Healthcare vs. Pandemic: Where do we stand?
Whether it’s the Spanish flu or COVID-19, viral pandemics are a grave threat to human health. While the world battles the deadly contagion, cutting-edge technologies like Artificial Intelligence (AI) and Machine Learning (ML) are giving a ray of hope to the global healthcare sector through the collection and collation of a large amount of data and sharing this enormous information about the virus as and when available. Robotics and automation technology plays a critical role in collaborating this knowledge and developing practical solutions for diagnosis and treatment.
Robust ML tools and advanced Deep Learning models are fueling a phenomenal transformation in the growth of AI. McKinsey’s acclaimed consulting firm predicts that by 2030, AI will touch a whopping $13 trillion worth of global economic activity. For instance, in the healthcare industry, electronic medical records have replaced volumes of paper documentation for systematic collection and storage of a patient’s medical and treatment history in a digital format that can be disseminated across various healthcare centers for disease diagnosis and treatment. However, this was just one example where advanced analytics is being made possible through the application of Big Data tools – the applications of AI and ML tools in healthcare has progressed by leaps and bounds to include cancer detection and diagnosis, pathology, radiology, drug discovery, personalized medicines, patient management, and most recently, in responding to the deadly COVID-19 outbreak. Examples in this regard include AI-powered Cardiovascular Disease Risk Score API, basic analysis of diagnostics by AI engine, and Computer-aided detection systems.
AI and ML: Responding to Disease Epidemics
The declaration of a pandemic has flipped the world to follow the ‘new normal.’ But we did not get to this point overnight. Much before the WHO issued a public notice, an AI company from Canada had already raised the alarm. BlueDot is famous for identifying the sources of disease epidemics and predicts its mechanism. They gather information through surveys, Machine Learning, and Natural Language Processing, which sift through immense data and accurately identify any ongoing or possible virus outbreaks. Epidemiologists substantiate the scientific validity of such findings, and consequently, the company sends out cautionary alarms to its customers. In this case, the warning was to steer clear of Wuhan, where the Coronavirus originated.
Coronavirus is but one example of other similar viruses with the potential for turning into a pandemic. In this regard, companies like Metabiota are utilizing data-driven techniques to trace the origin and spread of diseases like SARS-CoV-2. Well before the present pandemic, researchers could carry out the real-time prediction of infectious disease dissemination through trained neural networks. AI algorithms are being regularly used to identify preventive measures and develop new drugs in response to COVID-19. Considering the pace at which AI and ML technologies are moving ahead, that day might not be far when we can accurately predict a disease outbreak’s precise location even before it strikes.
The best example of how AI tools and techniques can help us identify newer viral outbreaks is BlueDot’s prompt and advanced warning system. The spread of a particular virus is mostly dependent on how long it can go undetected while propagating the viral progeny in a multitude of hosts. Identification of a new virus strain like SARS-CoV-2 is only the initial step towards orchestrating a response and, in time, developing a drug and vaccine. Also, a timely warning to vulnerable populations limits the rapid proliferation of the pathogen.
AI and ML: Augmenting COVID-19 Research
AI technologies like Natural Language Processing help scientists tackle the enormous amount of data about the novel coronavirus. Machines have enabled the researchers to address the COVID-19 challenge by rapidly extracting the most relevant information from thousands of research papers published every day and understanding the pattern of spread of COVID-19.
Machine learning projects make a massive impact at the core of pandemic intelligence by quickly detecting otherwise impossible patterns for humans to process.
AI and ML: Boons in the Time of Global Crises
Challenging times such as the current COVID-19 pandemic situation have become a significant shock to most industrial sectors. Companies find it hard to cope with the changing terms of competition and business landscapes brought about by the pandemic.
But history bears testimony that bold moves during adverse times have borne fruits – e-commerce giants like JD.com and Alibaba rose to fame during the SARS outbreak in 2003. Even companies like Starbucks and American Express suffering from the after-effects of the financial crisis of 2009 reached new heights of popularity. What’s common in these success stories is a significant shift to digital operating models that enabled them to flourish and rise higher on the ladder of shareholder value.
According to the research conducted by the Boston Consulting Group, 14% of the companies were able to increase their profit margins and sales growth during four prominent global economic slowdowns in the past (shown below).
In this context, the COVID-19 scenario has not proved to be any different. With trends such as remote working and online shopping becoming the new normal, companies will build more efficient value chain systems. The use of AI will immensely help in the adoption of these new trends. Even the healthcare sector will benefit massively. After all, advanced robots can achieve almost anything that a human does – from recognizing objects and handling tasks, AI-powered robots will facilitate the 24/7 operation of facilities with minimum manual intervention. The healthcare field needs humans and machines alike. Thus, a seamless combination of AI with human experience and judgment will turn the tables for the healthcare facilities that need our utmost attention now, more than ever.
Robotics and AI: Revolutionizing Healthcare
AI and robotics have immense potential to transform the healthcare ecosystem. Efficient, quick, and cost-effective, AI can achieve incredible feats with more sophistication and accuracy than humans. There are a growing need and demand for AI and ML technologies in the healthcare industry, and here’s why:
- Early detection- Thanks to AI, many cancers and heart diseases can be detected at early stages using state-of-the-art consumer wearables and medical devices.
- Diagnosis- Watson for Health, by IBM, uses cognitive technology to review and store vast amounts of medical information worldwide to power diagnosis. Google’s Deep Mind Health utilizes systems neuroscience and Machine Learning to mimic a human brain and diagnose healthcare problems in real-time.
- Treatment- The use of robotics in medicine ranges from simple laboratory machines to highly sophisticated surgical robots that can perform operations by themselves or help a human surgeon. Robots are also used for repetitive tasks, physical therapy, rehabilitation, and supporting long-term disease conditions.
- Keeping well- The combination of AI and the Internet of Medical Things (IoMT) used in consumer health applications are encouraging individuals towards a healthy lifestyle without giving frequent visits to the doctor.
- Decision making- AI is beginning to control crucial clinical decisions through predictive analysis and pattern recognition of high-risk individuals.
- Training- AI has allowed medical training programs to provide naturalistic simulations that would have been impossible using simple computer algorithms. The AI computer can be trained to meet the trainees’ learning demands and access training sessions anytime and anywhere.
- Research- The long and tedious journey of a drug from the lab to the patient can take as long as 12 years. In healthcare, drug research and discovery have been streamlined to cut down on marketing time and costs in the latest AI application applications.
- End of life care- Aging brings with it illness and loneliness. The combination of AI and humanoid robot designs can transform end-of-life care by enabling social conversations with aging minds and reducing care homes and hospitals’ needs.
AI and ML: Supporting the Healthcare Ecosystem Amidst the Pandemic
The COVID-19 pandemic may have unleashed several loopholes in the global healthcare system. Still, the contributions of AI and ML in battling the emergency is a silver lining in these distressing times. Experts in the healthcare sector are using AI and Machine Learning techniques in response to the pandemic. From studying the virus, testing potential treatments, and diagnosing individuals, analyzing the impacts on public health, AI and ML are changing the traditional ways of combating disease. Here are some of the highlights of the transformation brought about by these revolutionary technologies:
- Identification of high-risk individuals: Machine Learning has significantly helped predict COVID-19 risks in terms of susceptibility, the severity of symptoms, and treatment outcome concerning age, comorbidities, socioeconomic status, etc.
- Patients’ screening and diagnosis: Simple, rapid, cheap, and large-scale screening and diagnosis of patients through automatic face scans, wearable technology, and machine-learning enabled chatbots.
- Understanding host-virus interactions: Trained Machine Learning models have successfully mapped the possible interactions between the host and the virus that, in turn, influences drug and vaccine development.
- Expediting vaccine development: With Machine Learning, the tedious procedure of vaccine isolation has been significantly accelerated through fast and accurate identification of target regions on the virus.
- Identification of potent existing drugs: Until viable new drugs are approved, Machine Learning has enabled current and reliable drug candidates by predicting drug-viral protein interactions using biomedical knowledge graphs.
- Processing healthcare claims: Machine Learning-powered blockchain platforms have reduced direct interaction between patients and clinical staff while dealing with claims processing.
- Drone delivery: Unmanned aerial vehicles are the fastest and safest way of delivering medical supplies.
- Working robots: AI-powered robots are employed for cleaning, disinfection, sterilization, and delivery.
Artificial Intelligence and Machine Learning harbor immense strength to transform healthcare facilities across the world. However, we have just begun to realize their potential, and there is a lot more that needs to be uncovered. Drug discovery, precision medicine, and preventive healthcare involve a stiff price tag, impacting healthcare’s general cost.
The techniques of AI and ML have largely aided the pharma giants like Pfizer, Genentech, and Sanofi in the process of cost-effective drug development and subsequent market launch. Without the help of advanced deep neural networks and AI-driven algorithms, the prospect of designing personalized medicines would have been bleak. It so would have been the prior prediction of disease occurrence in patients.
The list goes on, but what needs to be remembered is that AI computer systems, however smart, have their limitations. Erroneous or unreliable data can ruin AI’s predictive power, and thus, every AI finding must be validated by human experts. At a time when a single virus has wreaked havoc with our world, we can only rely on advanced technologies to save us.