Historically driven by analog processes, healthcare activities have been significantly altered by the technology revolution. The increasing application of Artificial Intelligence (AI) systems is becoming more common in the healthcare industry and is helping healthcare businesses to be faster and more efficient.
Already pre-pandemic, about 80% of hospital leaders said cloud investments were a moderate, high, or critical priority for 2020. Going forward, the convergence of Artificial Intelligence (AI), Blockchain, and the Internet of Things (IoT) will further accelerate innovation adoption and related applications in the healthcare realm.
Technologies like Cloud computing, AI, IoT and machine learning are disrupting the health market and providing patients with new innovative services: for example, by engaging with digital providers, today patients can receive personalized medicines tailored to their specific needs, lifestyles, and genetic code, or can be visited by doctors directly through their smartphone.
Population aging around the world is another major tailwind for digital, patient-centric healthcare services. According to the World Health Organization (WHO), there were 703 million persons aged 65 years or over in the world in 2019. The number of older persons is projected to double to 1.5 billion by 2050. Technological advancements in screening processes, smartphones and wearables can bring point-of-care testing to the patients and represent a strong opportunity for providing sensitive, low-cost, rapid, and connected diagnostics.
There is increasing awareness that AI applications enable to analyze patient's health conditions and identify anomalies at a speed that humans cannot achieve, helping physicians to optimize and avoid time-consuming tasks, and reduce margins of error of diagnosis.
For example, today AI is already just as capable as (if not more capable than) doctors in diagnosing patients heart diseases, blood infections, and detect signs of potentially cancerous cellular growths. IBM’s AI program called Watson was recently challenged to analyze the genetic data of tumor cells. The human experts took about 160 hours to review and provide treatment recommendations based on their findings. Watson took just ten minutes to deliver the same kind of actionable advice.
Despite the rapid advancements in AI and machine learning in HC, we are still a long way from a total replacement of human intervention in medical processes. A research from Harvard showed that patients are reluctant to use health care provided by medical artificial intelligence even when it outperforms human doctors. The main reason is that patients believe that their medical needs are unique and cannot be adequately addressed by algorithms. For this reason, patients were less likely to utilize AI based services and wanted to pay less for it
The most likely evolution is that doctors will be supported by AI to perform repetitive tasks and increase quality of diagnosis at a fraction of time and costs. A recently developed machine-learning algorithm based on deep learning nearly matched the success rate of a human pathologist in interpreting pathology images, at about 96% accuracy. But the truly exciting thing was that combining the pathologist’s analysis the AI diagnostic method, the result improved to 99.5% accuracy,”
In summary: when it comes to healthcare, implementing AI solutions and machine learning will not necessarily mean replacing doctors, but optimizing and improving their abilities. The convergence between the healthcare industry with AI, Cloud computing, IT, and machine learning systems will further catalyze new innovative applications, providing patients with an early and accurate response to treatment and enabling healthcare organizations to reach new quality standards at a lower cost.
The information in this article should not be regarded as a description of services provided by Delian Partners SA. The opinions expressed in this article are for general informational purposes only and are not intended to provide specific advice or recommendations for any individual or on any specific security or investment product. It is only intended to provide education about the financial industry. The views reflected in this article are subject to change at any time without notice.
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