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Biggest AI-based Telehealth Updates for 2022

AI-based telehealth solutions are transforming the global healthcare management systems with superior access to care, support, and rehabilitation across all patient management departments. Despite advancements in patient care technologies, access to quality healthcare still remains a huge challenge, especially in the rural areas in some parts of the developing and under-developed continents. The COVID-19 outbreak in 2020, and subsequent waves of mutating viruses have further exacerbated the gaps in the healthcare industry. While the digital healthcare sector was already growing, the pandemic accelerated its expansion and revealed the potential of telehealth services in ensuring universal healthcare. With the exponential growth of telehealthcare and telemedicine, service providers must incorporate new trends and innovations to optimize the process and respond quickly.

Although the AI concept was first introduced 60 years ago, the rapid advancement of AI-based technology and applications began in the 2010s with the advancement of graphic processing units. Artificial intelligence (AI), the Internet of Things (IoT), and telemedicine are all heavily involved in our daily lives. These technologies control our shopping habits, daily lives, and government administration. It has also been widely used in the medical field, particularly in ophthalmology. Machine learning programs are the most widely used AI techniques today.

There are three types of ML algorithms: supervised learning, unsupervised learning, and reinforcement learning.

These algorithms are involved in the further expansion of telemedicine using AI and NLP capabilities.

Here are some of the areas in AI-based telehealth innovations that have piqued the interest of researchers and CEOs of healthcare companies around the world.

  • AI-based digital consultation
  • Automated patient monitoring and care support
  • AI-based medical examinations and procedures
  • Automated patient electronics healthcare records management
  • AI-based drug administration and monitoring
  • Telepathology
  • Teledematalogy
  • Telepyshiatry,and so on.

Recently, an increasing number of AI algorithms have been studied and accepted in various medical fields to aid in exam interpretation, improve diagnostic accuracy, and reduce time and manpower consumption. Despite the debate over ethical concerns, the trend of using AI in the medical field is unstoppable. AI would undoubtedly progress to a higher level with the advancement and incorporation of new technologies.

One of the important applications of AI in medicine is the provision of accessible screening tools in rural areas with underdeveloped health care systems. The current AI development trend is toward the creation of more complex networks to achieve higher diagnostic sensitivity.

AI for Diagnosis

AI is reinventing and reinvigorating modern healthcare through machines that can read, comprehend, learn, and act, whether it’s finding new links between genetic codes or driving surgery, or assisting robots. Incomplete medical histories and caseloads that are too large can result in fatal human errors. Except that in each of these cases, AI can predict and diagnose disease faster than most medical professionals.

AI for Skin Care

Teledermatology is the practice of dermatology from a distance. With the rapid evolution of communications technology resulting in lower equipment costs, the field of teledermatology is rapidly expanding. Healthcare organizations are rapidly expanding telehealth programs and embracing remote consultation. Deep learning, a type of artificial intelligence, has now reached dermatologist-level performance. According to the smartphone industry, next-generation devices and widespread adoption will put deep learning capable hardware in the hands of consumers all over the world in the coming decade. mHealth devices, specifically smartphone apps and wearable devices, are advancing the field of cardiovascular imaging at an unprecedented rate. Image recognition and automated measurements are also expanding the role of deep learning (DL) techniques. As time goes on, the futures of mHealth, telemedicine, and artificial intelligence will become increasingly intertwined, giving rise to precision medicine.

AI for Heart Care

Artificial intelligence (AI) and machine learning techniques are increasingly being recognized as potential solutions for easing the transition between cardiologists and big data. Recently, the University of Central Florida researchers participated in a new U.S. National Science Foundation-funded project to evaluate the role of artificial intelligence on various heart-related ailments in an AI-based immersive virtual environment. This AI solution can advise physicians and nurses when to switch from remote monitoring to in-person checking, depending on the severity of heart conditions.

AI can incorporate multi-factorial information from many aspects of healthcare, including echocardiographic data, and assist cardiologists in making better clinical decisions even in resource-constrained areas where specialists are not voluntarily accessible. AI, mHealth, and telemedicine hold bright promises, but they are entwined with complex challenges in cardiology and imaging. 

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AI for ENT and Ophthalmology

As various medical automation has liberated clinicians from menial tasks, AI will continue that trend by incorporating increasing volumes of clinical, genomic, and imaging data. This frees up the ophthalmologist’s time to focus on providing effective and compassionate clinical care.


To summarize, AI-based telehealth has a promising future when combined with other technological advancements. Because of the Covid-19 crisis, telehealthcare is thriving and finding new ways to expand in the medical field, such as real-time case visualization, virtual consultation, surgical and clinical training.

Many healthcare institutions now use AI-based telecommunication to screen reports and predict outcomes. Some of the rapidly emerging fields where AI-based telehealth technologies are growing and finding new ways to optimize the process of evaluation, screening reports, imaging, scanning x-rays, and so on are echocardiology, teleradiology, telepathology, telepsychiatry, ophthalmology, and teledermatology.

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