The role of Artificial Intelligence (AI) as a major catalyst in the healthcare revolution is unquestionable. We are today experiencing the Fourth Industrial Revolution, and the proliferation of technologies that are fusing the physical, digital and biological worlds and thereby impacting global economies and industries is unparalleled.
While we are seeing the pervasive influence of technology in our lifestyle, we are challenged by the burden of chronic disease on our healthcare system. In the United States chronic disease accounts for $3 of every $4 spent on healthcare or $7,900 for every American with chronic disease. Chronic disease causes 7 out of every 10 deaths. Chronic disease is both predictable and preventable, and AI can play a pivotal role in addressing solutions that can provide personalized medicine, and interventions.
There are some key trends in AI that will become mainstream in addressing the chronic disease challenge in our healthcare system:
Big Data, Deep Learning & Disease Detection – AI has already started revolutionizing the healthcare by leveraging big data analysis to optimize healthcare services. A good example of this service is Google’s Deepmind Health project. IBM Watson for Oncology has an advanced ability to analyze a patient’s data and provide personalized treatment plans that combines the attributes from the patient’s file, clinical expertise, external research and data. These techniques can be also leveraged to detect cancer or vascular diseases in their very early stage.
Precision Medicine & Deep Genomics – Identifying patterns in huge data sets of genetic information and medical records, looking for mutations and linkages in diseases and personalizing the treatment and process protocols for a patient will play a key role in increasing the efficacy of treatment to address chronic disease. Atomwise has launched a virtual search for safe, existing medicines that could be redesigned to treat the Ebola virus. Similarly, nearly 50% of the U.S. population, and almost 90% of people 65 years and over (or approximately 36 million patients), take at least one prescription drug and more than 10% of the U.S. population, and almost 40% of people 65 years and over (or approximately 16 million patients), take five or more prescription drugs. We can leverage AI to address the huge burden on the healthcare system by polypharmacy.
Predictive Analytics – We can leverage the power of AI based predictive algorithms to analyze stress and emotion response. This can be used by analyzing data from images via deep learning micro-expression analysis e.g. Affectiva, Voice stress and intonation analysis e.g. BeyondVerbal and epilepsy seizure detection via brain wave analysis. Google’s, Im2Calories leverages deep learning algorithm to analyze food and estimate calories on the plate. Medical imagery is especially amenable to machine-learning. Moorfields Eye Hospital in London announced that it was working with Google’s AI research division, DeepMind, to develop an AI system to spot sight-threatening conditions in digital scans of the eye. Samsung Medison's ultrasound system uses a deep-learning algorithm (“S-Detect for Breast”) to make recommendations about whether a breast abnormality is benign or cancerous.
Chatbots and virtual assistants – Chinese search engine Baidu has launched a medical chatbot designed to make diagnosing illnesses easier. The conversational bot is named Melody and comes built into the company's iOS and Android Baidu Doctor app, and allows users to contact local doctors, book appointments, and ask questions. Molly the virtual assistant developed by Sense.ly, is optimized to help people with chronic disease to monitor their health and generate personalized treatment plans. Also AI technologies can be leveraged to ensure better treatment plans and medication adherence.
IOT/IOE technologies will augment the healthcare system with data from external systems such as traffic congestion, community events, and environment pollution. These can also be integrated with solar activity and disturbance in earth’s magnetic field to look at correlation on health. Advanced medical data model, and developing AI that can engage patients just like a physician, can be enabled by creating medical maps linking probabilities between symptoms and conditions.
Over the next decade power of AI and the role it will play in healthcare is undeniable. Practicing more precision medicine than intuitive medicine will make health care simpler, more accessible, and less expensive. By understanding patients’ diseases precisely, we can push our healthcare system to deliver the best outcome i.e. patient centric care that is precise, personalized and participatory. We stand on the brink of the’ Fourth Industrial Revolution’, a technological revolution that will fundamentally alter the way we live, work, and relate to one another. AI will be seamlessly integrated into the healthcare fabric and has ability to transform how we look at wellbeing unlike anything humankind has experienced before.