After being inspired by Deniz Ozer about the use of Artificial Intelligence within the healthcare Industry I decided to do some research and write a blog post of my own. Within this post I will elaborate on the current use of Artificial Intelligence within he healthcare Industry and my beliefs.
Although Artificial Intelligence (AI) can be experienced within everyday life (for example Siri) the use of AI within the healthcare industry might evolve more quickly than the general public might believe. Not only because the use of machine learning, big data and AI is a specialized subject which can only be truly understood with deep knowledge of the subject, but also because the same is true within the healthcare industry. Several thought leaders believe that we are experiencing a new industrial revolution; a revolution that is fusing physical, digital and biological worlds, impacting all types of business, and arguable in specific the healthcare industry. In accordance to the third lecture of the Information Strategy course by Ting li, focussed on Disruptive technologies, we can argue that the healthcare industry is being disrupted by current technologies.
Dr. Bertalan Mesk, the medical futurist, argues that AI within the healthcare industry will help us live better, and is actually happening right now. Wearable devises help us monitor our current vital signs, surgical robots enable doctors to perform surgeries that were not possible within the past and hundreds of thousands have access to their genetic data, which enables them to prevent illnesses. These are all shifts that change the fundamentals of the healthcare business, indicating a disruption. It can argued that investing in A.I. can be extremely beneficial for both company revenues as the general public. (the (The Medical Futurist, 2017)
As argued above Philips, which is currently a 100% healthcare company, states that 60% of their R&D is dedicated to software and a large part of these researchers are working on AI as well. To be able to “perform precise diagnosis, support personalised therapy and intervene early to avoid deterioration” it is essential that Information is structured. According to Jeroen Tas, Philips’ Chief Innovation & Strategy Officer, Over 75% of all information on patients is not structured, which is one of the areas where A.I. could make a difference. Being able to perform correlations across variables within large data sets will enable Philips to better understand a patient’s health situation. Although there is a lot to be improved, Tas mentions that his company is already looking into what role AI, machine learning and analytics can play in navigating these mountains of data. (Philips, 2017)
In another article on Philips’ website it is mentioned that A.I. and the analysis of patient’s big data can breast cancer diagnosis. According to the article deep learning enables the analysis of the vast amount of data extracted from tumour tissue and related patients, stated as the proliferation of digital pathology. Philips argues that as a pioneer in the digitization of pathology, they have created a leading digital pathology business through strategic investments, partnerships and technology licenses. More about this disruptive technology can be seen in the video below. (Philips, 2017)
To conclude we can argue that there is a lot to be learnt and improved with regard to the use of A.I. Within the healthcare industry, but that a lot of steps have certainly already been taken. Although the general public does not directly realize the disruption is taking place, it may have a large influence on the general public’s quality of life. Because Big data can enable the shift within the healthcare industry towards more efficient treatments, diagnosis and rehabilitation, I believe sharing this data is of vital importance. Nevertheless, the disruption within the Healthcare industry may also have negative effects, a topic I will elaborately cover within my next blog post.
VIDEO: https://www.youtube.com/watch?time_continue=5&v=cUeScCtTng4
References:
The Medical Futurist. (2017). Embrace Disruptive Medical Technologies – The Medical Futurist. [online] Available at: http://medicalfuturist.com/grand-challenges/disruptive-medical-technology/ [Accessed 9 Oct. 2017].
Philips. (2017). Philips and PathAI team up to improve breast cancer diagnosis using artificial intelligence technology in ‘big data’ pathology research. [online] Available at: https://www.philips.com/a-w/about/news/archive/standard/news/press/2017/20170329-philips-and-pathai-team-up-to-improve-breast-cancer-diagnosis.html [Accessed 9 Oct. 2017].
Forbes.com. (2017). Forbes Welcome. [online] Available at: https://www.forbes.com/sites/mariyayao/2017/06/01/u-s-falls-behind-china-canada-in-advancing-healthcare-with-a-i/#611ad77206a3 [Accessed 9 Oct. 2017].
Philips. (2017). Connecting Machine Intelligence to Healthcare – Research | Philips. [online] Available at: https://www.philips.com/a-w/research/research-programs/ai-research-at-philips-research-north-america.html [Accessed 9 Oct. 2017].
A.I. and health care is such an interesting and promising intersection. I was just having a conversation with a friend about Skin Cancer and how tec innovations can make a difference in this field. In the last thirty years, more people people suffered from skin cancer than all people suffering from any other form of cancer combine (Stern, 2010). SkinVision works together with dermatologists, doctors and professors and they launched an application with which you can scan moles and other skin conditions and the application will analyse it and give immediate recommendations and it allows you to track changes continuously (SkinVision, 2017). I find this so interesting and imagining how many lives could be saved with this, gets me so excited. However, I believe that there are numerous institutional and legal hurdles to be taken as well as struggles with the acceptance by patients. Especially when considering older generations who aren’t digital natives. Promising thought. I hope there are ways to leverage the potentials also in the health field.
Stern, RS. Prevalence of a history of skin cancer in 2007: results of an incidence-based model. Arch Dermatol 2010; 146(3):279-282.
Skinvision. (2017). Skin Cancer Melanoma detection App | Check your moles or lesion | SkinVision. [online] Available at: https://skinvision.com/?locale=en [Accessed 9 Oct. 2017].