Role of Artificial Intelligence within the Telehealth Domain

Abstract

Objectives: This paper provides a discussion about the potential scope of applicability of Artificial Intelligence methods within the telehealth domain. These methods are focussed on clinical needs and provide some insight to current directions, based on reports of recent advances. Methods: Examples of telehealth innovations involving Artificial Intelligence to support or supplement remote health care delivery were identified from recent literature by the authors, on the basis of expert knowledge. Observations from the examples were synthesized to yield an overview of contemporary directions for the perceived role of Artificial Intelligence in telehealth. Results: Two major focus areas for related contemporary directions were established. These were first, quality improvement for existing clinical practice and service delivery, and second, the development and support of new models of care. Case studies from each focus area have been chosen for illustration purposes. Conclusion: Examples of the role of Artificial Intelligence in delivery of health care remotely include use of tele-assessment, tele-diagnosis, tele-interactions, and tele-monitoring. Further developments of underlying algorithms and validation of methods will be required for wider adoption. Certain key social and ethical considerations also need consideration more generally in the health system, as Artificial-Intelligence-enabled-telehealth becomes more commonplace.

Designing Futuristic Telemedicine Using Artificial Intelligence and Robotics in the COVID-19 Era

“…To summarize, AI and robotics could play an important role in providing telemedicine services during an outbreak or public health emergency while limiting exposure to healthcare workers and health systems (14,42,43). The AI-assisted telemedicine framework proposed by the current consortium could be an enabler in improving telemedicine access and spread across medical specialties and geography.…”

“…In a telemedicine framework, some of these testing may be unavailable, while others may be cost-prohibitive. To address this complex multivariate problem in finding an optimal diagnostic protocol, innovative data-driven artificial intelligence (AI) algorithms may offer a solution by applying machine learning to large datasets of disease populations (14,15). These models can learn directly from the data without any prior statistical modeling, thus producing more objective results while focusing on prediction generalizability for diagnostic purposes on diverse populations.…”

Internet de las cosas: Futuro y desafío para la epidemiología y la salud pública

“…La inteligencia artificial ha logrado increíbles avances en salud, pero un área de gran impacto es la telemedicina, la cual está dando frutos en el contexto de la salud pública. Las innovaciones en este ámbito brindan soluciones reales al problema de la asistencia remota en salud y de hecho, está transformando el desarrollo de nuevos modelos de atención con el uso de tele-evaluación, telediagnóstico, tele-interacciones y telemonitoreo (30) . Esto es algo disruptivo para el campo de la salud, dado que poblaciones de bajos recursos y ubicación geográfica remota pueden tener acceso a determinadas acciones en salud, que junto al desarrollo de drones para casos particulares, generaría grandes beneficios especialmente en países en vías de desarrollo donde la distancia entre zona urbana y rural, afecta el acceso a los servicios de salud.…”

Video consultations for triage of patients with covid-19

“…Healthcare facilities are likely to be overwhelmed with seriously ill patients in forthcoming days, so video consultation platforms would serve a complementary role. Embedding machine learning algorithms into the video consultation platform could facilitate the automation of triage, particularly for responding to queries and identifying those at risk using a symptom checklist and interactive voice interface that uses natural language processing capabilities 3. A potential model of remote home monitoring using video consultations and remote virtual presence has been described for chronic conditions such as end stage kidney disease 4.…”