As the years go by, many possibilities of Artificial Intelligence application have been realized and many are yet to be. Despite the progress that several industries have made in the AI front, healthcare continues to be one sector where it has truly made a major impact that goes beyond convenience and essentially affects human lives.
Artificial intelligence (AI) is defined as “the science of making computers do things that require intelligence when done by humans” by Turing Archive for the History of Computing. While we have not reached the level of sophistication in AI as in the Westworld, the AI technology is quickly developing.
The potential of AI in Healthcare
AI can re-design and improve healthcare in multiple ways. For e.g. it can assist medical professionals in designing treatment plans and finding the most suitable treatment method that is the best for the particular patient. It can help in carrying out tasks that are monotonous so that physicians can concentrate on their core jobs.
There are already few great examples of AI in healthcare which show great potential. Mining medical records are one of those evident applications of AI in healthcare.
Mining Medical Records
Data management is one of foremost potential-showing AI application in healthcare. The first step towards revolutionizing the existing healthcare systems is to collect it, store it, normalize it and trace its lineage. It contains developing a natural language processing technology to automatically extract data from narrative medical records.
Google Deepmind Health, is used to mine medical records in order to offer better and faster health services. It is able to process hundreds of thousands of medical information within a matter of minutes. Although machine learning and data-harvesting are at its initial stage- at the moment Google in co-ordination with Moorfields Eye Hospital NHS Foundation Trust is striving to improve eye treatment.
Assisting in Monotonous Tasks
AI can help in carrying out repetitive tasks which take away medical professional’s time from their core jobs. Tasks such as x-ray scans, CT scans, analyzing tests and data entry etc. can be done faster and more accurately by robots. Radiology and cardiology are two such disciplines where the amount of data for analyzing can be time-consuming and overwhelming and time-exhausting.
IBM Medical Sieve is an ambitious long-term exploratory project which plans to build the next-generation “cognitive assistant” which is capable of analytics and reasoning with a vast range of clinical knowledge. Medical Sieve can help in making the clinical decision regarding cardiology and radiology – a “cognitive health assistant” in other terms. It is able to analyze the radiology images to detect problems reliably and speedily.
AI chatbots use natural language processing to understand the user’s demands followed by knowledge management to offer an answer. Further, it uses deep learning to improve its response to each interaction. Sentiment analysis identifies the user’s issue and then transfers them to a human. In the context of healthcare, chatbots can fulfill various objectives like diagnosing the patient using the information given on symptoms.
Your.MD – This Chatbot uses Artificial Intelligence technology to guide the user with most relevant information for better health and life. It provides the most accurate and simplest to understand medical information.
Virtual Healthcare Assistants
Virtual healthcare assistants aim to use AI technology to enhance interactions between patients and caregivers to improve the consumer experience as well as reduce physician burnout.
Nuance Communications Virtual assistant platform enables conversational dialogue and pre-built capabilities that automate clinical workflows. The healthcare virtual assistant employs voice recognition, EHR integrations and strategic health IT relationships, voice biometrics, text-to-speech and prototype smart speaker customized for a secure platform.
AI systems have been designed to analyze data- reports and notes from a patient’s file, clinical expertise and external research, in order to assist in selecting the correct, individually customized treatment path.
IBM Watson provides clinicians evidence-based treatment options. Watson for Oncology has an advanced ability to analyze the meaning and context of structured and unstructured data in clinical notes and reports that may be critical to selecting a treatment pathway. The program ultimately identifies most potential treatment plans for a patient integrating notes on patient’s life, research and clinical expertise.
Development of pharmaceuticals via clinical trials can take more than a decade and cost a lot. Therefore, making the process speedier and cheaper is one of the main objectives AI startups are aiming for.
Atomwise – Amongst the recent Ebola scare, an AI powered program for scanning existing medicines that could be redesigned to fight diseases was utilized. The technology found two drugs that may significantly decrease Ebola infectivity. This analysis, which would have otherwise taken months/years, was completed within 24 hours. This efficiency in drug creation has the potential to save thousands of lives.
Conclusion: Our View
Even with big advancements of AI application in healthcare over the recent years, it is unlikely that technology will replace the diagnostic role of physicians- at least in the near future. AI, however, is now sophisticated enough to take over the tedious repetitive tasks that used take up the productive hours of a physician. The potential AI holds in healthcare is endless- with professionals exploring the application of AI in areas like insurance verification, skin cancer diagnosis, medical record data analysis etc.- we are just beginning to realize the true depth of health-tech innovation that can be unlocked with AI technology.