moncefem/clinical-trials-ai-2000-2025 huggingface dataset:
Evaluation Of Laser Versus Conventional Pulpotomies In Mature Molar Teeth With Irreversible Pulpitis (A Randomized Controlled Clinical Trial)
Trial ID: NCT07287709
Status: RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-11-07
Completion date: 2026-05
Sponsor: Rana Hegaz
Collaborators: Alexandria University
Conditions: Irreversible Pulpitis (Toothache)
Interventions: Diode laser; Sodium Hypochlorite Solution
Locations: Faculty of Dentistry
Countries: Egypt
Enrollment: 60
Age range: 16 Years - 50 Years
Sex: ALL

Summary:
this clinical trial is evaluating the outcome of laser assisted pulpotomy compared to conventional pulpotomy in mature teeth with symptomatic irreversible pulpitis (SIP) assessed by CBCT followed by automated segmentation using Artificial intelligence (AI).

Eligibility criteria:
Inclusion Criteria:

* Permanent molar teeth with symptomatic irreversible pulpitis.
* The patient should be ≥ 16 to 50 years old.
* Teeth should give positive response to cold testing and clinical diagnosis of SIP with or without periapical rarefaction.
* Teeth will be selected only if they are restorable.
* Patient medically healthy and free from systemic diseases. ASA I, II.
* patients who agreed to participate in the study to attend the control visits.
* Teeth with periapical index score (PAI) 1 and 2 will be selected

Exclusion Criteria:

* Teeth with necrotic pulp, resorption or subgingival caries.
* Teeth with open apices.
* Medically compromised patients.
* Pregnant patients.
* Patients with uncontrollable bleeding from the radicular pulp.
* Patients with (PAI) score 3-5 will be excluded from the study

Outcomes:
Assessment of healing progress; Radiographic assessment of the dentin bridge formation; Automated segmentation of the radicular pulp space
Improving Health Awareness Using Social Network Interventions
Trial ID: NCT04850287
Status: ACTIVE_NOT_RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2021-02-10
Completion date: 2026-06
Sponsor: University of California, Davis
Conditions: Health Knowledge, Attitudes, Practice
Interventions: Digital Sensors for Population Awareness about Health Issues using Social Media
Locations: UC Davis Medical Center
Countries: United States
Enrollment: 2000000
Age range: None - None
Sex: ALL

Summary:
The overarching hypothesis of our study is that social network interventions using artificial intelligence and social media can be used to increase population awareness about health issues. The overarching objective is to improve population awareness on multiple relevant health issues using social network interventions (SNI) and estimate the effect by conducting randomized control trials. Increase population awareness about organ donation in California, especially among minorities

Eligibility criteria:
Inclusion Criteria:

* Have a California zip code.
* Be a Facebook user

Outcomes:
Change the number of organ donor registration
Video Analysis and Artificial Intelligence for the Analysis of Upper Limb Movement in Children. Validation of a Technique in a Pediatric Population Aged 6 to 17 Years
Trial ID: NCT07147478
Status: NOT_YET_RECRUITING
Study type: OBSERVATIONAL
Start date: 2025-09
Completion date: 2026-12
Sponsor: Assistance Publique - Hôpitaux de Paris
Conditions: Clinical Examination of the Shoulder; Video-assisted Clinical Examination
Locations: Service de Chirurgie Orthopédique et Réparatrice de l'Enfant - Hôpital Armand Trousseau
Countries: France
Enrollment: 150
Age range: 6 Years - 17 Years
Sex: ALL

Summary:
The principle of the study is to compare the data obtained using a shoulder movement analysis software with those obtained during a traditional clinical examination, that is, using a goniometer and the modified Mallet classification

Eligibility criteria:
Inclusion Criteria:

* Age between 6 and 17 years old at the time of inclusion
* No neurological pathology
* No history of upper limb surgery
* No upper limb trauma above the hand in the 6 months preceding the examination
* Ability to stand for a minimum of 2 minutes
* Consent from the child, both parents, and/or legal representatives for participation in a filmed clinical examination.

Exclusion Criteria:

* Inability to understand the different movements requested.

Outcomes:
Comparison of a video-assisted clinical examination method with commonly used clinical practices
Older Adults' Attitudes Towards Stopping Aspirin
Trial ID: NCT07305376
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-11-10
Completion date: 2025-11-30
Sponsor: University of Michigan
Collaborators: University of Sydney
Conditions: Medication Overuse
Interventions: Additional harm information; Less information
Locations: University of Michigan
Countries: United States
Enrollment: 2819
Age range: 65 Years - None
Sex: ALL

Summary:
This online, survey-based experiment will include 2,400 adults who are 65 years and older (n=1,200 each from the United States and Australia). Each participant will be asked to share their opinions on a hypothetical patient scenario developed by our multidisciplinary team. This work is expected to significantly contribute to the understanding of how older adults make decisions about deprescribing medications. The long-term goal is to enhance communication between older adults and clinicians so that medication regimens are optimized and align with care preferences. These results will directly inform future research on the impact of communication choices in clinical practice.

Eligibility criteria:
Inclusion Criteria:

* Reside in Australia or the United States
* 65 years and older

Exclusion Criteria:

* Unable to read survey written in English

Outcomes:
"How safe do you think it would be to continue taking aspirin?" measured on a 6-point Likert scale; "How helpful do you think it would be to continue taking aspirin?" measured on a 6-point Likert scale
Development of Cardiovascular Risk Prediction Tools Based on Artificial Intelligence and Fundus Imaging Technology Study
Trial ID: NCT06181552
Status: UNKNOWN
Study type: OBSERVATIONAL
Start date: 2023-12
Completion date: 2025-06
Sponsor: China National Center for Cardiovascular Diseases
Collaborators: Beijing Tongren Hospital
Conditions: Cardiovascular Diseases
Interventions: fundus photograpgy; optical coherence tomography; optical coherence tomography angiography
Enrollment: 1072
Age range: 18 Years - None
Sex: ALL

Summary:
This study aims to develop a cardiovascular disease (CVD) screening tool and cardiovascular risk prediction tool based on fundus imaging data with the method of artificial intelligence.

Eligibility criteria:
Inclusion Criteria:

Three types of participants will be included, which are:

* Participants with established coronary heart disease, including previously diagnosed myocardial infarction, previous treatment with coronary intervention or coronary artery bypass grafting, coronary artery stenosis ≥50%, or chest pain with objective evidence of myocardial ischemia (myocardial ischemia indicated by stress electrocardiogram or stress imaging)
* Participants with established stroke.
* Participants without coronary heart disease or stroke, but are at high risk for CVD, defined as meeting at least two of the following:

  1. Men aged ≥ 60 years old, or women aged ≥ 65 years old;
  2. Diabetes;
  3. Total cholesterol\>5.2 mmol/L, or LDL-C\>3.4 mmol/L, or HDL-C\<1.0 mmol/L;
  4. Currently smoking, defined as daily smoking lasting for 1 year or more.

Exclusion Criteria:

* Participants unable to provide fundus imaging data required for the study due to the following reasons:

  1. Permanent blindness, blurred vision, flying mosquito disease, or refractive medium opacity seriously affecting fundus examination, such as severe cataracts, vitreous hemorrhage, etc.
  2. Macular edema, severe nonproliferative retinopathy in diabetes, proliferative vitreoretinopathy, radiation ophthalmopathy or retinal vein occlusion
  3. Eyeball enucleation, eye deformities, etc.
  4. Previous retinal laser therapy, injection therapy for any eye, or history of retinal surgery
  5. Photosensitivity, or taking medication that can cause photosensitivity, or currently undergoing photodynamic therapy
  6. Unable to cooperate with examination for collection of fundus imaging data
  7. Other situations that the participants fail to provide fundus imaging data required for the study
* Suffering from other serious diseases with an expected survival period of less than one year, such as advanced malignant tumors
* Unable to adhere to follow-up
* Other conditions which the researchers consider inappropriate for participants to enroll in the study

Outcomes:
Diagnosis of ASCVD at baseline; Major cardiovascular events
Prospective Validation of an Artificial Intelligence Tool for Pre-Anesthetic Assessment
Trial ID: NCT07290647
Status: NOT_YET_RECRUITING
Study type: OBSERVATIONAL
Start date: 2026-03-01
Completion date: 2028-06-30
Sponsor: Hospital Nossa Senhora da Conceicao
Conditions: Preoperative Care
Interventions: AI-based pre-anesthetic assessment; Anesthesiologist-led pre-anesthetic evaluation
Locations: Hospital Nossa Senhora da Conceição (Grupo Hospitalar Conceição)
Countries: Brazil
Enrollment: 270
Age range: 18 Years - None
Sex: ALL

Summary:
This prospective observational cohort study aims to validate an artificial intelligence (AI) tool designed for pre-anesthetic assessment in Portuguese, tailored to the Brazilian healthcare context. Conducted at a single tertiary hospital, the study will enroll 270 adult patients (aged \>18 years) scheduled for elective non-cardiac surgeries. Participants will use the AI tool to complete a self-assessment, generating general patient guidance and a detailed medical evaluation (the latter withheld from the anesthesiologist). A standard pre-anesthetic evaluation will then be performed by an anesthesiologist blinded to the AI results. A third blinded anesthesiologist will compare the assessments for accuracy, consistency, and risk identification (e.g., ASA classification and perioperative risk models). Primary outcome is concordance between AI and human assessments using Cohen's Kappa. Secondary outcomes include anesthesiologist perceptions of the tool's utility, impact on assessment quality, and patient usability challenges. The study poses minimal risks, with data collected over 24 months, and aims to enhance perioperative safety and efficiency in Brazil.

Eligibility criteria:
Inclusion Criteria:

* Patients aged 18 years or older
* Patients scheduled for elective non-cardiac surgeries

Exclusion Criteria:

* Patients undergoing diagnostic procedures with isolated sedation or local anesthesia
* If a patient undergoes more than one surgical intervention during the same hospitalization, only the major procedure will be considered (i.e., additional procedures during the same admission are not eligible for separate inclusion).

Outcomes:
Preoperative Risk Assessment
A Study on the Effect of Medical Students' Literature Reading Patterns on Cognitive Load and Academic Writing Ability
Trial ID: NCT07460258
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2026-01-20
Completion date: 2026-06-15
Sponsor: Zhongnan Hospital
Conditions: Accuracy in Understanding the Core Content of English Medical Literature
Interventions: [None]
Locations: Zhongnan Hospital of Wuhan University; Zhongnan Hospital of Wuhan University; Zhongnan Hospital
Countries: China; China; China
Enrollment: 160
Age range: None - None
Sex: ALL

Summary:
Compare the effects of three English medical literature reading modes (original text reading, bilingual comparison, full translation) on medical students' accuracy in literature comprehension, perceived cognitive load, mastery of professional terminology, and academic writing ability; assess whether reliance on artificial intelligence translation triggers a 'terminology shortage' phenomenon.

Eligibility criteria:
Inclusion Criteria:

* Students currently enrolled in our school's clinical medicine or related programs. Voluntarily participate and sign the informed consent form.

Exclusion Criteria:

* Native English speakers or those with a background in translation. Previously, they have read the specific literature selected for this study.

Outcomes:
Score for Objective Questions on Literature Comprehension
Detection of Reduced Left Ventricular Ejection Fraction and Atrial Arrhythmias With Single Lead ECG Using Artificial Intelligence
Trial ID: NCT05010655
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2021-06-01
Completion date: 2022-05-24
Sponsor: Eko Devices, Inc.
Conditions: Left Ventricular Dysfunction; Ventricular Dysfunction; Heart Diseases; Cardiovascular Diseases
Interventions: Use of Eko DUO Electronic Stethoscope
Locations: Prairie Cardiovascular Consultants; Prairie Cardiovascular Consultants
Countries: United States; United States
Enrollment: 1935
Age range: 18 Years - None
Sex: ALL

Summary:
The purpose of this research is to prospectively test and validate the single-lead Low EF algorithm in outpatients in order to test the performance of a single-lead ECG based algorithm to identify people with decreased left ventricular EF.

Eligibility criteria:
Inclusion Criteria:

* English-speaking adults who are 18 years and older
* Able and willing to provide informed consent
* Complete a clinical echocardiogram within 7 days before or after study procedures

Exclusion Criteria:

* Unwilling or unable to provide informed consent
* Patients who are hospitalized

Outcomes:
Single-lead ECG based algorithm development
Risk-Based Breast Screening (RIBBS) in Young Women: Personalized Imaging Protocols
Trial ID: NCT05675085
Status: UNKNOWN
Study type: INTERVENTIONAL
Phase: NA
Start date: 2020-01-20
Completion date: 2026-01-31
Sponsor: Istituto Oncologico Veneto IRCCS
Collaborators: Regione del Veneto (Italy)
Conditions: Breast Neoplasms
Interventions: Personalized screening protocol
Locations: Istituto Oncologico Veneto (IRCCS)
Countries: Italy
Enrollment: 10269
Age range: 45 Years - 45 Years
Sex: FEMALE

Summary:
The RIBBS study is a single-arm single-center study that aims to evaluate the effectiveness of a risk-based breast screening model using digital breast tomosynthesis (DBT) as the baseline test, quantitative individual breast density to guide supplemental ultrasound (US) imaging for dense breasts, and individual risk (calculated taking into account breast density) to guide the screening interval (annual or biennial).

Invited 45-year-old women are differentiated into five different screening protocols (based on breast density and risk), and screened according to a personalized model until they turn 50 and return to routine screening.

The only primary endpoint in this study is the cumulative incidence of advanced breast cancers (stage II and above). This endpoint will be evaluated at the end of the five-year intervention period and at 10 years.

The results of the personalized screening model will be compared with those obtained from an observational cohort from a neighboring region in which a "one-size-fits-all" approach involving annual mammography for women aged 45-49 years is used. The comparison will be conducted with the hypothesis of superiority of the personalized screening model.

Eligibility criteria:
Inclusion Criteria:

* Female
* Aged 45 years old
* Resident in the provinces of Padua and Rovigo (Italy)
* Willing and able to give written informed consent
* Willing and able to comply with scheduled visits, tests, and other procedures

Exclusion Criteria:

* Recent mammography
* Personal history of breast carcinoma, either invasive or ductal carcinoma in situ (DCIS)
* Known BRCA carrier or PALB2 or ≥50% risk
* Psychiatric or other disorders that are not compatible with compliance to the protocol requirements and follow-up
* Pregnant or breastfeeding
* Unable to give informed consent
* Current participation in another interventional breast screening trial

Outcomes:
Cumulative Incidence of Advanced Cancers
Development of Artificial Intelligence System for Detection and Diagnosis of Breast Lesion Using Mammography
Trial ID: NCT03708978
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2018-04-05
Completion date: 2020-05-04
Sponsor: Peking University Cancer Hospital & Institute
Collaborators: Peking University
Conditions: Women With Breast Cancer
Interventions: mammography
Locations: Beijing Cancer Hospital; Beijing Chao Yang Women and Children's Health Hospital; Beijing Da Xing People's Hospital; Beijing Hang Tian Centre Hospital; Beijing Nan Jiao Cancer Hospital; Beijing Shi Jing Shan Hospital; Beijing Shun Yi Qu Hospital; Beijing Shun Yi Woman and Children Health Hospital
Countries: China; China; China; China; China; China; China; China
Enrollment: 5809
Age range: 18 Years - None
Sex: FEMALE

Summary:
This project aims to establish a comprehensive artificial intelligence system for detecting and qualitative diagnosing breast lesions. Mammary images will be used to construct a diagnosis method based on deep learning. The system is proposed to automatically analyze the type of mammary glands, automatically identify and mark all breast lesions on the mammography images, provide the malignancy probability judgment of the lesions, the BI-RADS classification and the clinical suggestion, and also automatically generate the structured diagnosis report.

Eligibility criteria:
Inclusion Criteria:

* the X-ray images of the breast were complete
* the results of pathological diagnosis or more than 2 years of mammography follow-up were available
* subject signs informed consent(this item was only for prospective study cases)

Exclusion Criteria:

* there exists pathological diagnosis of breast lesions when receiving mammography
* there lacks pathological diagnosis or 2 years of mammography follow-up
* subject withdraws(this item was only for prospective study cases)

Outcomes:
benign-malignant diagnosis accuracy; benign-malignant diagnosis accuracy
A Study to Develop, Evaluate, and Validate a Tool to Infer/Predict an Estimated Microbiome Profile
Trial ID: NCT05847543
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2023-03-21
Completion date: 2024-12-22
Sponsor: Danone Asia Pacific Holdings Pte, Ltd.
Collaborators: KK Women's and Children's Hospital; National University Hospital, Singapore; University of Malaya; Thammasat University Hospital; Mount Elizabeth Medical Centre
Conditions: Healthy
Interventions: Stool diaper data and sample collection
Locations: University Malaya Medical Center; Mount Elizabeth Medical Centre; KK Women's and Children's Hospital; Thammasat University Hospital
Countries: Malaysia; Singapore; Singapore; Thailand
Enrollment: 440
Age range: 0 Months - 18 Months
Sex: ALL

Summary:
This is a study to collect data to build, evaluate and validate (test) a tool to infer/predict an estimated microbiome (community of microorganisms such as bacteria, fungi and viruses that exists in a particular environment) profile. The study will take place at several hospitals/clinics across Singapore, Malaysia, and Thailand.

Eligibility criteria:
Inclusion Criteria:

1. Children aged from 0 to 18 months old
2. Parent(s) should have access to the internet and a smartphone or tablet to upload stool data and complete the study questionnaires in the OneBiome web-platform.
3. Parent(s) should be able to comprehend the content of the study and to complete the study procedures in English.
4. Written consent from parent.

Exclusion Criteria:

1. Parent(s) incapable of completing the study questionnaires and uploading of the stool data using smart phone or tablet with internet.
2. Children born before gestational age 37 weeks.
3. Any other family member is enrolled in the study
4. Incapability of parents of children to comply with study protocol or Investigator's uncertainty about the willingness or ability of the parents of children to comply with the protocol requirements.

Outcomes:
To collect stool data and stool samples for full microbiome analysis. To collect stool images, stool data and stool samples for full microbiome analysis
Ependymomics: Multiomic Approach to Radioresistance of Ependymomas in Children and Adolescents
Trial ID: NCT05151718
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2021-09-30
Completion date: 2025-09-30
Sponsor: Institut Claudius Regaud
Collaborators: Institut National de la Santé Et de la Recherche Médicale, France; Centre Leon Berard; Assistance Publique Hopitaux De Marseille; Centre Hospitalier St Anne; Institut Pasteur
Conditions: Ependymoma of Brain; Pediatric Solid Tumor
Locations: Institut Claudius Regaud
Countries: France
Enrollment: 370
Age range: None - 25 Years
Sex: ALL

Summary:
Treatment of childhood ependymoma, the second most frequent pediatric brain tumor, is based on surgery and radiation therapy. However, 50% relapse, mainly locally. Progress in imaging, molecular biology and radiotherapy ballistics has led us to propose the EPENDYMOMICS project, a multi-omics approach using artificial intelligence to detect the predictive characteristics of relapse, and to define innovative radiotherapy targets using multimodal imaging. We previously reported that the relapse sites are mainly located in the high-dose radiotherapy zone and that there appear to be prognostic factors for relapse based on anatomical and functional MRI abnormalities by diffusion and perfusion. In addition, recent studies in molecular biology have identified significant prognostic factors. The challenge now is to use and correlate all these findings in larger cohorts to tackle the radio-resistance of this disease.

Our objective is to collate in a single database called NETSPARE (Network to Structure and Share Pediatric data to Accelerate Research on Ependymoma) the clinical, histological, biological, imaging and radiotherapy data from two consecutive studies that included 370 children and adolescents with ependymoma since 2000 in France. The EPENDYMOMICS project will comprise a clinical research team, three imaging research teams, two histopathology teams, and a biostatistics team working on NETSPARE. Our goal is to obtain a radiogenomic signature of our data, which will be validated with the English external cohort of 200 patients that is currently being analyzed. The perspective is to optimize the indications and volumes of irradiation that could in the future be used in a European translational research trial to tackle radioresistance.

Eligibility criteria:
Inclusion Criteria:

* children with intracranial ependymoma
* treated
* included in PEPPI study, pediaRT or in SIOP II Ependymoma french program

Exclusion Criteria:

* NA

Outcomes:
Definition of radiogenomics signatures that are predictive of patient outcome