PeriodontitisNCT05926999
Conversational AI Models in Periodontitis Classification
An observational study of Periodontitis, run by Necmettin Erbakan University at 1 site in Turkey (Türkiye).
Trial summary
The goal of this observational study is to test periodontitis classification ability of ChatCPT. The main questions it aims to answer are: question 1: Could ChatCPT classify periodontitis? question 2: Is there a better result if ChatCPT is trained for perodontitis classification? Read more about this study
- Who is it for?
- Ages 18 to 65 years
- Conditions the study is for
- Periodontitis
- How many people
- 62 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 25 Jun 2023to 30 Jul 2023
- How long will I take part?
- 1 Month
- Phase
- Observational
- Are there results?
- None posted in the registry
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 to 65 years
- All sexes
- Adult, Older adult
Study population: Periodontitis
Who may be able to join
- The cases whose clinical, photographic, and radiological records are excellent quality and have good diagnostic sensitivity.
Who cannot join
- Acute periodontal lesions
- gingival diseases
- the presence of dental implants
- periodontitis as a manifestation of systemic diseases were considered as exclusion criteria.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Using ChatGPT to Determine the Stage and Degree of Periodontontitis
The goal of this observational study is to test periodontitis classification ability of ChatCPT. The main questions it aims to answer are:
question 1: Could ChatCPT classify periodontitis? question 2: Is there a better result if ChatCPT is trained for perodontitis classification?
Read the detailed description
The descriptive pilot research will be based on an analysis of the baseline digital record and subsequent stage, extent, and grade characterization of 75 untreated patients diagnosed with periodontitis. All cases will be evaluated by 4 examiners and the obtained standardized diagnosis for each case. The information will be used to determine the stage, grade, and extent of 75 periodontitis cases will be copied directly for each case as input to a large AI model called ChatGPT (https://chat.openai.com/), followed by query: "What is the stage, grade, and extent of periodontitis?" The received replies will be compared to standardized diagnosis.
2.2 Ethical Considerations From December 2022 to May 2023, baseline clinical and radiographic documentation of periodontitis patients were collected in the context of regular visits at the Necmettin Erbakan University Periodontology Clinic. In the study, anonymized data will be used. All participants have given their agreement in writing for the data to be used for training and research. This study will adhere to the 2013 revision of the 1975 Declaration of Helsinki and will be authorized by the Necmettin Erbakan University Faculty of Dentistry Ethics Committee for Non-Pharmac eutical and Medical Device Clinical Research.
2.3.Selection and preparation of the documentation of the periodontitis cases Using randomization software, a database of 150 patients receiving periodontal therapy will be used for selecting 85 cases of periodontitis from the archive of patients of the periodontology department at Necmettin Erbakan University. Acute periodontal lesions, gingival diseases, the presence of dental implants, and periodontitis as a manifestation of systemic diseases will be considered as exclusion criteria.
The case description included a comprehensive summary of the patient's medical and dental history, intra-oral photographs, a panoramic radiograph, a complete set of periapical radiographs, and periodontal charting that encompassed various clinical measures related to periodontal health. These measures will be plaque scores (visually assessed after the use of a revealing solution, as present or absent), probing depth, bleeding on probing, clinical attachment loss (CAL), furcation involvement (Hamp, Nyman, \& Lindhe, 1975) and tooth mobility (Miller, 1985). The medical history will be also supplied, including details regarding pertinent medical issues including glycemic management and cigarette usage. The clinical, photographic, and radiological records for the 85 patients that will be chosen will be of excellent quality and good diagnostic sensitivity.
The whole documentation of the periodontitis instances will be compiled into four presentation files. They will be presented in different orders in all four presentations for four expert evaluations. The first presentation is provided 2.4 Experts' Evaluation Four experienced periodontists who work as full-time faculty members (Z.T.E, O.B, D.O.S, and F.U.Y.) will evaluate the cases in the first phase utilizing the prepared presentations. The four experts had gone over the consensus reports for the 2018 periodontal classification (Papapanou et al., 2018; Tonetti, Greenwell, \& Kornman, 2018) multiple times and had been using it to make clinical diagnoses for at least 4 years. These diagnoses will be considered standardized diagnoses and served as the reference for each respective case. The cases that did not achieve a consistent diagnosis among the experts will be excluded from the study.
2.5 Staging, grading, and determining extent of periodontitis cases using ChatCPT
ChatGPT is an implementation of the Generative Pre-Training Transformer 3 (GPT-3) language model developed by OpenAI, which is publicly accessible and freely available for use. (Brown et al., 2020). GPT-3 is a highly expansive neural network-based natural language processing (NLP) model, currently one of the largest in existence. With training on 175 billion parameters, its primary purpose is to generate text that closely resembles human language. Acting as a versatile chatbot, GPT-3 is capable of performing diverse NLP tasks such as language translation, summarization, and question-answering (Balas \& Ing, 2023). Among its many possible uses, we will evaluate the performance of GPT-3 in stage, grade, and extent determination of periodontitis using case descriptions. its ability to stage, grade, and determine extent when given case descriptions of periodontitis. Since ChatCPT is a language model and cannot use images, the radiographs of the cases will be evaluated by the four experts. Bone loss amounts and bone loss rates will be measured and turned into numerical data that ChatCPT could use. Standardized texts containing the information that should be used to determine the stage, grade, and extent of each case will be created. This information is as stated below.
For staging;
- Age and gender;
- Maximum clinical attachment loss in the interproximal area
- The percentage of bone loss;
- Number of tooth loss due to periodontal reasons;
- Maximum probing depth;
- The bone loss type;
- Furcation involvement (FI) according to the Hamp classification (Hamp et al., 1975)
- the presence of chewing dysfunction;
- 2nd-degree and above-tooth mobility;
- The presence of ridge defect;
- Number of teeth in occlusion; For determining the extent; Periodontitis coverage; For Grading;
- The amount of bone loss in the last 5 years; b. The age ratio of the percentage of bone loss in the worst area; c. Phenotype of destruction: d. Smokin status and number of cigarettes smoked per day; e. Diabetic status and HbA1c level below or above. For this study, a new account will be created, granting access to ChatGPT through the link provided (https://chat.openai.com/chat). The standardized texts for each case will be written in English, and then the question "What stage, grade, and extent is the periodontitis?" will be asked to ChatGPT. The same current version of the ChatGPT program will be used in the query, and the query process will be done in two ways.
- To minimize the impact of prior responses, a new chat window will be opened for each question asked, and the responses will be recorded for later analysis.
- A new chat window will be opened and the basic information needed to determine the stage, grade, and extent of periodontitis according to the 2018 classification will be transmitted to ChatCPT. ChatCPT will be then asked to classify the cases to be forwarded later according to this information, and this request will be approved by ChatCPT. The same standardized texts for each case used in the first query will be transmitted to the ChatCPT, this time using the same chat window, and again "What stage, grade, and extent is the periodontitis?" question will be asked. The responses will be recorded for later analysis.
In 2 different inquiries from chatCPT, an answer will be obtained for the stage, grade and extent of periodontitis for each case. The stage, grade and extent responses obtained for each case will be compared with the standardized diagnosis created by the experts.
- Conditions
- Periodontitis
- Keywords
- classification, periodontitis, Artificial intelligence, Language processing, diagnosis, periodontal diseases
- Medical subject headings
- Periodontitis, Disease, Periodontal Diseases
What is being measured
The primary outcome is the main question the study is designed to answer.
Classficiation ability of ChatCPT
The primary result will the comparison of results obtained from two different queries in the ChatCPT with the standardized diagnosis.
Measured: 1 month
Secondary outcomes (1)
Comparison of stage, grade and extent in ChatCPT's answers and standard diagnosis
In ChatCPT's answers, stage, grade and extent will be compared with compliance with the standard diagnosis. Thus, it will be evaluated that ChatGPT is more successful in guessing which of them correctly.
Measured: 1 month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Jul 2023
- Study start25 Jun 2023
- Primary completion20 Jul 2023
- Study completion30 Jul 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for PeriodontitisStudies of the same condition, open and under way.
- 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
- Observational
- Observational model
- Case only
- Time perspective
- Cross-sectional
- Enrolment
- 62 participants (actual)
- Target duration
- 1 Month
Sponsor and investigators
- Lead sponsor
- Necmettin Erbakan University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Zeynep Tastan Eroglu, Necmettin Erbakan University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05926999
- Sponsor's protocol ID
- NEUandChatCPT
- Status last verified
- Aug 2023
- First submitted
- 6 Jun 2023
- Last updated
- 15 Aug 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Hamp SE, Nyman S, Lindhe J. Periodontal treatment of multirooted teeth. Results after 5 years. J Clin Periodontol. 1975 Aug;2(3):126-35. doi: 10.1111/j.1600-051x.1975.tb01734.x.
PubMed 1058213Miller PD Jr. A classification of marginal tissue recession. Int J Periodontics Restorative Dent. 1985;5(2):8-13. No abstract available.
PubMed 3858267Papapanou PN, Sanz M, Buduneli N, Dietrich T, Feres M, Fine DH, Flemmig TF, Garcia R, Giannobile WV, Graziani F, Greenwell H, Herrera D, Kao RT, Kebschull M, Kinane DF, Kirkwood KL, Kocher T, Kornman KS, Kumar PS, Loos BG, Machtei E, Meng H, Mombelli A, Needleman I, Offenbacher S, Seymour GJ, Teles R, Tonetti MS. Periodontitis: Consensus report of workgroup 2 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. J Periodontol. 2018 Jun;89 Suppl 1:S173-S182. doi: 10.1002/JPER.17-0721.
PubMed 29926951Tonetti MS, Greenwell H, Kornman KS. Staging and grading of periodontitis: Framework and proposal of a new classification and case definition. J Periodontol. 2018 Jun;89 Suppl 1:S159-S172. doi: 10.1002/JPER.18-0006.
PubMed 29926952Tastan Eroglu Z, Babayigit O, Ozkan Sen D, Ucan Yarkac F. Performance of ChatGPT in classifying periodontitis according to the 2018 classification of periodontal diseases. Clin Oral Investig. 2024 Jun 29;28(7):407. doi: 10.1007/s00784-024-05799-9.
PubMed 38951256
Study at a glance
From the registry record, last updated by the sponsor on 15 Aug 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Using ChatGPT to Determine the Stage and Degree of Periodontontitis
- ClinicalTrials.gov ID
- NCT05926999
- Acronym / sponsor ID
- NEUandChatCPT
- Conditions
- Periodontitis
- Keywords
- classification, periodontitis, Artificial intelligence, Language processing, diagnosis, periodontal diseases
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 62 participants (actual)
- Lead sponsor
- Necmettin Erbakan UniversityUniversity, hospital or other
- Study start
- 25 Jun 2023 (actual)
- Primary completion
- 20 Jul 2023 (actual)
- Study completion
- 30 Jul 2023 (actual)
- First posted
- 3 Jul 2023 (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.
The goal of this observational study is to test periodontitis classification ability of ChatCPT. The main questions it aims to answer are:
question 1: Could ChatCPT classify periodontitis? question 2: Is there a better result if ChatCPT is trained for perodontitis classification?
Detailed description
The descriptive pilot research will be based on an analysis of the baseline digital record and subsequent stage, extent, and grade characterization of 75 untreated patients diagnosed with periodontitis. All cases will be evaluated by 4 examiners and the obtained standardized diagnosis for each case. The information will be used to determine the stage, grade, and extent of 75 periodontitis cases will be copied directly for each case as input to a large AI model called ChatGPT (https://chat.openai.com/), followed by query: "What is the stage, grade, and extent of periodontitis?" The received replies will be compared to standardized diagnosis.
2.2 Ethical Considerations From December 2022 to May 2023, baseline clinical and radiographic documentation of periodontitis patients were collected in the context of regular visits at the Necmettin Erbakan University Periodontology Clinic. In the study, anonymized data will be used. All participants have given their agreement in writing for the data to be used for training and research. This study will adhere to the 2013 revision of the 1975 Declaration of Helsinki and will be authorized by the Necmettin Erbakan University Faculty of Dentistry Ethics Committee for Non-Pharmac eutical and Medical Device Clinical Research.
2.3.Selection and preparation of the documentation of the periodontitis cases Using randomization software, a database of 150 patients receiving periodontal therapy will be used for selecting 85 cases of periodontitis from the archive of patients of the periodontology department at Necmettin Erbakan University. Acute periodontal lesions, gingival diseases, the presence of dental implants, and periodontitis as a manifestation of systemic diseases will be considered as exclusion criteria.
The case description included a comprehensive summary of the patient's medical and dental history, intra-oral photographs, a panoramic radiograph, a complete set of periapical radiographs, and periodontal charting that encompassed various clinical measures related to periodontal health. These measures will be plaque scores (visually assessed after the use of a revealing solution, as present or absent), probing depth, bleeding on probing, clinical attachment loss (CAL), furcation involvement (Hamp, Nyman, \& Lindhe, 1975) and tooth mobility (Miller, 1985). The medical history will be also supplied, including details regarding pertinent medical issues including glycemic management and cigarette usage. The clinical, photographic, and radiological records for the 85 patients that will be chosen will be of excellent quality and good diagnostic sensitivity.
The whole documentation of the periodontitis instances will be compiled into four presentation files. They will be presented in different orders in all four presentations for four expert evaluations. The first presentation is provided 2.4 Experts' Evaluation Four experienced periodontists who work as full-time faculty members (Z.T.E, O.B, D.O.S, and F.U.Y.) will evaluate the cases in the first phase utilizing the prepared presentations. The four experts had gone over the consensus reports for the 2018 periodontal classification (Papapanou et al., 2018; Tonetti, Greenwell, \& Kornman, 2018) multiple times and had been using it to make clinical diagnoses for at least 4 years. These diagnoses will be considered standardized diagnoses and served as the reference for each respective case. The cases that did not achieve a consistent diagnosis among the experts will be excluded from the study.
2.5 Staging, grading, and determining extent of periodontitis cases using ChatCPT
ChatGPT is an implementation of the Generative Pre-Training Transformer 3 (GPT-3) language model developed by OpenAI, which is publicly accessible and freely available for use. (Brown et al., 2020). GPT-3 is a highly expansive neural network-based natural language processing (NLP) model, currently one of the largest in existence. With training on 175 billion parameters, its primary purpose is to generate text that closely resembles human language. Acting as a versatile chatbot, GPT-3 is capable of performing diverse NLP tasks such as language translation, summarization, and question-answering (Balas \& Ing, 2023). Among its many possible uses, we will evaluate the performance of GPT-3 in stage, grade, and extent determination of periodontitis using case descriptions. its ability to stage, grade, and determine extent when given case descriptions of periodontitis. Since ChatCPT is a language model and cannot use images, the radiographs of the cases will be evaluated by the four experts. Bone loss amounts and bone loss rates will be measured and turned into numerical data that ChatCPT could use. Standardized texts containing the information that should be used to determine the stage, grade, and extent of each case will be created. This information is as stated below.
For staging;
- Age and gender;
- Maximum clinical attachment loss in the interproximal area
- The percentage of bone loss;
- Number of tooth loss due to periodontal reasons;
- Maximum probing depth;
- The bone loss type;
- Furcation involvement (FI) according to the Hamp classification (Hamp et al., 1975)
- the presence of chewing dysfunction;
- 2nd-degree and above-tooth mobility;
- The presence of ridge defect;
- Number of teeth in occlusion; For determining the extent; Periodontitis coverage; For Grading;
- The amount of bone loss in the last 5 years; b. The age ratio of the percentage of bone loss in the worst area; c. Phenotype of destruction: d. Smokin status and number of cigarettes smoked per day; e. Diabetic status and HbA1c level below or above. For this study, a new account will be created, granting access to ChatGPT through the link provided (https://chat.openai.com/chat). The standardized texts for each case will be written in English, and then the question "What stage, grade, and extent is the periodontitis?" will be asked to ChatGPT. The same current version of the ChatGPT program will be used in the query, and the query process will be done in two ways.
- To minimize the impact of prior responses, a new chat window will be opened for each question asked, and the responses will be recorded for later analysis.
- A new chat window will be opened and the basic information needed to determine the stage, grade, and extent of periodontitis according to the 2018 classification will be transmitted to ChatCPT. ChatCPT will be then asked to classify the cases to be forwarded later according to this information, and this request will be approved by ChatCPT. The same standardized texts for each case used in the first query will be transmitted to the ChatCPT, this time using the same chat window, and again "What stage, grade, and extent is the periodontitis?" question will be asked. The responses will be recorded for later analysis.
In 2 different inquiries from chatCPT, an answer will be obtained for the stage, grade and extent of periodontitis for each case. The stage, grade and extent responses obtained for each case will be compared with the standardized diagnosis created by the experts.
Study design
- Observational model
- Case only
- Time perspective
- Cross-sectional
- Target follow-up
- 1 Month
Who may qualify
- Ages
- 18 to 65 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Periodontitis
Key inclusion criteria (1 listed)
- The cases whose clinical, photographic, and radiological records are excellent quality and have good diagnostic sensitivity.
Key exclusion criteria (4 listed)
- Acute periodontal lesions
- gingival diseases
- the presence of dental implants
- periodontitis as a manifestation of systemic diseases were considered as exclusion criteria.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Classficiation ability of ChatCPT
Time frame: 1 month
The primary result will the comparison of results obtained from two different queries in the ChatCPT with the standardized diagnosis.
1 secondary outcome
Comparison of stage, grade and extent in ChatCPT's answers and standard diagnosis
Time frame: 1 month
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Aug 2023.
- Results publication: PubMed 1058213Hamp SE, Nyman S, Lindhe J. Periodontal treatment of multirooted teeth. Results after 5 years. J Clin Periodontol. 1975 Aug;2(3):126-35. doi: 10.1111/j.1600-051x.1975.tb01734.x.
- Results publication: PubMed 3858267Miller PD Jr. A classification of marginal tissue recession. Int J Periodontics Restorative Dent. 1985;5(2):8-13. No abstract available.
- Results publication: PubMed 29926951Papapanou PN, Sanz M, Buduneli N, Dietrich T, Feres M, Fine DH, Flemmig TF, Garcia R, Giannobile WV, Graziani F, Greenwell H, Herrera D, Kao RT, Kebschull M, Kinane DF, Kirkwood KL, Kocher T, Kornman KS, Kumar PS, Loos BG, Machtei E, Meng H, Mombelli A, Needleman I, Offenbacher S, Seymour GJ, Teles R, Tonetti MS. Periodontitis: Consensus report of workgroup 2 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. J Periodontol. 2018 Jun;89 Suppl 1:S173-S182. doi: 10.1002/JPER.17-0721.
- Results publication: PubMed 29926952Tonetti MS, Greenwell H, Kornman KS. Staging and grading of periodontitis: Framework and proposal of a new classification and case definition. J Periodontol. 2018 Jun;89 Suppl 1:S159-S172. doi: 10.1002/JPER.18-0006.
- Derived from this study: PubMed 38951256Tastan Eroglu Z, Babayigit O, Ozkan Sen D, Ucan Yarkac F. Performance of ChatGPT in classifying periodontitis according to the 2018 classification of periodontal diseases. Clin Oral Investig. 2024 Jun 29;28(7):407. doi: 10.1007/s00784-024-05799-9.
- Brown T, Mann B, Ryder N, et al. Language models are few-shot learners. Advances in neural information processing systems 2020;33:1877-1901.Link provided by the sponsor.
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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. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Periodontitis, run by Necmettin Erbakan University at 1 site in Turkey (Türkiye).
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 1 inclusion and 4 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: finished, as of the sponsor's last update on 15 Aug 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Turkey (Türkiye). 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Classficiation ability of ChatCPT (time frame: 1 month). 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 NCT05926999, which also lists 5 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 15 Aug 2023.