Predicting the risk of exacerbation in patients with chronic obstructive pulmonary disease using home telehealth measurement data

Conclusion The CART analyses have shown that features extracted from three types of physiological measurements; forced expiratory volume in one second (FEV1), arterial oxygen saturation (SPO2) and weight have the most predictive power in stratifying the patients condition. This CART algorithm for early detection could trigger the initiation of timely treatment, thereby potentially reducing exacerbation severity and recovery time and improving the patient's health. This study highlights the potential usefulness of automated analysis of home telehealth data in the early detection of exacerbation events among COPD patients.
Source: Artificial Intelligence in Medicine - Category: Bioinformatics Source Type: research