Revolutionizing Hypertension Management and Prediction with AI and Big Data
Revolutionizing Hypertension Management and Prediction with AI and Big Data unknown
The advent of artificial intelligence (AI) and big data has brought about a seismic shift in the management and prediction of hypertension (HTN) and blood pressure (BP) time series. The evolution of digital technology has made daily BP records and BP measurement devices more compact and accessible, paving the way for an era of BP big data.
Smartphone Applications for BP Treatment Assistance
Recent studies have underscored the clinical impact of smartphone applications in aiding BP treatment. These applications allow patients to keep track of their BP levels and adjust their lifestyle and medication accordingly. This level of patient engagement not only aids in better management of hypertension but also improves patient outcomes.
Wearable Monitors and Cuffless BP Measurement Techniques
In addition to smartphone applications, advancements in wearable technology have also contributed to hypertension management. Wearable beat-to-beat BP monitors provide continuous monitoring and offer a more comprehensive view of a patient’s BP levels throughout the day. Furthermore, the introduction of cuffless 24-h BP measurement techniques using photoplethysmography (PPG) has revolutionized the way BP is estimated, making it more convenient and less intrusive for patients.
AI Models for BP Estimation and HTN Prediction
AI models like XGBoost and Transformer have shown promising results in estimating BP. They have also been utilized for HTN prediction, including white-coat HTN, masked HTN, and future BP predictions, demonstrating high accuracy and potential economic benefits. For instance, AI has been used to predict intracranial hypertension (IH) in patients with traumatic brain injury (TBI), showing a high degree of accuracy and readiness to be tested in the clinical workflow. However, it is important to assess possible bias and machine learning readiness level for integration in the clinical workflow.
AI’s Role in Preventive Medicine
AI’s potential extends beyond hypertension management and into preventive medicine. The development of AI-based tools for predicting heart attack risk marks a paradigm shift towards preventive measures based on non-invasive medical imaging. This approach uses personalized data to predict the occurrence of a heart attack, potentially saving lives and improving patient outcomes.
Challenges and the Way Forward
Despite the promising results of AI and big data in hypertension management and prediction, challenges still exist. The accuracy of cuffless BP measurement devices needs to be validated, and their clinical efficacy must be established. Furthermore, integrating AI into real-world clinical practice requires further validation and prospective studies. Nevertheless, the potential benefits of AI and big data in hypertension management and prediction make them a promising avenue for future research and development.