Early Online (Volume - 9 | Issue - 2)

The Use of Machine Learning Decision Tree Algorithms in Phenotyping Acute Respiratory Distress Syndrome (ARDS) Based on Clinical, Radiological, and Biological Heterogeneity- A Review

Published on: 8th July, 2025

Background: Acute Respiratory Distress Syndrome (ARDS) is a clinically, radiologically, and biologically heterogeneous condition. This variability contributes to diagnostic challenges and inconsistent responses to therapy. Identifying homogeneous subgroups or phenotypes within ARDS may enhance precision medicine and therapeutic targeting.Objective: This review evaluates the utility of decision tree–based supervised machine learning (ML) algorithms—specifically CART, Random Forest, and AdaBoost—in phenotyping ARDS using clinical, radiological, and biological data.Methods: A comprehensive literature search was conducted between December 2023 and March 2024 using PubMed and Google Scholar. Search terms included ‘decision tree in ARDS’, ‘phenotype in ARDS’, and ‘ML in hypo- and hyperinflammatory ARDS’. Twenty-six relevant articles were included, comprising original studies and reviews.Results: Decision tree–based models have demonstrated significant potential in classifying ARDS subtypes using routine clinical variables, radiographic features, and biomarker profiles. These algorithms have shown strong predictive performance in differentiating inflammatory phenotypes, forecasting mortality, and enabling early ARDS prediction.Conclusion: Decision tree algorithms offer a promising approach to ARDS phenotyping by leveraging routinely available data. Their interpretability and predictive accuracy may aid in translating complex biological insights into bedside clinical decision-making, advancing personalized care in critical illness.
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Digital Model’s Structure Andremote Patient Monitoring in Respiratory Medicine

Published on: 21st July, 2025

Digital regression models based on an interactive questionnaire and objectively measured results were used for the investigation of new objective methods of remote monitoring of respiratory patients. 43 patients with COPD and 26 with bronchial asthma were examined in a retrospective-prospective observation study before and after exacerbation in the hospital (the first observation). After that, theywere monitored by a digital system with an interactive questionnaire including results of Smart Watch use and a velometric test at home for at least 6 months. The effectiveness of remote patient monitoring was achieved by changes in the treatment program and rehabilitation. An integrative scale for patient monitoring effectiveness evaluation was used for a comparison study before and after remote monitoring wasstarted (historical control). The results of correlation, regression analysis, and OR calculation showed that new monitoring parameters: velometric test distance, daily steps count, night sleep duration, and the number of night awake ups were dependent on the dyspnea score and FEV1. The system of remote patient monitoring based on a digital model decreased the number of calls for emergency medical care, hospitalizations, and increased the effectiveness score of patient monitoring.
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Inhalation Technique among Patients with Chronic Obstructive Pulmonary Disease Visiting a Teaching Hospital, Chitwan

Published on: 8th August, 2025

Background: Chronic Obstructive Pulmonary Disease (COPD) is a major cause of illness and death worldwide, and inhalers are often used to manage its symptoms. However, patients’ ability to use inhalers correctly is crucial for the effectiveness of treatment.  Incorrect technique can lead to poor management of the disease and limit the effectiveness of the medication. This study aimed to assess the inhalation technique of patients with COPD who visited a teaching hospital in Chitwan.Methodology: A descriptive cross-sectional study was conducted among patients with COPD who had been using a dry powder inhaler through a rotahaler device for at least 1 month and were attending the Medicine and Respiratory OPD of the teaching hospital in Chitwan. A convenience sampling technique was used to select a total of 103 participants. An observational checklist was used to assess inhalation technique, and a structured interview schedule was used to collect socio-demographic information. Descriptive statistics were used to analyze the obtained data in SPSS version 20 for Windows.Findings: The mean age of the 103 respondents was 70.1 ± 9.56 years, and 62.1% of them were female. While 78.6% had observed a demonstration of the inhalation technique, only 5.8% of the respondents performed the inhalation technique correctly, and 94.2% performed it incorrectly. Only 22.3% of the participants were able to perform at least one critical step of the inhalation technique. The most commonly observed errors included placing the mouthpiece between the lips and teeth (20.4%), breathing out through the mouth (21.4%), and inhaling the powder forcefully and deeply (26.2%).Conclusion: Patients with COPD attending the teaching hospital in Chitwan exhibited incorrect inhalation technique, which can affect the effectiveness of medication and disease management. Healthcare providers should emphasize critical steps and common mistakes to ensure that patients receive maximum benefit from their medication.
Cite this ArticleCrossMarkPublonsHarvard Library HOLLISGrowKudosResearchGateBase SearchOAI PMHAcademic MicrosoftScilitSemantic ScholarUniversite de ParisUW LibrariesSJSU King LibrarySJSU King LibraryNUS LibraryMcGillDET KGL BIBLiOTEKJCU DiscoveryUniversidad De LimaWorldCatVU on WorldCat
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