AI in Healthcare:
Why it’s here to stay and not as hard to implement as you might think
David Salim writes about Artificial Intelligence (AI) and how ‘Good Data’ can be key to Good Healthcare too!
AI’s Development
Artificial Intelligence or AI has been in the cultural zeitgeist for years now but still remains a mystery for the majority of people. I think most people still see AI as this ultra high tech software that requires outlandish budgets to operate, and only really being used by big tech companies like Meta, Shopee, Google or even national governments. The truth of the matter is that one can actually create similar programs with tools you can find on the internet for free. The accessibility of said developer tools is one of the contributing factors to why we are seeing a lot more tech startups popping up each year (Moayed, 2021).
AI is a computer code where you set the parameters on how it will receive and process data to return your desired output.
However, just as important as a good programmer/good code is good data (O’Leary, 2013). Good data is described as data that accurately reflects the situation. That’s why another contributing factor to the growth of AI is the continuous improvement of our capacity to record and store massive amounts of data, commonly referred nowadays as big data. Just look at the growth of cloud storage services or customer relationship management (CRM) services (Canalys, 2022).
Big data is where the usefulness of AI comes in. We want to give the tedious task of combing through millions of rows of data to AI so we could get the results of an analysis (that would have taken a human being days or even months to get to) almost instantly.
Specific AI Innovations in the Healthcare industry
The healthcare industry is one industry that is already in the business of storing large amounts of data for their patients. There is huge potential for AI to be applied here and make use of data that might have not been touched since the day it was recorded. Here are just a few examples of how it can be used to improve patient care and hospital/clinic workflow.
1. Chatbots — Using Natural Language Processing (NLP), a model is then trained to give human-like responses through text-based or auditory inputs (Adamopoulou & Moussiades, 2020). Although the technology is still not in a place where it can replace human doctors for diagnosis and treatment, it can answer FAQ questions to assist in the admin work of a clinic or a hospital. There is also an added benefit of anonymity with using a chat bot. Take the Philippines for example where sexual health is still somewhat of a taboo topic. There are still people who would not even dare to bring up questions regarding this topic to their doctors. With a chatbot one may be able to ask their general questions free of any prejudice or malice and receive accurate information backed by honest sources.
2. Product recommendations — With machine learning one can train a model to find patterns in a certain dataset (Rodrigues & Ferreira, 2016). You can see this type of AI in action in some e-commerce websites where other relevant items are recommended to you when you check out a certain product. The AI finds which group of items are usually inquired further or bought together by a user in a single session. As online pharmacies have become more popular due to the pandemic, this recommendation technology can remind users of certain over the counter drugs to better simulate the experience of walking up to a drug store counter where these products are displayed.
3. Supply Chain Management — AI can also be used to manage inventory levels in hospital equipment or products in pharmacies. There are now models to predict movement of trends in demand, dictate optimal points of resupply, etc. (Wenzel, Smit, & Sardesai, 2019). Alessandro De Luca (Healthcare Chief Information Officer) from Merck (a German science and tech company) had this to say about the use of AI in their supply chain planning in an executive report pertaining to their partners in the healthcare industry during the pandemic (Gartner Research, 2020).
“The new systems (AI models) mean we’re better able to mitigate supply shortages, predict spikes in demand, and bottlenecks,” says De Luca. “Initially, this approach was piloted with our portfolio of fertility medicines, but now we’ve expanded the program to incorporate our whole Healthcare portfolio.”
Potential for Abuse/ Ethics
All this new technology can be exciting to implement but we should still be wary of the potential for the tool’s abuse, especially in the healthcare industry where the betterment of the patient is above all. It is key to maximize the benefits while minimizing risks or harm when applied to the health sector.
Responsible AI innovations are defined as those that are ethical, inclusive, and equitable, respect human rights, and contribute to environmental sustainability.
Placing safeguards, having regular checks to see if the AI is doing as it is intended, being transparent to the patient or the public how the technology is being used are ways to make sure that the tool will always be for the care of the patient.
AI4HEALTH Asia — Accelerating Innovations in health across South & Southeast Asia
There is a strong opportunity to advance maternal, sexual, and reproductive health and rights, and adequately address epidemics while strengthening health systems in South and Southeast Asia through the responsible development and deployment of AI innovations.
In January 2023 Villgro Philippines joined hands with International Development Research Centre, Canada (IDRC) to scout, support, and scale Asian AI-enabled healthcare innovators to catalyze the emerging ecosystem towards responsible development of technology while strengthening the capacity of innovators to scale their models to improve health outcomes across South and Southeast Asia.
AI4HEALTH Asia is a 10-month accelerator program designed to nurture innovations in responsible Artificial Intelligence (AI) in South and Southeast Asia. The objective of the program is to fund and support startups that integrate AI innovations to solve health challenges across the region still reeling from the impact of COVID-19, particularly in the areas of (1) Sexual, Reproductive, and Maternal Health, and (2) Epidemic and Pandemic Prevention, Preparedness and Response.
Applications are invited from entrepreneurs with cutting-edge solutions that will transform the way Sexual, Reproductive, and Maternal Health as well as Epidemic and Pandemic Prevention, Preparedness and Response are addressed across emerging Asian countries.
Learn more about the program here: https://villgrophilippines.org/ai4health/ or reach out to us at hello@villgrophilippines.org and ac@villgrophilippines.org for possible collaborations.
About the Author
David Salim is an Incubation Intern at Villgro Philippines providing assistance to the company’s many accelerator programs. He is also in his Senior year as an Industrial Engineering undergraduate in De La Salle University. The course has brought him classroom and internship experience with various data science topics (data analytics, data visualization, and machine learning) and development tools (Excel, Python, Matlab)
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