Since the global fallout due to the Covid-19 crisis in 2020, healthcare professionals and governments across the world have been turning to data and advanced technologies to stem the further spread of the coronavirus. This has led to the heightened pace of digital disruption in the healthcare sector, with artificial intelligence (AI) and related fields increasingly being pushed to the forefront.
A huge amount of Covid-19-related data has been collected over the past year for the research of the pandemic. Thanks to AI and machine learning, which take advantage of recent progress in computer processing power that render compiling and handling vast amount of data possible, datasets relating to Covid-19 can be easily shared in real time among key stakeholders, such as medical doctors, public health professionals, scientists and researchers all over the world.
In doing so, not only can scientists and public health authorities better predict the length of hospitalisation and probable health outcomes among different patients, but they can also more accurately detect asymptomatic people who have unknowingly been infected with the virus. A case in point: there may be instances where RT-PCR tests (reverse transcription polymerase chain reaction) may not be sensitive enough to diagnose patients with the contagious disease at the early phase of the infection. However, AI and machine learning have proven great success in its detection of the virus from chest X-ray and CT (computer-assisted tomography) scan images as they can better differentiate Covid-19 from other community-acquired pneumonia.
However, the use of AI in medicine is not new. In cancer research and precision medicine, for instance, scientists have been turning to deep learning software to process millions and millions of genetic data and patient health outcomes in the hopes of uncovering new relationships between tumour genes, cancer growth and certain drugs. After all, the tumour cells of two individuals may look very different at the molecular level under the microscope even though these patients may be suffering from the same cancer type, like breast or prostate cancer. Therefore, personalised treatments offer the best chances of success to patients suffering from the malignancy. Nevertheless, precision medicine is still in its early stage of development since only 10 per cent of patients with advanced cancers have genes that respond well to a new therapy. For this reason, scientists will continue to require a huge amount of genetic data from cancer patients in order to find new treatments.
AI helps turn the huge volume of unstructured data from a liability to an advantage. It is in this context that tailor-made treatments for individuals should become more prominent in the future, as gene-based diagnoses and therapies become more personalised for the patient. However, novel approaches across different disciplines and sectors should be brought together in order for us to be able to move to an era of truly personalised care, which holds great promise in the prevention and treatment of diseases. These certainly include whole genome sequencing, data and informatics.
The adoption of AI in the healthcare industry is also gaining momentum in Gulf countries. For instance, the outbreak of the Covid-19 pandemic across the region has prompted two UAE-based health companies to launch the “world’s first” AI-powered rapid Covid-19 antigen test. Simply by connecting the nasal swabs to a smartphone, a special application can be activated to scan for signs of nucleocapsid protein from SARS-COV-2. And the result is in less than ten minutes. Another application of AI in healthcare can be found in the provision of advice on emotional and mental health issues. Available via the Arabic version of Google Assistant, the AI-powered virtual assistant offers support to users with informed suggestions on how best to deal with difficult emotional situations caused by the pandemic. Also highlighting the importance of cross-border collaboration between key stakeholders on AI and Covid-19, a UAE-based pharma company has signed a deal with a local AI and cloud-computing firm to manufacture millions of doses of Sinopharm vaccines for the Gulf country and the wider region.
Beyond the Covid-19 pandemic, the UAE is also striving to become one of the major healthcare hubs in the world through a series of initiatives and actions. Driven by its rising elderly population and continued economic growth, there has been growing awareness about the importance of harnessing AI and digital technologies to transform its national healthcare industry. For this reason, an AI-based preventive healthcare platform (Enayati) was launched at the 45th edition of Arab Health, which took place in late-January last year, as part of the country’s National Agenda 2021.
The UAE has also announced its plan to launch its first International Artificial Intelligence in the Medical Sector Summit this year.
Although some may argue that it is still early days in terms of fully grasping the potential role of AI in healthcare, one thing is for certain. As the number of older people is expected to multiply further in the region and beyond, the urgency for innovative healthcare solutions is poised to come more to the fore.
The writer is a Next Generation Analyst at Julius Baer