Chih-Ying Wu
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Respiratory Medicine
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Predicting Response to Inhaled Corticosteroid Maintenance Therapy in Patients with Chronic Obstructive Pulmonary Disease Using Machine Learning Models
KEYWORDS Pulmonary Disease Chronic Obstructive Corticosteroids Administration Inhalation Machine Learning Get full text access Log in, subscribe or purchase for full access. REFERENCES 1. Boers, E. ∙ Barrett, M. ∙ Su, J.G. ... Global burden of chronic obstructive pulmonary disease through 2050 JAMA Netw Open. 2023; 6, e2346598 2. Sidhaye, V.K. ∙ Nishida, K. ∙ Martinez, F.J. Precision medicine in COPD: where are we and where do we need to go? Eur Respir Rev. 2018; 27, 180022 3.
Predicting outcomes after hospitalisation for COPD exacerbation using machine learning
Introduction COPD significantly contributes to global morbidity and mortality [1]. Exacerbations of COPD (ECOPD), characterised by a sudden worsening of symptoms, frequently result in hospitalisations and are associated with increased systemic inflammation, escalating the risk of subsequent cardiovascular and respiratory complications. ∼18–20% of ECOPD hospitalisations lead to readmissions within 30 days [2, 3], and the post-discharge 30-day mortality rate ranges from 7% to 9% [4].
The Application of Deep Learning to Accurately Identify the Dimensions of Spinal Canal and Intervertebral Foramen as Evaluated by the IoU Index
1. Introduction The lumbar spine is a complex anatomical structure composed of bony vertebrae, intervertebral joints, ligamentum flavum, and intervertebral discs. These elements work in concert with the paraspinal muscles to maintain the overall stability of the human body, facilitating both static posture and dynamic trunk movements.
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