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Review Papers | Health Sciences | United States of America | Volume 13 Issue 4, April 2024 | Popularity: 5.5 / 10
Transformative Wearables: How AI and ML are Shaping Healthcare Innovations
Bharath Srinivasaiah
Abstract: Transformative wearables are revolutionizing healthcare by enhancing patient outcomes and increasing the efficiency of healthcare services. Wearable devices with artificial intelligence (AI) and machine learning (ML) capabilities can monitor vital signs, track medication adherence, and provide personalized coaching and recommendations to patients. According to a report by Grand View Research, the global wearable medical devices market size is expected to reach $87.77 billion by 2027, growing at a CAGR of 26.8% from 2020 to 2027 [1]. Wearable technology with AI/ML capabilities is rapidly evolving and is becoming increasingly sophisticated, leading to the development of more innovative healthcare solutions. Remote monitoring of patients using wearable devices with AI/ML capabilities has shown promising results in reducing mortality rates and hospital admissions. A study published in the European Journal of Heart Failure found that remote monitoring of patients with chronic heart failure using wearable devices resulted in a 35% reduction in mortality rates and a 40% reduction in hospital admissions [2]. Wearable devices with AI/ML algorithms can also analyze data from multiple sources to provide more accurate diagnoses, improve treatment plans, and reduce the risk of adverse events. For example, wearable devices that track a patient's gait, balance, and mobility can help diagnose Parkinson's disease and multiple sclerosis [3]. Personalized treatment plans generated by AI/ML algorithms can improve patient outcomes and reduce the need for emergency department visits and hospital readmissions, resulting in significant cost savings for both patients and healthcare providers [4].
Keywords: Wearable devices, Artificial intelligence (AI), Remote monitoring, Patient outcomes, Personalized treatment plans
Edition: Volume 13 Issue 4, April 2024
Pages: 152 - 156
DOI: https://www.doi.org/10.21275/SR24402055352
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