Artificial Intelligence in healthcare and how it will affect you

Artificial intelligence (AI) is set to transform the healthcare industry, poised to impact the cost, quality, and access to healthcare worldwide. From streamlining the drug research process, enabling personalized patient care, to fixing inefficient miscommunication within medical institutions, the list of ways in which AI will shape how we deliver patient care continues to grow. In fact, according to a research report by Global Market Insights, the global ‘Healthcare Artificial Intelligence Market’ is expected to surpass USD13 billion by 2025. The healthcare industry however, continues to present challenges that threaten to slow down this progress. What are the key opportunities and obstacles facing companies and institutions developing healthcare artificial intelligence, and how will they affect you? 

We recently spoke to Susanne Suter, software engineer at Supercomputing Systems AG, at the ‘Women in Digital Health’ event where she was a guest speaker. She shared with us about these opportunities and challenges, and the innovative healthcare projects her team is currently working on to harness AI technology for good.

How do AI and machine learning work? 

“When we talk about AI nowadays, we mean data-driven systems and machine learning,” explained Susanne. During a training process, machines are essentially fed a tremendous volume of high-quality data, what each piece of data means. When this learning phase is completed, the machines are able to predict or classify any new data that is inputted based on its stored knowledge – hence developing its intelligence.

This ability of AI to analyze tremendous volumes of medical data and recognize meaningful patterns within these data sets has proven groundbreaking in healthcare innovation.

The benefits of AI 

For example, AI technology has made it possible to detect potentially life-threatening medical issues in patients early enough so that they can be treated quickly. Supercomputing Systems AG is working on a project with Prof.Dr.med. Emanuela Keller from the University Hospital in Zurich, to develop an AI research system that monitors and analyses real-time medical data of patients at the neuro-intensive care unit, predicting for example the occurrence of brain hypoxia in patients before it happens so that effective preventive action can be taken.

Pharmaceutical companies are also exploring ways to adopt AI technology in drug development; speeding up the drug discovery process and reducing costs. For example, Berg Health is using massive volumes of data from patients with diseases such as prostate cancer in order to identify new targets and develop new drugs. In Europe, global biopharmaceutical company Sanofi recently signed a 250 million Euros collaboration-deal with leading British drug design company Exscientia to discover bispecific small-molecule drugs against metabolic diseases.

The success of AI technology in healthcare, therefore, hinges fundamentally on its access to quality medical data – and lots of it. Collecting quality medical data however continues to present a real challenge for many companies working on harnessing AI technology for good.

Powering AI technology is challenging

Collecting quality medical data is time-consuming. “From my experience, 30 to 50% of time needed to develop an AI system is spent collecting quality data,” shared Swiss Supercomputing AG software engineer Susanne Suter. Furthermore, medical data in most countries continue to be siloed in disconnected systems that are difficult to access. In some cases, this data still resides in handwritten records stored in file cabinets in the doctor’s office. As expressed in Forbes, “Data must flow freely through AI systems to achieve real results but extracting data from handwritten patient files or PDFs is cumbersome for us, and difficult for AI.”

Successful collaboration by experts from fields including medicine and data science is also necessary in developing useful AI systems in healthcare. In a project with Dr. med. Peter Maloca from the Institute of Molecular and Clinical Ophthalmology Basel (IOB), Susanne’s team is developing automated analysis systems that can detect retinal tissues and medical conditions such as tumors in eyes. The team used over 2,000 images taken from an estimated sample of 650 different eyes. Each image had to be marked by experts, i.e. the retinal tissues are drawn on each image, before this data was fed to AI systems as part of the machine-learning process.

Additionally, companies developing AI solutions for healthcare have to actively consider issues related to cybersecurity and data protection. For AI systems that need to be connected to the internet to make use of powerful cloud-based backends, sufficient cybersecurity needs to be put in place to protect it against hacking. Because AI systems depend on the integrity of large medical data sets to be effective, sufficient measures also need to be put in place to ensure that medical data (e.g. from databases maintained by hospitals and other medical institutions) remain protected.

What’s next

The potential AI in technology has in transforming how we receive medical care continues to grow. However, much of this progress still depends on the speed at which the healthcare industry successfully undergoes digital transformation. Additionally, as its success hinges on its access to a high quantity of medical data, questions remain about how the development of AI technology in healthcare will benefit from current efforts to return data ownership to the people – efforts that thereby free medical data previously siloed in medical institutions and restricted by data consent laws, back in the control of people who can consent their transaction.

“AI will ultimately help us in decision-making, but we are still quite far from a reality where machines can think and draw their own conclusions. And in thinking about how to collect quality data, it’s important to remember, the person who owns the data has the power,” concluded Susanne.

The future of AI in healthcare looks bright, and it will surely be an exciting area of healthcare innovation to watch over the next few years.

susanne-suter-foto-2017

Susanne Suter, Dr. sc. Computer Science University of Zurich, has been successfully involved for over 15 years in multidisciplinary innovative projects at the interface between computer science, biology and medicine (including scientific prizes, third-party funds and publications). Since four years, she is working for Super Computing Systems as a software project leader and engineer producing custom-tailored medical software systems such as a patient monitoring system at a neuro-intensive care unit, second-opinion case-review systems for medical doctors, and an automated surveillance service to track the health condition in human eyes.


About the author

Aisha Schnellmann is a Singaporean sociologist by training, interested in healthcare, education, and sustainability issues. She is passionate about producing content that promotes meaningful dialogue, focusing on print and digital content that resonates with a strong call-to-action. Based in Zurich, her interest in digital healthcare grew from the conversations she had with committed medical staff in rural hospitals in Asia, who remain hard-pressed with the technology available to them.

10.4.2019: Digital @ Schulthess Klinik – Träume und Realität

*This event will be held in German and is open to all genders*

Am 10. April 2019 ist “Women in Digital Health” in der Schulthess Klinik in Zürich zu Gast. Unsere Redner werden Andrea Rytz, CEO und Stefan Lienhard, Digital Manager (beide Schulthess Klinik) sein und uns einen Einblick zur Digitalisierung in den Schweizer Spitälern im Allgemeinen sowie in der Schulthess Klinik im Speziellen vorstellen. Was erhofft man sich und was passiert, wenn die schillernden Digital-Träume mit der Realität kollidieren?

Wir freuen uns auf die spannenden Insights und eure Teilnahme!

Interessiert? Dann geht’s hier zum Ticket! 

13.3.2019: Die “Women in Digital Health” Treffen den “Healthcare Women Circle”

Wir freuen uns, einen gemeinsamen Event mit den Frauen des Healthcare Women Circle durchzuführen, um uns gegenseitig kennenzulernen und uns zu vernetzen. 

AGENDA
Empfang ab 18:00 Uhr
Beginn um 18:30 Uhr
Apéro dinatoire ab ca. 19:45 Uhr

ORT
Microsoft Schweiz, Office Wallisellen, Richtistrasse 3, 8304 Wallisellen

Wir starten mit einer Begrüssung durch unseren Gastgebers Microsoft Schweiz. Anschliessend wird uns Mirjam Blechner, Enterprise Channel Manager eine Einführung zum Thema geben mit Ihrem Kurzvortrag «Digitale Services von Microsoft im Gesundheitsbereich». Anschliessend spricht Dr. Daniela Gunz, Director of Research Partnerships bei healthbank innovation AG über «healthbank – the world’s first people-owned health data platform» und wir hören Dr. med. Silke Schmitt OggierMPH, Medizinische Leitung santé24, Telemedizin Zentrum der SWICA Gesundheitsorganisation mit ihrem Referat «BENECURA – Gesundheit als digitaler Service in Patientenhand»

Der Apéro wird heute von Healthcare Women Circle offeriert – herzlichen Dank!

BITTE BEACHTE:Die Vorträge werden alle auf deutsch gehalten (die Slides sind zum Teil auf Englisch) und heute ist es für einmal ein WOMEN ONLY Event.

Interessiert? Dann geht’s hier zum Ticket! 

Alle Teilnehmerinnen müssen Microsoft vorgängig gemeldet werden, damit ein Gästebadge erstellt werden kann. Wir schliessen daher die Anmeldung per 12.3. Es gibt auch keine Abendkasse!

6.2.2019: “Women in Digital Health” presents: “Medical Software Systems Using Artificial Intelligence: Lessons Learned and Prospects” by Susanne Suter (SCS)

Very excited to announce that our next guest speaker will be Susanne Suter, Project Manager and Software Engineer at Supercomputing Systems, with the topic “Medical Software Systems Using Artificial Intelligence: Lessons Learned and Prospects “.

1st part: Susanne will tell us how she became the lead of multidisciplinary innovative projects at the interface between computer science, biology and medicine and how she became a mentor at “Super Computing Sisters: Women in Engineering”.

2st part:

Today, medical systems produce large amounts of signals, images and other health-related information. Hence, there is a great potential to provide health professionals with software tools based on these data sets. At Supercomputing Systems, Susanne was involved in a number of medical software systems such as a web tool for ophthalmological tumor analysis, a patient monitoring system at a neuro-intensive-care-unit, or web-platforms for second-opinion-reviewing systems for ultrasound hip condition diagnosis and ophthalmologic tissue conditions. During her talk, Susanne presents these medical software systems and how they aggregate data and make use of artificial intelligence. In particular, she highlights the lessons learned and prospects of using artificial intelligence for medical software systems.

3rd part: Networking apéro (sponsored by Supercomputing Systems AG), enjoy snacks, drinks, and get to know other people in digital health

Join us at that event and be inspired!

Please book your ticket here:

AGENDA

18:15 Door opening and registration

18:30 Short intro by “Women in Digital Health”

18:40 Talk by Susanne Suter

approx. 20:15: Networking apéro

LOCATION

Supercomputing Systems AG
Technoparkstrasse 1
8005 Zürich

Room: Wing Edison, 5th floor left

ABOUT SUSANNE SUTER

Susanne Suter, Dr. sc. Computer Science University of Zurich, has been successfully involved for over 15 years in multidisciplinary innovative projects at the interface between computer science, biology and medicine (including scientific prizes, third-party funds and publications). In particular, she has experience in the field of biomedical 3D image processing, software services, web applications and automated processing of large amounts of data; both, in the international research environment and in the private industry sector.

Since four years, she is working for Super Computing Systems as a software project leader and engineer producing custom-tailored medical software systems such as a patient monitoring system at a neuro-intensive care unit, second-opinion case-review systems for medical doctors, and an automated surveillance service to track the health condition in human eyes.

Besides, she is committed to boost/connect women in engineering/computer science, as a mentor and currently with the network series “Super Computing Sisters: Women in Engineering” (see https://www.scs.ch/2018/10/frauen-im-engineering/)