Skin CancerAI-DSSCNCT06932172
Artificial Intelligent Decision Support for Skin Cancer Diagnostics in Primary Care
A study testing Artificial inteligence based decision support to detect skin cancer in people with Skin Cancer, run by Linkoeping University at 8 sites in Sweden.
Trial summary
Background: Artificial intelligence has in numerous studies shown high accuracy in detecting skin cancer when trained on various databases of dermatoscopic images. However, there are very few prospective studies conducted in real clinical settings directed at patients seeking healthcare for assessment of skin lesions… Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Skin Cancer
- What is being tested?
- Artificial inteligence based decision support to detect skin cancer
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 3,000 participants
- Where
- 8 sitesSweden
- Study dates
- 4 Nov 2025to 31 Dec 2031
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Patients attending a primary care facility in order to have one or more skin lesions checked for skin cancer, or patients presenting with one or more skin lesions raising suspicion of skin cancer when noticed by the primary care physician.
- Willingness and ability to provide informed consent.
Who cannot join
- Individuals with skin type V and VI according to the Fitzpatrick's scale (darker brown or black coloured skin)
Trial locations and contacts
8 sites in 1 country. Contact the study team or a site near you to ask about taking part.
8 sites in 1 country
Sweden8 sites, 8 recruiting
- Recruiting
Finspång Primary Healthcare Centre
Finspång, Docent, 61230
Moa Lundgren, M.D., +4610105 92 60, Moa.lundgren@regionostergotland.se
Magnus O Falk, M.D., Ph.D., Professor
- Recruiting
Valla Primary Healthcare Centre
Linköping, Docent, 58213
Magnus Falk, M.D., Ph.D., Professor, +46708106176, magnus.falk@liu.se
Magnus O Falk, M.D., Ph.D., Professor
- Recruiting
Kärna Primary Care Centre
Linköping, Docent, 58662
Magnus Falk, M.D., Ph.D., Professor, +46708106176, magnus.falk@liu.se
Magnus O Falk, M.D., Ph.D., Professor
- Recruiting
Ekholmen Primary Healthcare Centre
Linköping, 589 29
My Söderholm, M.D., +46768551533, my.soderholm@liu.se
Magnus O Falk, M.D., Ph.D., Professor
- Recruiting
Mjölby Primary Care Centre
Mjölby, Docent, 59530
Emil Kristensen, M.D., +4610-105 99 10, Emil.Kristensson@regionostergotland.se
Magnus O Falk, M.D., Ph.D., Professor
- Recruiting
Vikbolandet Primary Care Centre
Norrköping, Docent, 61024
John Berglund, M.D., +46101059280, John.berglund@regionostergotland.se
Magnus O Falk, M.D., Ph.D., Professor
- Recruiting
Åby Primary Healthcare Centre
Norrköping, Docent, 61330
Hanna Skytt, M.D., +4610105 93 10, hanna.skytt@regionostergotland.se
Magnus O Falk, M.D., Ph.D., Professor
- Recruiting
Skärvet Primary Healthcare Centre
Vaxjo, Docent, 35234
Jon Pallon, M.D., Ph.D., +4647058 97 50, jon.pallon@kronoberg.se
Jon O Pallon, M.D., Ph.D.
About this study
Official title: Artificial Intelligent Decision Support for Skin Cancer Diagnostics in Primary Care - a Multicentre Randomized Controlled Trial.
Background: Artificial intelligence has in numerous studies shown high accuracy in detecting skin cancer when trained on various databases of dermatoscopic images. However, there are very few prospective studies conducted in real clinical settings directed at patients seeking healthcare for assessment of skin lesions, and nosuch studies at all in primary care, where the majority of patients are managed.
Project aim: To study the accuracy, reliability, and clinical utility of an AI-based decision support system (Dermalyser), developed for primary care, in distinguishing skin cancer from benign lesions.
Read more
Method: Cluster-randomized controlled trial at approx. 30 primary care centers in Sweden, Germany, Scotland, the Netherlands and Australia. At study start, the participating primary care centres in each country are equally randomised to either be enabled to use the Dermalyser (intervention phase) or to assess patients according to the standard clinical procedure (control phase). When half of the intended sample size (i.e. 1500 of 3000 participants) have been included, the primary care centres switch phase from intervention to control, or vice versa. During the intervention phase, the physicians may use (if found indicated) Dermalyser as a part of their clinical evaluation, whereas during the control phase the physicians follow their ordinary diagnostic routine without support from Dermalyser. This will direct the participants to either an intervention or a control cohort. Both groups will be followed for up to 5 years, with regard to the tumour diagnoses, proportions of skin cancer/benign lesions, and morbidity and mortality in skin cancer. Possible between-group differences will be investigated statistically.
Potential benefits: If the Dermalyser prooves to be safe and diagnotically reliability, it could enhance the chance of detecting skin cancer in early stage in primary care, and to reduce the proportion of benign skin lesion unnecessarily excised or referred to dermatologist.
- Conditions
- Skin Cancer
- Being tested
- Artificial inteligence based decision support to detect skin cancer
- Keywords
- Artificial Intelligence (AI), Primary care, Diagnostics
- Medical subject headings
- Skin Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial inteligence based decision support to detect skin cancerDevice
When assessing skin lesions in patients seeking primary care, the primary care physician may use the device to be evaluated in the study (Dermalyser) as a complementary diagnostic doecision support to differentiate skin cancers from benign skin lesions. However, the decision on clinical management of the lesion remains with the physician.
| Study group | Role | What they receive |
|---|---|---|
| Possibility to use AI support | Experimental | The primary care physician may use the AI decision support (Dermalyser) in their assessment of skin lesions. Receives: Device: Artificial inteligence based decision support to detect skin cancer |
| Control | No intervention | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
Proportion of skin cancers
Proportion of skin cancers (melanoma, SCC or BCC) excised or referred to dermatologists, as described in percentage of total number of skin lesions included.
Measured: From enrollment until all included lesions have been diagnosed following standard clinical investigation procedure, which we consider in the normal case will not exceed 6 months from inclusion.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Apr 2025
- Study start4 Nov 2025
- Primary completion31 May 2027 (estimated)
- Study completion31 Dec 2031 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Skin CancerStudies of the same condition, open and under way.
- More trials run by Linkoeping UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Crossover
- Model description
- Cross-over cluster-randomized clinical trial
- Masking
- None (open label)
- Enrolment
- 3,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Linkoeping University
- Sponsor type
- Other government
- Collaborators
- Karolinska Institutet, Göteborg University, Region Östergötland
- Responsible party
- Principal investigator, Magnus Falk, Linkoeping University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06932172
- Sponsor's protocol ID
- CIV-23-03-042574
- Other IDs
- 2023-05996, 2023
- Acronym
- AI-DSSC
- Status last verified
- Jan 2026
- First submitted
- 9 Jan 2025
- Last updated
- 12 Jan 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: All IPD that underlie results in a publication.
Publications
Helenason J, Ekstrom C, Falk M, Papachristou P. Exploring the feasibility of an artificial intelligence based clinical decision support system for cutaneous melanoma detection in primary care - a mixed method study. Scand J Prim Health Care. 2024 Mar;42(1):51-60. doi: 10.1080/02813432.2023.2283190. Epub 2024 Feb 7.
PubMed 37982736Papachristou P, Soderholm M, Pallon J, Taloyan M, Polesie S, Paoli J, Anderson CD, Falk M. Evaluation of an artificial intelligence-based decision support for the detection of cutaneous melanoma in primary care: a prospective real-life clinical trial. Br J Dermatol. 2024 Jun 20;191(1):125-133. doi: 10.1093/bjd/ljae021.
PubMed 38234043
Study at a glance
From the registry record, last updated by the sponsor on 12 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligent Decision Support for Skin Cancer Diagnostics in Primary Care - a Multicentre Randomized Controlled Trial.
- ClinicalTrials.gov ID
- NCT06932172
- Acronym / sponsor ID
- AI-DSSC / CIV-23-03-042574
- Conditions
- Skin Cancer
- Keywords
- Artificial Intelligence (AI), Primary care, Diagnostics
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 3,000 participants (estimated)
- Lead sponsor
- Linkoeping UniversityOther government
- Collaborators
- Karolinska Institutet, Göteborg University, Region Östergötland
- Study start
- 4 Nov 2025 (actual)
- Primary completion
- 31 May 2027 (estimated)
- Study completion
- 31 Dec 2031 (estimated)
- First posted
- 17 Apr 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Background: Artificial intelligence has in numerous studies shown high accuracy in detecting skin cancer when trained on various databases of dermatoscopic images. However, there are very few prospective studies conducted in real clinical settings directed at patients seeking healthcare for assessment of skin lesions, and nosuch studies at all in primary care, where the majority of patients are managed.
Project aim: To study the accuracy, reliability, and clinical utility of an AI-based decision support system (Dermalyser), developed for primary care, in distinguishing skin cancer from benign lesions.
Method: Cluster-randomized controlled trial at approx. 30 primary care centers in Sweden, Germany, Scotland, the Netherlands and Australia. At study start, the participating primary care centres in each country are equally randomised to either be enabled to use the Dermalyser (intervention phase) or to assess patients according to the standard clinical procedure (control phase). When half of the intended sample size (i.e. 1500 of 3000 participants) have been included, the primary care centres switch phase from intervention to control, or vice versa. During the intervention phase, the physicians may use (if found indicated) Dermalyser as a part of their clinical evaluation, whereas during the control phase the physicians follow their ordinary diagnostic routine without support from Dermalyser. This will direct the participants to either an intervention or a control cohort. Both groups will be followed for up to 5 years, with regard to the tumour diagnoses, proportions of skin cancer/benign lesions, and morbidity and mortality in skin cancer. Possible between-group differences will be investigated statistically.
Potential benefits: If the Dermalyser prooves to be safe and diagnotically reliability, it could enhance the chance of detecting skin cancer in early stage in primary care, and to reduce the proportion of benign skin lesion unnecessarily excised or referred to dermatologist.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- Cross-over cluster-randomized clinical trial
| Arm | Type | Receives |
|---|---|---|
| Possibility to use AI support | Experimental | Device: Artificial inteligence based decision support to detect skin cancerThe primary care physician may use the AI decision support (Dermalyser) in their assessment of skin lesions. |
| Control | No intervention | – |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- Patients attending a primary care facility in order to have one or more skin lesions checked for skin cancer, or patients presenting with one or more skin lesions raising suspicion of skin cancer when noticed by the primary care physician.
- Willingness and ability to provide informed consent.
Key exclusion criteria (1 listed)
- Individuals with skin type V and VI according to the Fitzpatrick's scale (darker brown or black coloured skin)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial inteligence based decision support to detect skin cancerWhen assessing skin lesions in patients seeking primary care, the primary care physician may use the device to be evaluated in the study (Dermalyser) as a complementary diagnostic doecision support to differentiate skin cancers from benign skin lesions. However, the decision on clinical management of the lesion remains with the physician. | Device | Possibility to use AI support |
Primary outcome
Proportion of skin cancers
Time frame: From enrollment until all included lesions have been diagnosed following standard clinical investigation procedure, which we consider in the normal case will not exceed 6 months from inclusion.
Proportion of skin cancers (melanoma, SCC or BCC) excised or referred to dermatologists, as described in percentage of total number of skin lesions included.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Jan 2026.
- Background: PubMed 37982736Helenason J, Ekstrom C, Falk M, Papachristou P. Exploring the feasibility of an artificial intelligence based clinical decision support system for cutaneous melanoma detection in primary care - a mixed method study. Scand J Prim Health Care. 2024 Mar;42(1):51-60. doi: 10.1080/02813432.2023.2283190. Epub 2024 Feb 7.
- Background: PubMed 38234043Papachristou P, Soderholm M, Pallon J, Taloyan M, Polesie S, Paoli J, Anderson CD, Falk M. Evaluation of an artificial intelligence-based decision support for the detection of cutaneous melanoma in primary care: a prospective real-life clinical trial. Br J Dermatol. 2024 Jun 20;191(1):125-133. doi: 10.1093/bjd/ljae021.
- Individual participant dataSharing planned: Yes. All IPD that underlie results in a publication.
Related trials for Skin Cancer
RecruitingPhase 1/2
Study of INBRX-106 and INBRX-106 in Combination With Pembrolizumab (Keytruda®) in Subjects With Locally Advanced or Metastatic Solid Tumors (Hexavalent OX40 Agonist)
Solid Tumor, Non-Small Cell Lung Cancer
RecruitingPhase 1
IL-17 Blockade to Decrease irAEs (REPLAY)
Metastatic Melanoma
Active, not recruiting
Streamlined Geriatric and Oncological Evaluation Based On IC Technology
Breast Cancer, Comorbidities and Coexisting Conditions
RecruitingPhase 2
Gene Signatures to Guide HR+MBC Therapy in a Diverse Cohort
Invasive Mammary Carcinoma, Metastatic Breast Cancer
RecruitingPhase 3
A Study of Camrelizumab Plus Chemotherapy in Combination With or Without Famitinib as Neoadjuvant Therapy in Participants With Triple Negative Breast Cancer (BCTOP-T-N01)
TNBC - Triple-Negative Breast Cancer
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
8 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Artificial inteligence based decision support to detect skin cancer in people with Skin Cancer, run by Linkoeping University at 8 sites in Sweden.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 12 Jan 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 8 sites in Sweden. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Magnus Falk, Professor (+46708106176, magnus.falk@liu.se), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Proportion of skin cancers (time frame: From enrollment until all included lesions have been diagnosed following standard clinical investigation procedure, which we consider in the normal case will not exceed 6 months from inclusion.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06932172, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Jan 2026.