Quality

The best of both worlds. Human and Artificial Intelligence.

The interaction between humans and AI offers the best of both worlds. This combination enables us to meet the highest standards of performance and safety as a medical device. 

Highest quality through clearly defined processes.

Proven quality

Proven quality

All our solutions are certified by a notified body as Class IIa medical devices (certificate pending) and therefore meet the highest quality and safety standards. 

Technological innovation

Technological innovation

We use technology where it makes sense. By leveraging AI, we can automatically analyze and process millions of medical publications to create the baseline for our algorithms.

Perfect symbiosis

Perfect symbiosis

The practical knowledge of doctors combined with millions of medical publications and groundbreaking technology create the perfect symbiosis between humans and AI.

Trust is good, control is better.

Medical device with CE certification

Our technology is certified as a Class IIa medical device (certificate pending). This means that an independent notified body, in our case TÜV Süd, verifies our compliance with norms and standards in annual audits.

Quality management according to ISO 13485

The safety of our products has absolute priority for us, therefore all key processes in the company are certified according to ISO 13485:2016. This quality management system ensures that the highest standards of performance and safety are reliably met.

Standardized processes and norms

Being a medical device manufacturer, we have to adhere to a large number of regulatory requirements, which are ensured by compliance with standards. In addition to the ISO 13485-compliant quality management system, we meet the requirements of the following relevant standards, directives and laws:

  • Medical Devices Directive (MDD) 93/42/EEC with 2007/47/EC
  • Medical Devices Regulation (MDR) 2017/745
  • Medical Devices Act and relevant regulations
  • EN ISO 14971:2019
  • EN 62304:2006 + A1:2015
  • EN 62366-1:2015
  • EN 82304-1:2017

In addition to this, we comply with all local regulations in countries where we market our product.

Committed to security and data protection.

State-of-the-art encryption methods

State-of-the-art encryption methods

By using state-of-the-art encryption methods when transferring and storing health information, we guarantee the security and privacy of sensitive data.

Sophisticated database architecture

Sophisticated database architecture

We prevent unauthorized access to data through structural and technological barriers. No one other than the user can view personal health data.

Data centers in Austria and Switzerland

Data centers in Austria and Switzerland

By relying on local storage with certified data centers, we ensure that no sensitive information leaves the European legal area.

The knowledge of millions in one health solution.

Data analysis with AI

Data analysis with AI

Our artificial intelligence can analyze millions of medical publications from the literature and process data on over 4.000 medical conditions.

Review by doctors

Review by doctors

Our team of doctors then verifies this information qualitatively and enriches it with reference literature and practical experience.

Medical stress test

Medical stress test

We verify our technology with thousands of real life case studies. This is the most objective way to test accuracy of our system.

Usability tests

Usability tests

Through ongoing testing with real users, we ensure that our medical algorithms work as intended and meet the defined requirements.

Convincing medical accuracy and reliability.

We verify the medical accuracy of our technology in medical stress tests. This happens continuously and on the basis of thousands of case studies from the literature. The goal is to identify the verified diagnosis from the case study as a possible outcome. This has proven to be the most reliable method of testing medical accuracy under objective conditions.

Medical accuracy
91,1 %

Tested with XUND v.1.2.0 based on case studies by Semigran et al. 2015.

Benchmark with case studies from the standard literature.

In order to objectively assess the quality of XUND also in comparison to other solutions, we assessed the 45 case studies from one of the most frequently cited publications in the domain. These case studies are regularly used by researchers to evaluate medical accuracy, most recently by Ceney et al. 2021.

ICD-10
Medical condition
Age
Result
ICD-10B30
Medical conditionViral conjunctivitis
Age14 Years
Result identified
14-year-old male with viral conjunctivitis
ICD-10: B30
Present symptoms:
  • Red eyes
  • Tearing eyes
  • Sore throat
  • Cough
  • Sniffles
Additional information:
Are your eyes "glued" shut when you wake up in the morning?
Yes
Have you recently had contact with a person suffering from similar symptoms?
Yes
Are you aware that in the last 14 days you have had personal contact with a person suffering from COVID-19?
No
Source:
Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015
Verified diagnosis identified as 1. result
Conditions identified by XUND:
  • Viral conjunctivitis
  • Acute bronchitis
  • Common cold
ICD-10N23
Medical conditionRenal colic
Age45 Years
Result identified
45-year-old male with renal colic
ICD-10: N23
Present symptoms:
  • Flank pain
  • Nausea
  • Vomiting
  • Groin pain
Additional information:
Gently tap your flanks. Does that hurt?
Yes
Source:
Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015
Verified diagnosis identified as 2. result
Conditions identified by XUND:
  • Renal pelvis inflammation
  • Renal colic
ICD-10I82.40
Medical conditionDeep leg vein thrombosis
Age65 Years
Result identified
65-year-old female with deep leg vein thrombosis
ICD-10: I82.40
Present symptoms:
  • Leg pain 
  • Swelling of the leg 
  • Difference in leg circumference 
  • Reddening of the skin 
Additional information:
Are you suffering from hypertension?
Yes
Are you aware of any heart disease?
Yes
Have you recently had a period in which you haven't moved much?
Yes
Source:
Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015
Verified diagnosis identified as 1. result
Conditions identified by XUND:
  • Deep leg vein thrombosis
  • Factor V Leiden Mutation
ICD-10A02.0
Medical conditionSalmonella infection
Age14 Years
Result identified
14-year-old male with salmonella infection
ICD-10: A02.0
Present symptoms:
  • Nausea
  • Vomiting
  • Diarrhea
  • Fever
  • Abdominal pain
  • Abdominal cramps
Additional information:
Have you eaten raw meat, raw fish or raw eggs in the last three days?
Yes
Source:
Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015
Verified diagnosis identified as 2. result
Conditions identified by XUND:
  • Rotavirus
  • Salmonella infection
  • COVID-19 Infection
ICD-10J44
Medical conditionCOPD
Age56 Years
Result identified
56-year-old female with COPD
ICD-10: J44
Present symptoms:
  • Breathing difficulties
  • Cough
  • Sniffles
Additional information:
Have you been suffering from such complaints regularly for a longer period of time?
Yes
Do you smoke or have you been a smoker in the past?
Yes
Source:
Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015
Verified diagnosis identified as 1. result
Conditions identified by XUND:
  • COPD
  • Acute bronchitis
  • COVID-19 infection
ICD-10I82.40
Medical conditionDeep leg vein thrombosis
Age28 Years
Result identified
28-year-old male with deep leg vein thrombosis
ICD-10: I82.40
Present symptoms:
  • Leg pain
  • Swelling of the leg
  • Difference in leg circumference
  • Reddening of the skin
Additional information:
Are you suffering from hypertension?
Yes
Are you aware of any heart disease?
Yes
Have you recently had a period in which you haven't moved much (e.g. air travel or bed-riddenness)?
Yes
Source:
Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015
Verified diagnosis identified as 1. result
Conditions identified by XUND:
  • Deep leg vein thrombosis
  • Factor V Leiden Mutation
  • Vein inflammation
ICD-10J20
Medical conditionAcute bronchitis
Age61 Years
Result identified
61-year-old female with acute bronchitis
ICD-10: J20
Present symptoms:
  • Cough
  • Sniffles
  • Fever
Source:
Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015
Verified diagnosis identified as 1. result
Conditions identified by XUND:
  • Acute bronchitis
  • Common cold
  • COVID-19 infection
ICD-10J02
Medical conditionPharynx inflammation
Age26 Years
Result identified
26-year-old male with pharynx inflammation
ICD-10: J02
Present symptoms:
  • Sore throat
  • Cough 
  • Headache 
  • Red throat
Additional information:
/
No
Source:
Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015
Verified diagnosis identified as 1. result
Conditions identified by XUND:
  • Pharynx inflammation
  • Acute bronchitis
  • Common Cold
ICD-10K37
Medical conditionAppendicitis
Age12 Years
Result not identified
12-year-old female with appendicitis
ICD-10: K37
Present symptoms:
  • Abdominal pain
  • Nausea
  • Vomiting
  • Diarrhea
  • Fever
  • Hard abdominal wall
Additional information:
Has your appendix already been removed?
No
Are you aware that in the last 14 days you have had personal contact with a person suffering from COVID-19?
No
Source:
Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015
Verified diagnosis could not be identified
Conditions identified by XUND:
  • Rotavirus
  • Salmonella infection
  • COVID-19 infection
ICD-10R10.83
Medical conditionBaby colic
Age1 Years
Result not identified
1-year-old male with baby colic
ICD-10: R10.83
Present symptoms:
  • Constipation
  • Anal bleeding
  • Changed stool color
Source:
Evaluation of symptom checkers for self diagnosis and triage: audit study Hannah L Semigran, Jeffrey A Linder, Courtney Gidengil, Ateev Mehrotra 2015
Verified diagnosis could not be identified
Conditions identified by XUND:
  • Anal fissure

Always one step ahead.

In the study conducted by Ceney et al 2021, 9 symptom checkers were analyzed and compared regarding their medical performance. In this study the correct result was listed in the top five diagnoses in 51.0% of all cases and the mean number of questions to reach a disposition was 22.2. Using the dataset from the study, XUND identifies the correct condition in 91.11% of cases in the top 5 results and asks a mean number of 20.3 questions, outperforming all solutions in terms of accuracy and most in terms of process speed.

You want to know more? We have collected some of the most frequently asked questions for you.

Do you work together with medical doctors?

We have our own team of medical doctors who verify the quality of every single piece of information in the medical database based on reference literature and experience from the medical practice.

How do you ensure the quality of the medical content?

Our medical content is created and validated in cooperation with the Thieme Group, tailored to our offering.

Is all content created or reviewed by medical doctors?

Our technology is based on two pillars, one quantitative and one qualitative. Using AI, several million medical publications are analyzed and then reviewed again by our doctors with literature and practical experience. So it's the symbiosis of both worlds and our standardized quality assurance systems that make the difference.

What diseases do you cover?

Our AI can automatically analyze millions of medical publications and process data on over 4.000 medical conditions. However, in order to provide our users with statistically relevant and meaningful results, XUND prioritizes the most common medical conditions out of this dataset, that account for the vast majority of illness cases.

Step into the future of healthcare.