How is AI impacting the healthcare industry?

In the wake of the pandemic, the demand for better healthcare services is rapidly increasing. A smart hospital refers to a combination of artificial intelligence, cloud technology, and connected devices utilized to enhance patient’s care services and optimize hospital’s workflows. The objective is to create a connected ecosystem to provide patients with the best experience while allowing hospitals to increase their operational efficiency.

Healthcare startup Subtle Medical has developed a deep learning-based application which enhances images during the acquisition phase of the radiology workflow and improve hospital's productivity by reducing work hours for diagnosis. The company uses NVIDIA’s Graphics Processing Unit (GPU) to improve PET image quality and shortening the image recognition pipeline, from 10 minutes to 10 seconds per patient.

Intel also uses AI based applications to make healthcare services more personalized, connected, and smart. Through Natural Language Processing (NLP), Intel is accelerating the development of telemedicine: In the next years for doctors, it will be normal to visit a patient remotely or to keep automatically note of a visit, uploading it directly into the Cloud. The combination of Telemedicine and AI will help smart hospitals to systematically analyze patients’ real-time data and to respond quickly to emergencies, as AI software can analyze data quicker than humans and more rapidly identify medical issues before they become calamitous.

Also, tech giant Apple is working with hospitals to make it easier for patients to share information with their doctors: Through the Apple Watch, people can share their health data with doctors and keep these recorded in a dashboard accessible through the app. Apple collaborates with many institutions to establish the clinical accuracy of Apple Watch features by continuously upgrading its software and technology, showing that the cardiac metrics it monitors is as good as clinical tests.

Smart hospitals are disrupting the healthcare industry. As reported by MarketWatch, the smart hospital market is expected to be around $77.80B by 2026, growing at a CAGR of 23.5% over the forecasted period. Technology can enrich people’s lives, and AI – including machine learning, deep learning, etc.- plays a critical role to reach this goal. By combining innovative infrastructure and smart technologies, it will be possible to create a metaverse where patients' health can be constantly kept under control and hospitals can respond quicker than ever to emergencies providing more personalized treatments.

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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.

From Work Automation to RPA: A Revolution in the Digital Workers’ Era

In recent years the level of interest in the Robot-as-a-Service ecosystem has increased together with the acceleration of digitalization worldwide. Compared with Traditional Automation, where a machine’s software is programmed and updated by humans to execute specific repetitive tasks, Robotic Process Automation (RPA) is run by an Artificial Intelligence-powered software that allows a machine to autonomously learn and mimic user’s actions and subsequently execute a high volume of repetitive tasks and transactions, with limited human interaction.

RPA is bringing organizations into a new automation era. Digital robots can do a wide range of tasks in a faster and more efficient way than humans. At the same time, with a higher degree of accuracy, they help organizations to reduce workflow costs while improving productivity.

UiPath is among the fastest-growing RPA software Companies in the world. The company developed a high-scale automation software solution for enterprises which operate in different sectors – such as healthcare, finance, or manufacturing, to help them automate repetitive and boring office tasks: By combining different capabilities of AI, Machine Learning, and Deep Learning, the UiPath RPA system can save organizations million-hours of work office and allow employees to be focused on more important things to do.

Another example is Nintex, a global management and automation system developer which provides companies with an RPA bot to control and orchestrate workflows through a simple web interface. Nintex RPA software uses “digital workers” to perform actions similar to human workers, but non-stop, at a higher speed, and without errors, by replicating the same mouse clicks performed by humans. In summary, tasks delegated to the RPA bot interact with apps, systems, websites, and services, allowing people to focus on more relevant aspects of their job.

RPA represents a fast-growing segment as businesses need automated technology to interact more efficiently with their customers and process complex, data-hungry tasks in a faster and more efficient way. According to Gartner, the RPA industry is expected to grow at double-digit rates through 2024. The addressable market is huge, as RPA could disrupt data collection, data processing and predictable physical activities which collectively represent $1.3tn in wages in the US and 51% of time spent in US jobs. As an example, 70% to 80% of both front and back-office processes could be automated in the future.

Of course, human employee performance continues to be critical for the correct functioning of business operations. But RPA is going to be a key component to automate time-consuming processes, limit repetitive tasks, enable quick data entry, and ultimately provide a competitive advantage in the marketplace.

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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.

Tech innovation is shaping the future of the healthcare sector

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.

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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.