Cleveland Clinic Reports Findings in Personalized Medicine (Novel Machine Learni ng Identifies Five Asthma Phenotypes Using Cluster Analysis of Real-World Data)

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外文摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Drugs and Therapies - Personalized Medicine is the subject of a report. According to news reporting or iginating in Cleveland, Ohio, by NewsRx journalists, research stated, “Asthma cl assification into different sub-phenotypes is important to guide personalized th erapy and improve outcomes. This study sought to further explore asthma heteroge neity through determination of multiple patient groups by using novel machine le arning (ML) approaches and large-scale real-world data.” The news reporters obtained a quote from the research from Cleveland Clinic, “We used electronic health records of patients with asthma followed at the Clevelan d Clinic between 2010 and 2021. We employed k-prototype unsupervised ML to devel op a clustering model where predictors were age, gender, race, body mass index ( BMI), pre- and post-bronchodilator (BD) spirometry measurements, and the usage o f inhaled/systemic steroids. We applied elbow and silhouette plots to select the optimal number of clusters. These clusters were then evaluated through LightGBM ’s supervised ML approach on their cross validated F1 score to support their dis tinctiveness. Data from 13,498 patients with asthma with available post-BD spiro metry measurements were extracted to identify 5 stable clusters. Cluster 1 inclu ded a young non-severe asthma population with normal lung function and higher fr equency of acute exacerbation (0.8 /patient-year). Cluster 2 had the highest BMI (mean (SD): 44.44 (7.83) kg/m2), and the highest proportion of female (77.5% ) and African Americans (28.9%). Cluster 3 comprised patients with normal lung function. Cluster 4 included patients with lower FEV1% of 77.03 (12.79) and poor response to bronchodilators. Cluster 5 had the lowest FEV1% of 68.08 (15.02), the highest post-BD reversibility, and the highest proportion of severe asthma (44.9%) and blood eosinophilia (>300 cells/mL) (34.8%).”

外文关键词：

Cleveland, Ohio, United States, North an d Central America, Asthma, Bronchial Diseases and Conditions, Cyborgs, Drugs and Therapies, Emerging Technologies, Health and Medicine, Immune System Diseases a nd Conditions, Lung Diseases and Conditions, Machine Learning, Obstructive Lung Diseases and Conditions, Personalized Medicine, Personalized Therapy, Respirator y Hypersensitivity, Respiratory Tract Diseases and Conditions

出版年：

2024

Robotics & Machine Learning Daily News

ISSN：

年,卷(期)：2024.(MAY.9)