academic leaders who will advance the field in the laboratory as well as the clinic.

I welcome your thoughts and feedback on this report at charles.powell@mssm.edu. My colleagues and I would also be grateful for your consideration in the upcoming U.S. News & World Report “Best Hospitals” voting.