Artificial Intelligence

Team Zorg Enablers
Published on
Trends | Diagnosis


“A computer would deserve to be called intelligent if it could deceive a human into believing that it was human”

Alan Turing


Artificial intelligence (AI) is a technology that focuses on making machines ‘intelligent’. Intelligence in this regard is defined as the quality that enables an entity to function correctly and with foresight in its surroundings [1]. AI uses self-learning algorithms that analyse and process data in order to ultimately function independently. They can recognise patterns in datasets that are too complex and too large for the human brain to deal with. Popular AI techniques are machine learning (specifically deep learning) and natural language processing [2].


Applications & benefits

AI is guaranteed to improve patient results and quality of life. AI can assist in making diagnoses and clinical decision-making, monitoring and coaching patients, assisting with treatments and operations, and assisting with the management of healthcare systems [2-4]. The technology changes the cognitive tasks of healthcare professionals, offers possibilities for personalised medicine and makes processes quicker and more cost-effective [3,5]. In this way, AI prevents errors being made [6]. The field of radiology in particular is regarded as a promising area in which AI can support the radiodiagnostic process [7-9].



AI is growing dramatically within the field of healthcare. Whereas in 2012 just 20 investments were made in AI-related enterprises in the USA, this number is expected to be 117 in 2017 [10]. The global market value of AI is expected to continue growing until at least 2022 [11]. Over a third of American hospitals plan to implement AI within the next two years, and over half expect to do so within five years [12]. Last year we reported that 90% of American healthcare institutions are expected to have implemented AI by 2025, compared with 60% worldwide [13]. Furthermore, over half of patients worldwide feel positive about AI technology being applied in treatment programmes [14]. AI chatbots are saving healthcare millions, and a recent study showed that thanks to AI, a total of over EUR 170 billion can be saved on healthcare costs in Europe resulting from obesity, dementia and breast cancer [15,16].


Driving forces

This explosive growth in AI can be attributed to several factors, including:

  • The development of more sophisticated, cheaper and more accessible software and hardware technology for entrepreneurs, together with the advent of Big Data and cloud computing technology, have resulted in the rapid growth of AI techniques such as deep learning [2,3,17]. The digitisation of society and healthcare has resulted in unprecedented quantities of data with which AI can offer support in healthcare.
  • There is growing acceptance among patients and consumers of the fact that AI is contributing towards healthcare quality and cost-cutting [3,18]. Furthermore, healthcare professionals are looking for ways to reduce the increasing workload, a search with which AI can lend a helping hand [3]. With a shortage of healthcare providers and rising costs in the offing, the demand for ‘substitution of human capital’ will increase further [11,17].
  • An increased focus on personalised medicine is pushing the AI market forwards [11]. New applications for this technology are being explored thanks to financial and other contributions from large corporations, and the formation of new joint ventures [11,17].

New technological capabilities
Increased awareness and growing acceptance
Supply matches demand

Hindering forces

High costs (development, purchase, and maintenance)
Lack of expertise
Increasing emphasis on privacy sensitivity

There is no question that this technology is growing explosively, but there are still some obstacles to be overcome before AI can be fully integrated into healthcare. Technical shortcomings and high investments without clear a business case are obstructing a wide roll-out in healthcare, which therefore demands a step-by-step approach [3,12,19,20]. This requires the involvement of experienced and qualified personnel [3,21]. Despite growing acceptance, trust still has to be won [19]. Patients and healthcare professionals also have to provide input with respect to the development of AI systems [3,21]. Ways must be identified in which AI might take over certain tasks and in doing so perhaps influence the added value of human intervention [3,20]. Last but not least, concerns about privacy also play a role [3]. In order for AI to be a success, adequate high-quality data must be made available [19]. Stringent regulations and legal aspects as well as ethical considerations will have to be addressed when implementing AI technology in healthcare [19]; this is generally not yet the case [2,17].



AI is on the rise and, as well as having a huge impact, will drive personal and predictive healthcare. Partly as a result of AI, the diagnostic process will be reformed, although in the short-term many obstacles still have to be overcome. Experts predict that within 45 years, AI systems will be able to perform a wide range of tasks better than humans.


  1. Nils J. Nilsson, The Quest for Artificial Intelligence: A History of Ideas and Achievements. 2010
  2. Jiang F. et al. Artificial intelligence in healthcare: past, present and future. SVN. 2017: 2(3)
  3. The One Hundred Year Study on Artificial Intelligence. Artificial intelligence and life in 2030. September 2016
  4. New narrative Ltd. Future health index. Philips 2017
  5. United Nations, Department of Economic and Social AffAIrs, Population Division (2013). World Population Ageing 2013.
  6. Quora. How will Artificial Intelligence change healthcare? Forbes. Juni 2017.
  7. Mesko B. The future of radiology and artificial intelligence.
  8. Campbell D. Patients’ illnesses could soon be diagnosed by AI, NHS leaders say. The guardian. September 2017
  9. Jacobs F. Kunstmatige intelligentie verandert beroep van de radioloog. Smarthealth. November 2016.
  10. CB Insights. Up And Up: Healthcare AI Startups See Record Deals. Augustus 2017
  11. Marketsandmarkets. Artificial Intelligence in Healthcare Market by Offering (Hardware, Software and Services), Technology (Deep Learning, Querying Method, NLP, and Context Aware Processing), Application, End-User Industry, and Geography – Global Forecast to 2022. Mei 2017
  12. Sullivan T. Half of hospitals to adopt artificial intelligence within 5 years. Healthcare IT News. April 2017
  13. Das R. Five technologies that will disrupt healthcare by 2020. Maart 2016
  14. PwC. What doctor? Why AI and robotics will define New Health. 2017
  15. Juniper Research. These AI Start-ups are Disrupting Healthcare in a Big Way. 2017
  16. PwC. Sherlock in Health. How artificial intelligence may improve quality and efficiency, whilst reducing healthcare costs in Europe. 2017
  17. Allied Market Research. Artificial Intelligence in Healthcare Market by Offering, Technology, Application, and End User – Global Opportunity Analysis and Industry Forecast, 2017-2023. Juli 2017
  18. Bughin J. et al. Artificial Intelligence – The next digital frontier? Discussion paper. McKinsey Global Institute. Juni 2017
  19. Mesko B. Artificial intelligence will redesign healthcare. 2017
  20. Accenture. Artificial intelligence: Healthcare’s new nervous system. 2017
  21. Grace K. et al. When Will AI Exceed Human Performance? Evidence from AI Experts. arXiv. Mei 2017