webAI Digital Health
The webAI Digital Health Agent was trained by ISTARI.AI to identify companies with a focus on the digital health sector and to map their focus on this topic as an individual Digital Health Intensity Score. This numerical indicator measures how centrally the topic of digital health is communicated by the company on its own website and presented as essential for its own business model.
Digital Health includes theuse of information and communication technology (ICT) in the field of healthcare. More specifically we look at four sub-segment:
- E-health: Companies that offer services or products that are used to support the treatment and care of patients with modern ICT methods. This includes, for
example, the communication of medical data made available with an electronic health card. Electronic prescriptions for medicines and electronic patient records
also fall into this category. Examples are: Pharmacies that accept electronic prescriptions, doctors and clinics that allow appointments to be made digitally, manufacturer of card readers for electronic health cards, developers offering software for electronic medical records or patient management systems, providers and users of software for online consultations, online pharmacies.
- Trend Health: Companies that offer digital services and products from the health sector mainly for private consumers. This includes applications and products for self-care and disease prevention (elderly care / assisted living), vital data monitoring with medical wearables (activity trackers, mHealth apps). Examples are: Manufacturer of wearable smart insulin pump, manufacturer of wearable fitness tracker, manufacturer of wearable, digital SOS button for seniors, developer of calorie counting app, developer of fitness tracking app, manufacturer of smart body scale, developer of AI health companion, provider of genetic testing for private individuals.
- Tech Health: Companies that offer novel digital services and products from the health sector mainly for professional consumers. This includes products and services from the fields of robotics, big data, artificial intelligence, sensor technology and 3D printing. Examples are: Provider of software for AI-supported analysis
of disease data (e.g. cancer detection), digital (robotic) prosthesis manufacturer, manufacturer of 3D printers for medical needs, manufacturer of remote-controlled robots for operations, manufacturer of nanorobots for diagnostics.
Companies that are active in these digital health-related areas, have business fields geared to them, or offer products and services with a direct connection, usually communicate this on their websites. The more central the topic is for the company, the more significant it is for the company’s external communication. For example, a startup for health monitoring software communicates almost exclusively on the topic of digital health, while a clinic, which among many other (more traditional health) services also offers digital consulting hours, does so only to a limited extent.
Our webAI reads the website of the company under investigation and searches for text sections (paragraphs) that deal with the topic of digital health. To do this, webAI first searches for keywords that are potentially related to digital health, analyzes the paragraphs identified in this way, and determines whether or not they are actually digital health-related texts. If webAI has assigned a corresponding paragraph to the topic of digital health with a high probability, webAI remembers this paragraph and continues searching. In this way, webAI searches the entire company website or the particularly relevant “top-level” sub-pages if it is a very extensive website with hundreds of sub-pages (for more information, see the publication: Web mining for innovation ecosystem mapping: a framework and a large-scale pilot study).
In this way, webAI finds a certain number of paragraphs per company website that deal with the topic of digital health. WebAI then puts this number in relation to the total amount of text content read on the website. In this way, webAI determines a Digital Health Intensity for each company.
The Digital Health Intensity Score calculated in this way would be 0.0 for a company with no digital health-related texts. For the example of a clinic described above, the calculated intensity value could be 0.15 and 3.97 for the startup that is particularly focused on digital health. The Digital Health Intensity Score has no upper limit. In addition, we integrate an auxiliary column into our data as an interpretation and reading aid. It categorizes the intensities from “low” to “very high”. In the example above, the clinic would be classified as “low” intensity and the startup as “very high” intensity.
In contrast to simpler, binary classifications (“Digital Health YES/NO”), webAI outputs a continuous score at the company level. This makes it possible to distinguish between companies for which digital health is only a peripheral issue and those for which it plays a central role. Users of the webAI data can thus easily determine for themselves how strongly a company should be engaged in the digital health sector for it to be relevant to them.
In Europe, it can be said that 1% of the companies studied have a Digital Health Intensity Score of greater than 0.0 and thus communicate the topic of digital health in some form on their websites. The average Digital Health Intensity Score of these companies is 0.4 and half of the companies have a score lower than 0.17. The maximum score achieved is 5.3, with 11% achieving a score of 1.0 or higher.
Like all our webAI agents, the webAI Digital Health Agent was developed and validated together with independent subject matter experts. This ensures that we train the webAI agent with real expert knowledge and that it then delivers expert-level results. For this agent ISTARI.AI has collaborated with researchers from the University of Mannheim. The Energy Intensity Scores are currently also being validated in a not yet published study.
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