Interview with Bassam Shoukri and Willem de Fiouw from Business Data Challengers about the development of the BDC Image Classification Tool

Bassam Shoukri, one of the developers of BDC's new product, answers a number of questions about the development and the possibilities.

1. You presented a new tool this week. The BDC Image Classification Tool. How and when did the idea to develop this arise?

Together with Hetty Wessel, I took the initiative and a number of colleagues to look for opportunities to use our knowledge and experience in the field of artificial intelligence, machine learning, data science, and processes for the development of innovative solutions with added value for the customer.

In November 2019, we came up with the idea of using artificial intelligence for image classification of MRI scans. The impact of that application has a major influence on the working method within the domain of healthcare and medicine.

2. Who or what inspired you to do this?

In the BDC innovation club we think about possible new solutions and new developments. The goal is for the solution or idea to benefit the community and the business. Our knowledge of the latest technology and the added value of this technology for the customer organization form the starting points for this. From this approach we discovered how image classification is very valuable for the healthcare sector, among others.

3. Do you work with medical specialists?

We work together with Bytesnet Data Center in Groningen and also have a lot of contact with specialists in various hospitals to see how we will apply this using anonymized data from these institutions.

4. Do you have an estimate of how much time this could save the medical specialists?

The use of artificial intelligence saves medical specialists a lot of time when classifying MRI images. This solution helps medical specialists look at the images in a more targeted manner by alerting the specialist to specific parts of the images that require extra attention. An additional advantage is the speed of classification. This method saves a lot of time because a large number of images can be classified in a very short time instead of having the images assessed one by one by a medical specialist.

5. Do you plan to develop more of these types of tools for healthcare? If so, can you tell us something about it?

In BDC's innovation club we are always thinking about new technologies and advanced processes to improve our customers' services.

In the healthcare sector, the Image Classification tool can also be used to classify blood samples. This was tested by BDC with Malaria infected blood images. But the tool can also be used to detect abnormalities on X-rays or to detect Covid-19 in a blood sample.

The product has been developed flexibly. The Image Classification tool can be used in other domains with minimal adjustments. This makes it possible to adapt the technology and use it for object recognition.

We have currently started the next innovation project, the use of text mining and NLP (Natural Language Processing). We help organizations make analyzes based on large amounts of text and documentation. Translate substantive text into a value in dashboards. A complex whole that delivers a lot of value to our customers through the use of new technology.

Also this question for Willem de Fiouw:

Are there more areas where Business Data Challengers will offer innovative solutions?

The healthcare market is an important sector for us. We believe that the use of technology makes an important contribution to more effective and efficient and therefore affordable care. By developing the Data Health scan, the Image Classification tool, but also our solution for capacity issues in healthcare, we fulfill our ambition to offer socially involved services.

In addition to the healthcare market, the safety domain is an important segment for us where we have a lot of knowledge and experience. One of the innovative initiatives that we are taking up with the market there concerns a solution to use AI and ML to extract required information from many thousands of texts and documents and correctly label them based on the content of the text and then present in clear dashboards.

Business Data Challengers