moncefem/clinical-trials-ai-2000-2025 huggingface dataset:
Accuracy of Artificial Intelligence-Assisted Staging and Grading for Diagnosis of Periodontitis: A Cross-Sectional Study
Trial ID: NCT07113327
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2024-07-01
Completion date: 2025-06-01
Sponsor: Ain Shams University
Conditions: Periodontitis
Interventions: Artificial Intelligence-Assisted Staging and Grading for Diagnosis of Periodontitis
Locations: Ain Shams University
Countries: Egypt
Enrollment: 47
Age range: 18 Years - None
Sex: ALL

Summary:
This observational study aims to develop and assess the accuracy, specificity, and sensitivity of a deep learning model for the classification of periodontitis using panoramic radiographs and clinical data inputs. A total of 341 panoramic images will be retrospectively collected and labeled by experienced periodontists to train and test the model. The model will be evaluated for its ability to determine the stage and grade of periodontitis based on the 2017 classification guidelines set by the American Academy of Periodontology. The results will be compared to those of clinical experts to validate the AI-assisted diagnostic system. This study is conducted at the Faculty of Dentistry, Ain Shams University, in fulfillment of a Master's degree in Periodontology.

Eligibility criteria:
Inclusion Criteria:

* patients with periodontitis causing radiographic bone loss

Exclusion Criteria:

* x-ray images with

  1. Mixed dentition
  2. Orthodontic brackets
  3. Images with artifacts and distortion

Outcomes:
Establishment of an AI model for calculating periodontal bone loss (%) and assigning stage and grade of periodontitis using 2017 classification
Mobile Health and Oral Testing to Optimize Tuberculosis Contact Tracing in Colombia
Trial ID: NCT06338462
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2024-03-28
Completion date: 2024-09-11
Sponsor: Yale University
Collaborators: National Institute of Allergy and Infectious Diseases (NIAID)
Conditions: Tuberculosis
Interventions: Chatbot; Oral testing
Locations: Centro Internacional de Entrenamiento e Investigaciones Medicas (CIDIEM)
Countries: Colombia
Enrollment: 269
Age range: None - None
Sex: ALL

Summary:
The overall objective of this Aim is to design and iteratively adapt a home-based, mHealth- and oral testing facilitated strategy for implementing tuberculosis (TB) contact tracing in Cali, Colombia. Investigators will employ an iterative, community-engaged, participatory co-design process to optimize the feasibility, acceptability, usability, and appropriateness of the mobile health (mHealth) and oral testing strategy, in preparation for a future, appropriately powered implementation-effectiveness trial.

This protocol includes the baseline contact tracing protocol and the procedures for determining adaptations to the mHealth strategy (i.e., nominal group technique).

Eligibility criteria:
Inclusion Criteria:

For index persons with TB:

* assigned by the SoPH to receive contact investigation services from the study community health worker
* may be of any age (represented by a parent or legal guardian for those age\<18)

For contacts of index persons with TB:

* include the index person's named household contacts, defined as those spending one or more days or nights within the past 3 months sleeping under the same roof as the index person;
* may be of any age (represented by a parent or legal guardian for those age\<18).

Exclusion Criteria:

For index persons with TB:

* who are living outside the city of Cali;
* who lack capacity to agree to testing.

For contacts of index persons with TB:

* who have already been diagnosed with and treated for active TB within the past two years;
* who lack capacity to agree to testing.

Outcomes:
Implementation of the mHealth Strategy to Assess Feasibility.; Oral Specimen Collection to Assess Feasibility.
Digital Techniques for Measuring Chronic Leg Ulcers in Peripheral Arterial Disease: Aspects of Measurement Precision and Evaluation of Wound Treatment
Trial ID: NCT06421961
Status: ENROLLING_BY_INVITATION
Study type: OBSERVATIONAL
Start date: 2024-08-15
Completion date: 2026-04-01
Sponsor: Sahlgrenska University Hospital
Conditions: Chronic Limb-Threatening Ischemia
Locations: Sahlgrenska University Hospital
Countries: Sweden
Enrollment: 223
Age range: 18 Years - None
Sex: ALL

Summary:
The purpose of the project is to investigate the agreement with Bland-Altman plots between an AI-supported automatic digital measurement method of wound area and depth and existing manual measurement methods in patients with arterial ulcers on the lower leg. The expectation is that the digital measurement tool can provide healthcare providers with better opportunities to objectively monitor and detect changes in the wound healing process in patients with peripheral arterial disease.

Eligibility criteria:
Inclusion Criteria:

* Adults with peripheral arterial disease.
* Arterial or arteriovenous ulcers on lower leg
* Age \<18

Exclusion Criteria:

* Adults with non-ischemic ulcers,
* Purely venous ulcers,
* Purely traumatic wounds,
* Wounds resulting from non-atherosclerotic chronic vascular conditions of the lower extremity (e.g.,vasculitis, Buerger disease, radiation arteritis),

Outcomes:
To assess the clinical agreement between two methods of measuring arterial wound size, we will utilize the Bland-Altman plot.; To assess the clinical agreement between two methods of measuring the depth of arterial wounds, we will utilize the Bland-Altman plot.
Computer-assisted Adenoma Detection Coloscopy With Endo-AID Artificial Intelligence System and Endocuff Versus Endocuff Assisted Colonoscopy: a Randomized Controlled Trial
Trial ID: NCT05141773
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2022-11-01
Completion date: 2023-04-30
Sponsor: Hospital Universitario de Canarias
Conditions: Adenoma Detection Rate
Interventions: Computed adenoma detection system (CADe) plus endocuff; Endocuff
Locations: Hospital Universitario de Canarias
Countries: Spain
Enrollment: 696
Age range: 18 Years - None
Sex: ALL

Summary:
The main purpose of the study to evaluate the usefulness of the Endo-AID artificial intelligence system combined with endocuff compared with endocuff in the detection of colorectal adenomas in consecutive patients for outpatient colonoscopy.

The secondary aims were:

* To evaluate the benefit of Endo-AID and endocuff in adenoma detection rate by comparing endoscopists with high and low adenoma detection rate.
* To evaluate serrated detection rate, advanced adenoma detection rate, adenoma detection rate according to the size (\<= 5mm, 6-9mm,\> = 10mm) and number of adenomas by colonoscopy. Stratification by location and morphology.

Eligibility criteria:
Inclusion Criteria:

* Age ≥ 18 years.
* Patients referred for outpatient colonoscopy

Exclusion Criteria:

* Colonic resection
* Taking anticoagulants or antiaggregants that contraindicate the performance of therapy
* Patients with a recent colonoscopy (\<6 months) of good quality (e.g. cited for endoscopic therapy)
* IBD
* Patients with incomplete colonoscopy
* Patients with inadequate preparation using the Boston Colonic Preparation Scale (BBPS). A cleaning quality of less than 2 points in any of the 3 colonic sections will be considered inadequate.
* Patients with polyposis syndromes

Outcomes:
Adenoma detection rate
Artificial Intelligence-based Health Information Management System and Key Technology Study of Early Screening and Hierarchical Diagnosis and Treatment of Pancreatic Cancer
Trial ID: NCT06638866
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2024-08-03
Completion date: 2030-12-31
Sponsor: Changhai Hospital
Collaborators: Yinzhou Hospital Affiliated to Medical School of Ningbo University; The Second Affiliated Hospital of Jiaxing University; Central Hospital of Lishui City; Jingning County People's Hospital; Alibaba DAMO Academy
Conditions: Pancreatic Cancer; Pancreatic Ductal Adenocarcinoma; Pancreatic Intraepithelial Neoplasias; Intraductal Papillary Mucinous Neoplasm; Mucinous Cystic Neoplasm
Interventions: PDAC; Pancreatic precursor lesions
Locations: Shanghai Changhai Hospital; Second Affiliated Hospital of Jiaxing University; Yinzhou Hospital Affiliated to Medical School of Ningbo University
Countries: China; China; China
Enrollment: 5000
Age range: 18 Years - None
Sex: ALL

Summary:
Pancreatic ductal adenocarcinoma (PDAC) remains a therapeutic challenge with 5-year survival rates of 13%, primarily attributable to advanced-stage diagnosis (AJCC Stage III/IV in \>80% of cases). This prospective, observational, multi-center study will evaluate the performance of an AI-powered opportunistic screening system utilizing non-contrast computed tomography (NCCT) acquired during routine clinical encounters or health check-ups. The proposed AI model will perform automated detection of pancreatic parenchymal abnormalities, including PDAC and precursor lesions (intraductal papillary mucinous neoplasms \[IPMN\], mucinous cystic neoplasms \[MCN\]). Algorithm-positive cases will be independently reviewed by two radiologists. Highly suspected individuals will undergo further diagnostic verification, including serological tests and multimodal imaging confirmation. Patients with confirmed positive diagnosis will receive multidisciplinary consultation and specialized treatment, whereas those with negative results will undergo at least one-year clinical follow-up. This study will quantitatively evaluate the AI system's performance, and aims to advance PDAC early detection, improve patient outcomes, and make it accessible in underserved populations.

Eligibility criteria:
Inclusion Criteria

1\. Individuals undergoing routine non-contrast chest and/or abdominal CT scans for non-pancreatic indications.

Exclusion Criteria

1. History of pancreatic cancer;
2. History of thoracic or abdominal surgery;
3. Acute pancreatitis within 6 months;
4. Patients referred for evaluation of suspected or confirmed pancreatic cancer.

Outcomes:
Detection rate of PDAC; Detection rate of high-risk precursor lesions; PPV; Recall rate
Development and Clinical Validation of an Embodied-Intelligence-Assisted Bronchoscopy Navigation and Diagnostic System: A Multicenter Prospective Study
Trial ID: NCT07230431
Status: NOT_YET_RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-11
Completion date: 2026-11
Sponsor: Chinese Medical Association
Collaborators: Nanjing University; Micro-Tech (Nanjing) Co., Ltd.
Conditions: Respiratory Failure (Pediatric Patients); Pneumonia
Interventions: Embodied-Intelligence-Assisted Bronchoscopy Navigation and Diagnostic System (EIBRONCH); Conventional Bronchoscopy (Standard of Care)
Enrollment: 100
Age range: 18 Years - None
Sex: ALL

Summary:
This study will evaluate an embodied-intelligence-assisted bronchoscopy navigation and diagnostic system for patients with severe pneumonia who require clinically indicated bronchoscopy. The system provides real-time visual cues and voice prompts to help physicians localize target lung segments and describe endobronchial findings; physicians remain fully responsible for all clinical decisions. The trial is designed as a prospective, multicenter, controlled study conducted at about ten hospitals in China, with an anticipated sample size of approximately 100 patients. The primary objective is to determine whether AI assistance improves diagnostic agreement compared with the reference assessment, while secondary objectives include navigation success (e.g., loss-of-path rate), procedure time, and complication rates. The results will provide evidence on the safety and effectiveness of AI-assisted bronchoscopy and support product validation and registration.

Eligibility criteria:
Inclusion Criteria:

1. Age ≥18 years.
2. Severe pneumonia requiring clinically indicated bronchoscopy for diagnosis and/or therapy, as determined by the treating team.
3. Written informed consent from the patient or a legally authorized representative.
4. Expected to tolerate bronchoscopy with current respiratory support (e.g., HFNC/NIV/IMV) per site protocol

Exclusion Criteria:

1. Standard contraindications to bronchoscopy, such as uncontrolled hypoxemia despite support (SpO2 \<90% for ≥30 s on FiO2 ≥0.60), hemodynamic instability requiring escalating vasopressors, or malignant arrhythmia not controlled.
2. Uncorrected coagulopathy likely to increase bleeding risk (e.g., platelets \<50×10\^9/L or INR \>1.5) per site policy.
3. Known pregnancy or breastfeeding if the investigator judges risk outweighs benefit according to site policy.
4. Participation in another interventional drug/device study that could interfere with outcomes.
5. Any condition that, in the investigator's judgment, makes participation unsuitable (e.g., emergent life-saving bronchoscopy without time for consent).

Outcomes:
Diagnostic agreement versus central adjudication
Artificial-intelligence-based QUAntification of Size measuremeNts of Adenoma in Routine Endoscopy
Trial ID: NCT06040710
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2024-02-14
Completion date: 2024-03-28
Sponsor: Wuerzburg University Hospital
Conditions: Colorectal Polyp; Colorectal Adenoma
Interventions: POSEIDON size estimation software with the EndoMind polyp detection system
Locations: Universitätsklinikum Würzburg
Countries: Germany
Enrollment: 145
Age range: 18 Years - None
Sex: ALL

Summary:
Polyp size and count determines the follow-up intervals after colonoscopy. However, relying on the endoscopist's optical diagnosis for size estimation has shown considerable variability, leading to erroneous surveillance intervals and increased colorectal cancer risk. This study aims to assess the effectiveness of a new polyp size estimation software, called POSEIDON, which uses the tip of the auxiliary water-jet as reference and is implemented together with the EndoMind polyp detection system.

Eligibility criteria:
Inclusion Criteria:

* Adult patients
* Scheduled for colonoscopy

Exclusion Criteria:

Patient Level:

* Inflammatory Bowel Disease
* Familiar Polyposis Syndrome

Data Level

* Failure to initialize system before examination
* Missing image instrument placed next to polyp to obtain gold standard

Outcomes:
Error of size estimation for colorectal polyps using POSEIDON versus physician optical evaluation
Generating Personalized Stories With Artificial Intelligence for Pediatric Kidney Recipients
Trial ID: NCT07532382
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2026-03-01
Completion date: 2026-12-01
Sponsor: Paris Translational Research Center for Organ Transplantation
Conditions: Kidney Transplant
Interventions: AI-generated story; AI generated story
Locations: Necker hospital
Countries: France
Enrollment: 100
Age range: 5 Years - 12 Years
Sex: ALL

Summary:
Pediatric kidney transplant recipients often face major psychosocial challenges that are difficult to address with existing tools. This study evaluates whether clinically supervised AI can generate personalized, age-adapted therapeutic stories for these children and their families.

Eligibility criteria:
Inclusion Criteria:

* Age 5-12 years inclusive at enrolment.
* Recipient of a kidney transplant.
* Clinically stable at enrolment (no active rejection, acute infection, or current hospitalization for a graft-related complication).
* Fluency in French or English.
* Written informed consent from parent(s)/legal guardian(s); child assent when age-appropriate.

Exclusion Criteria:

* Severe cognitive impairment precluding engagement with narrative content.
* Mental state not allowing participation.
* Family unwilling or unable to commit to the study timeline and interview requirements.

Outcomes:
Child and family experience of the story after delivery.; Child and family experience of the story after delivery.
Early DiAgnosis Real-Time Healthcare System for CANcer Trial
Trial ID: NCT05064124
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2024-07-18
Completion date: 2025-05
Sponsor: University College, London
Conditions: Polyps; Adenoma Colon; Colorectal Polyp; Colon Polyp; Polyps of Colon
Interventions: CADDIE - Computer Aided Detection and Diagnosis for Intelligent Endoscopy
Locations: University College London Hospitals NHS Foundation Trust
Countries: United Kingdom
Enrollment: 420
Age range: 18 Years - None
Sex: ALL

Summary:
The purpose of the study is to assess whether the AI characterisation system of the CADDIE device improves the endoscopists accuracy in the optical diagnosis of diminutive colorectal polyps in the bowel during colonoscopy. Participants will either have a colonoscopy with the assistance of the CADDIE device characterisation AI system ("intervention group") or have a colonoscopy in line with routine clinical practice i.e., without the CADDIE device characterisation AI system ("control group"). The randomisation method of this trial will allocate enrolled participants to the "intervention" group and to the "control" group by a technique similar to flipping a coin.

Eligibility criteria:
Inclusion Criteria:

* Participants scheduled to undergo a screening, surveillance or symptomatic colonoscopy with an endoscopist participating in the study phase of the trial.
* Male and female participants aged 18 years or older at the time of informed consent.
* Participants able to comprehend, sign and date the written informed consent document to participate in the study.

Exclusion Criteria:

* Emergency and/or inpatient colonoscopies
* Participants with inflammatory bowel disease (IBD)
* Participants with current Colorectal Cancer (CRC)
* Participants with a contraindication for biopsy or polypectomy. These include:

  * Participants who have not withheld medications pre-disposing to bleeding at time of colonoscopy as per local site /national guidelines.
  * Participants with a history of haemostasis disorders (haemostasis disorders will include but will not be limited to: participants with haemophilia or other congenitally acquired clotting factor deficiencies, participants with cirrhosis with coagulopathy, participants known to have thrombocytopenia (\<80,000 platelet/ul) and individuals with Von Willebrand's disease or other known platelet malfunction disorders)
* Participant is enrolled in another research study with an investigational medicinal product (IMP) or non-IMP that pre-disposes them to bleeding

Outcomes:
The primary objective of this study is to evaluate whether the CADDIE system improves endoscopists accuracy in the optical diagnosis of diminutive colorectal polyps (≤5mm).
Multiparametric Assessment of Residual Congestion at Discharge in Patients With Acute Heart Failure
Trial ID: NCT06993220
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2025-01-01
Completion date: 2027-01-01
Sponsor: Consorci Sanitari Integral
Conditions: Acute Heart Failure (AHF); Congestive Heart Failure(CHF)
Interventions: Evaluation of residual congestion at discharge
Locations: Complex Hospitalari Universitari Moisès Broggi
Countries: Spain
Enrollment: 500
Age range: 18 Years - None
Sex: ALL

Summary:
Treatment of congestion is one of the main goals in patients hospitalized for acute heart failure. Nevertheless, current evidence shows that decongestion is often not achieved and that residual congestion at discharge is strongly associated with poor outcomes. While this association has been demonstrated, previous studies have primarily focused on single parameters of congestion (physical examination, biomarkers, or imaging features). The aim of the study is to assess residual congestion at discharge using a multiparametric approach and to compare the prognostic value of each evaluation strategy. Additionally, the analysis will be supported by artificial intelligence to develop a multiparametric prognostic algorithm that can provide an improved predictive model compared to standard statistical approaches.

Eligibility criteria:
Inclusion Criteria:

* Age ≥ 18 years.
* Patients hospitalized for new onset heart failure or worsening heart failure defined by:

  1. Symptoms classified as New York Heart Association class III or IV.
  2. Clinical or instrumental signs of volume overload (e.g., dyspnea with evidence of pulmonary congestion on X-rays or lung ultrasound, pitting edema, and jugular venous distension).
  3. Elevated NT-proBNP levels within the first 24 hours of admission (cutoff values: 450 ng/L for patients \< 50 years; \>900 ng/L for patients aged 50-75 years; \>1800 ng/L for patients \>75 years).
* Ability to provide informed consent.

Exclusion Criteria:

* Known diagnosis of septicemia.
* Glomerular filtration rate \< 15 ml/min.
* Life expectancy \< 6 months.
* Active myocarditis.
* Heart transplant recipients.
* Patients with ventricular assist devices.
* Congenital heart diseases.
* Moderate-to-severe liver disease (Child-Pugh B-C).
* Patients that will not be followed up by the Heart Failure Unit.

Outcomes:
Worsening heart failure or cardiovascular death
Let's K-Talk: A Storytelling Intervention Leveraging Chatbot Technology to Prevent HPV and HPV Associated Cancers for Ethnic Koreans Living in the U.S.
Trial ID: NCT05884697
Status: ACTIVE_NOT_RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2023-05-10
Completion date: 2026-07-31
Sponsor: University of Cincinnati
Conditions: Human Papillomavirus Viruses; Papillomavirus Vaccines
Interventions: K-Talk Intervention (Storytelling and K-Bot); Storytelling Intervention; K-Bot Intervention; Written Information
Locations: Minjin Kim
Countries: United States
Enrollment: 120
Age range: 18 Years - 45 Years
Sex: ALL

Summary:
The goal of this clinical trial is to test the feasibility, acceptability, and preliminary efficacy of a storytelling video-based intervention using AI chatbot technology (K-Talk) to promote HPV vaccination behavior among Korean Americans aged 18 to 45.

The main questions this study aims to answer are:

* Is the K-Talk intervention feasible for use among Korean Americans aged 18 to 45?
* Is the K-Talk intervention acceptable to the target population?
* What is the preliminary efficacy of the K-Talk intervention in promoting HPV vaccination uptake?

Participants will be Korean Americans aged 18 to 45 who are at risk for HPV infection. Participants will be asked to complete a baseline survey and then will be "randomized" into one of four groups: Group 1 (chatbot + storytelling intervention), Group 2 (chatbot only), Group 3 (storytelling only), and Group 4 will be only exposed to written didactic HPV education materials. All groups will receive written didactic HPV education materials. Researchers will compare how Group 1, a combination of AI Chatbot and storytelling intervention is more effective than other intervention groups in promoting HPV vaccination uptake among underserved, hard-to-reach Korean Americans.

Eligibility criteria:
Inclusion Criteria:

1. Identify as a Korean ethnic person
2. Reside in the U.S.
3. between the ages of 18 and 45
4. be able to speak or read English
5. not have been vaccinated against HPV
6. use a mobile device.

Exclusion Criteria:

1. Participants who do not identify as a Korean ethnic person
2. Participants who do not reside in the U.S.
3. Participants who are not between the ages of 18 and 45.
4. Participants who cannot speak or read English.
5. Participants who have been vaccinated against HPV.
6. Participants who do not use a mobile device.

Outcomes:
Number of participants who completed 3 doses of HPV vaccines at 12-months; Number of participants who completed 3 doses of HPV vaccines at 6-months; Number of participants who received at least one dose of HPV vaccine at 3-month; Number of participants who received at least one dose of HPV vaccine at 6-month; Number of participants who received at least one dose of HPV vaccine at 12-month