Telemedicine and Artificial Intelligence – Contributions of AI in Telemedicine So Far
Artificial Intelligence (AI) backed telemedicine services are no longer restricted to research laboratories only as they now contribute much to the ongoing efforts aimed to improve healthcare services. Telehealth (or Telemedicine) is referred to as the practical application of electronic data and broadcast communication technologies to help support long-distance clinical medicinal services, patient and expert health-related education, public health, and healthcare organization.
In recent times, a surge has been observed in mobile health, e-diagnosis, and medication. Tata Consultancy Services recently observed in the latest study featuring 56 driving healthcare organizations that said that 86% of them have already embraced AI. According to the Global Observatory survey for eHealth conducted by World Health Organization, AI in the telemedicine field is directly contributing to innovations in areas including teleradiology, telepathology, teledermatology, and telepsychiatry.
How is AI Empowering Telemedicine?
1. Improved Diagnoses with AI
When remote examination/check-ups are combined with AI, considerable progress can be seen with limited specialty labor. Artificial Intelligence can be utilized to reduce hospital queues and wait times and other regulatory pains. While this is currently limited to in-person visits, predictive analytics can help discover specialists quicker for telemedicine patients as. As an example, AI provides the option to course inquiries to the specialist with the best-filtered results for a patient’s symptoms rather than simply sending them to the first doctor available.
Clinicians would already be able to analyze, screen, and treat diabetic retinopathy remotely using telemedicine. The Los Angeles County Department of Health Services recently reduced visits to specialty care professionals by more than 14,000 by implementing telemedicine screenings for diabetic retinopathy at its security net facilities.
2. Remote Patient Monitoring
At present, the greatest use of telemedicine software is patient monitoring. A practical application of AI and telemedicine for monitoring and gathering data on a patient’s progress is the recent study on an Ankle Rehabilitation System with Feedback from a Smartphone Wireless Gyroscope Platform and Machine Learning Classification. AI and ML features add the capability to predict the amount of medication based on previous data and for real-time diagnosis and faster data collection.
The forthcoming times may see a decreased requirement for personal interactions among patients and doctors but the realization of AI applications in telemedicine would highly depend on how rapidly the industry adapts to an all-inclusive digital platform of service offerings to create a circle of trust and security with patients, doctors, nurses, radiologists, vendors and the other important participants in the ecosystem.
Services in healthcare are all about people. With AI, trust and reliability may not be a problem; however, issues related to ethical applications, emotions, and security would continue to pull back applications in telemedicine.
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