The strategic role of artificial intelligence in developing mobile health

Background and aims: In recent years, the integration of artificial intelligence (AI) into mobilehealth (m-Health) has shown great promise for improving healthcare delivery, enhancing patientoutcomes, and reducing healthcare costs. This review aims to explore the current state of AI applicationsin m-Health and its potential impact on healthcare.Method: A comprehensive search was conducted in electronic databases including PubMed,Scopus, and Web of Science for relevant studies published from ۲۰۱۶ to ۲۰۲۳. The search termsused were “artificial intelligence”, “mobile health”, “m-Health”, and “machine learning”(and synonyms).English language articles were retrieved, screened, and reviewed by the authors. Studiesthat investigated the application of AI in m-Health and its impact on healthcare were included inthis review.Results: A total of ۴۵ studies met the inclusion criteria and were included in this review. Thestudies were conducted in various settings and focused on different aspects of healthcare delivery,including diagnosis, treatment, and monitoring. The most common applications of AI in m-Healthwere in the areas of disease detection and diagnosis, personalized treatment planning, and remotepatient monitoring.Disease Detection and Diagnosis:AI-powered m-Health applications were found to be effectivein the early detection and diagnosis of various diseases. For instance, AI-powered mobile appshave been developed for the early detection of skin cancer, diabetic retinopathy, and lung cancer.These applications use image recognition algorithms to analyze images of skin lesions, retinalscans, and CT scans, respectively, to identify early signs of disease.Personalized Treatment Planning:AI-powered m-Health applications have also been developedfor personalized treatment planning. These applications use machine learning algorithms to analyzepatient data, such as medical history, genetic information, and lifestyle factors, to providepersonalized treatment recommendations. For instance, AI-powered mobile apps have been developedfor personalized treatment planning for diabetes, hypertension, and depression.Remote Patient Monitoring AI-powered m-Health applications have also been developed for remotepatient monitoring. These applications use sensors and other wearable devices to collectpatient data, such as heart rate, blood pressure, and glucose levels, and analyze this data usingmachine learning algorithms to provide real-time feedback to healthcare providers.Conclusion: The integration of AI into m-Health has the potential to transform healthcare delivery,enhance patient outcomes, and reduce healthcare costs. AI-powered m-Health applicationshave been shown to be effective in disease detection and diagnosis, personalized treatmentplanning, and remote patient monitoring. However, several challenges and limitations must beconsidered, including the availability and quality of data, ethical and privacy concerns, and theneed for significant investment in technology and infrastructure. Despite these challenges, thepotential benefits of AI-powered m-Health applications make them an exciting area of researchand development in healthcare.

کلیدواژه ها:

artificial intelligence ، medicine ، mobile health ، machine learning ، healthcare