moncefem/clinical-trials-ai-2000-2025 huggingface dataset:
Validation of an Artificial Intelligence-based Biliopancreatic EUS Navigation System for Real-time Quality Improvement: A Prospective, Single-center, Randomized Controlled Trial
Trial ID: NCT05457101
Status: UNKNOWN
Study type: INTERVENTIONAL
Phase: NA
Start date: 2022-07-01
Completion date: 2023-07-30
Sponsor: Renmin Hospital of Wuhan University
Conditions: Endoscopic Ultrasonography; Pancreatic Disease; Bile Duct Diseases; Artificial Intelligence
Interventions: AI-based biliopancreatic EUS navigation system
Locations: Renmin Hospital of Wuhan University
Countries: China
Enrollment: 264
Age range: 18 Years - None
Sex: ALL

Summary:
Endoscopic ultrasonography (EUS) is a key procedure for diagnosing biliopancreatic diseases. However, the performance among EUS endoscopists varies greatly and leads to blind areas during operation, which impaired the health outcome of patients. We previously developed an artificial intelligence (AI) device that accurately identifies EUS standard stations and significantly reduces the difficulty of ultrasound image interpretation. In this study, we updated the device (named EUS-IREAD) and assessed its performance in improving the quality of EUS examination in a single-center randomized controlled trial.

Eligibility criteria:
Inclusion Criteria:

1. Male or female aged 18 or above;
2. Patients able to give informed consent were eligible to participate.
3. Able and willing to comply with all study process.
4. history of previous biliopancreatic disease
5. Biliopancreatic lesions suspected due to clinical symptoms and/or radiological findings and/or laboratory findings
6. Patients at high risk of pancreatic cancer : Known genetic mutations associated with pancreatic cancer risk (BRCA2, BRCA1, PALB2, ATM, CDKNA/p16); Familial pancreatic ductal adenocarcinoma without known germline mutation; Peutz-Jeghers syndrome (STK11); Lynch syndrome (MLH1/MSH2/MSH6, EPCAM, PMS2); Familial adenomatous polyposis (APC). etc.

Exclusion Criteria:

1. Has participated in other clinical trials, signed informed consent and was in the follow-up period of other clinical trials.
2. Has participated in clinical trials of the drug and is in the elution period of the experimental drug or control drug.
3. patients with absolute contraindications to EUS examination;
4. Drug or alcohol abuse or psychological disorder in the last 5 years.
5. Patients in pregnancy or lactation.
6. bleeding diathesis or thrombocytopenia
7. history of previous digestive surgery.
8. severe medical illness
9. upper GI tract obstruction
10. previous medical history of allergic reaction to anesthetics
11. anatomical abnormalities of the upper gastrointestinal tract due to advanced neoplasia
12. Researchers believe that the patient is not suitable to participate in the trial.

Outcomes:
Missed scanning rate of standard stations in the experimental group and control group
Patient Perceived Degree of Empathy Exhibited by Physician Guided, Prompt Engineered, Generative AI Chatbot Designed for Atrial Fibrillation Education
Trial ID: NCT06684457
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2024-11-25
Completion date: 2025-05-02
Sponsor: University of Pittsburgh
Conditions: Atrial Fibrillation (AF)
Interventions: Atrial Fibrillation Education
Locations: UPMC Heart and Vascular Institute
Countries: United States
Enrollment: 40
Age range: 18 Years - None
Sex: ALL

Summary:
Atrial Fibrillation is a chronic disease with significant health consequences like increased risk of stroke, heart failure, heart attack and death. Educating patients about the disease is important for them to be able to understand the condition better, feel empowered and take an active part in their care plan. AI technology can potentially be used to impart such education. However, doing so with care and empathy is equally important.

Therefore, it is necessary to ensure when AI technology is used to impart education about atrial fibrillation to patients, the humane aspects of the interaction are rigorously tested. This study examines a way to impart atrial fibrillation education through interaction with an AI chatbot, that uses text and links to educational videos. To participate in this study, people need to be age 18 or older and have a history of newly diagnosed atrial fibrillation. Approximately 40 individuals will be asked to take part in this study.

The first step to the study will be reading through, understanding, and signing an informed consent. People who then agree to join the study will have a one-time interaction with the AI chatbot and structured educational material by using an iPad provided to them for the approximately 1 hour duration of the study. People in the study will obtain atrial fibrillation education by typing one by one on the iPad, up to 10 questions about the disease. Answers will include text and links to videos. Before and after atrial fibrillation education, people who join this study will be asked to fill out a survey. The study team will teach patients how to use the iPad and type in questions.

Eligibility criteria:
Inclusion criteria:

* Age greater than18 yrs
* Known diagnosis of atrial fibrillation

Exclusion criteria:

* Inability to text/use an electronic device
* Inability to read English

Outcomes:
Empathy
An Open-label, Single-blinded, Randomized, 2-way Crossover, Performance Study of the EyeMirage (Test Device) Relative to Standard of Care (Reference Device) in Patients Undergoing Standard Eye Examinations for Various Conditions
Trial ID: NCT06908967
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-06-13
Completion date: 2026-02-24
Sponsor: Neuroptek Corporation Inc.
Collaborators: St. Boniface Hospital; St. Boniface Hospital Asper Clinical Research Institute
Conditions: Visual Function
Interventions: EyeMirage device
Locations: St. Boniface Eye Care Centre; Brain, Vision and Concussion Clinic; Prairie Eye Care (Northgate); Armstrong + Small Eye Care Centre
Countries: Canada; Canada; Canada; Canada
Enrollment: 160
Age range: 18 Years - 65 Years
Sex: ALL

Summary:
This study will assess the effectiveness and accuracy of results of a new device for eye function testing. This will be done by comparing results of four eye tests that are done through the current standard used in eye clinics and that of this new device. Participants of this study will undergo the four eye tests using both the new device and the standard of care devices.

The study will be done in one visit to the eye clinic. Thirty days after the eye tests were done, participants will be called by the clinic for a general follow-up and to discuss any problems, if needed.

Eligibility criteria:
Inclusion Criteria:

* Evidence of a signed and dated informed consent document confirming that the participant has been informed of all aspects of the clinical study.
* Male or female participants, 18 to 65 years of age at time of screening.
* Visual acuity of 20/200 or better.
* Willingness to comply with required screening procedures, eye assessments, and follow-up visits, if needed.

Exclusion Criteria:

* Visual acuity worse than 20/200 in either eye
* Complete blindness or diffuse vision loss in either eye
* Clinical diagnosis of cognitive and motor diseases including but not limited to the following:

  1. Neurodegenerative diseases such as dementia-like Alzheimer's disease, posterior cortical atrophy
  2. Movement disorders such as Parkinson's disease and Parkinsonism tremors
  3. Multiple sclerosis, stroke or any other neurological or physical conditions with paresis or plegia (i.e. weakness or paralysis of the limbs)
* Eyes with a spherical equivalent of greater than +9 or -9 diopters where the corrective lens is too large to fit in the headset.

Outcomes:
Accuracy and Reliability of EyeMirage Test Results from Four Elements of Visual Testing in Comparison to Current Standard of Care
Applying Artificial Intelligence to Identify Subphenotypes of Acute Kidney Injury in Mexican Patients With Severe COVID-19
Trial ID: NCT06471101
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2024-06-18
Completion date: 2024-06-18
Sponsor: Instituto Nacional de Enfermedades Respiratorias
Conditions: COVID-19; Acute Kidney Injury
Interventions: clusters
Locations: Instituto Nacional de Enfermedades Respiratorias
Countries: Mexico
Enrollment: 2934
Age range: 15 Years - None
Sex: ALL

Summary:
The goal of this observational study was to identify subphenotypes of acute kidney injury patients with COVID-19, and the investigators analyzed their impact on mortality. The study included demographic and clinical variables of the participants. The implementation of Machine Learning algorithms and Artificial Intelligence methods are used, and some specific implementations were designed for the analysis, where each group was characterized by traditional statistical methods.

Eligibility criteria:
Inclusion Criteria:

* Patients older than 15 years old, hospitalized, and with severe acute respiratory syndrome (SARS-CoV-2) positive confirmation.

Exclusion Criteria:

* Patients who did not have at least 1 creatinine measurement.

Outcomes:
Subphenotypes of acute kidney injury in patients
Model Construction for AI-assisted Teaching
Trial ID: NCT06942130
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2024-10-01
Completion date: 2024-11-02
Sponsor: Hospital of Stomatology, Wuhan University
Conditions: Medical Education
Interventions: Artificial intelligence; Video
Locations: School & Hospital of Stomatology, Wuhan University
Countries: China
Enrollment: 192
Age range: None - None
Sex: ALL

Summary:
Clinical procedural skills training is a cornerstone of preclinical education for dental students. While technological aids such as virtual reality and simulators are increasingly integrated into training, direct instructor guidance remains fundamental to skill development. Artificial intelligence（AI）， as an emerging technology, is now gradually being adopted in medical education. This medical education trial, aimed at evaluating the potential of artificial intelligence in dental education, seeks to address two key questions: 1) Can AI assistance enhance the skill performance of dental students? 2) How can AI be effectively integrated into modern medical education? Researchers will compare the effects of AI and video-based instruction on skill acquisition, assessing differences in skill performance outcomes. Participants will engage in skill acquisition using either AI or video-based instruction over a one-week period.

Eligibility criteria:
Inclusion Criteria:

* They must have completed courses in endodontics, periodontology, prosthodontics, and oral and maxillofacial surgery; participants should have little to no prior training in the skills related to the experiment; and they must voluntarily agree to participate in the study and sign an informed consent form.

Exclusion Criteria:

* Participants will be excluded if they meet any of the following criteria: failure in final exams of the four courses (endodontics, periodontology, prosthodontics, and oral and maxillofacial surgery); transfer to another major, suspension, or withdrawal from the current academic year; refusal to join the study or withdrawal midway; failure to meet the calibration standards in the 9-point eye-tracking calibration; use of OpenAI-related software or applications in the control group; or failure to complete the skill test.

Outcomes:
Operational test scores; spatial ability; cognitive load
Scenario-Driven Virtual Reality Game for Dementia Education Among Healthcare Students: Protocol for a Four-Arm Study
Trial ID: NCT07238439
Status: ENROLLING_BY_INVITATION
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-09-01
Completion date: 2026-06-30
Sponsor: Universitas Airlangga
Collaborators: Chiba University; Tokyo University
Conditions: Dementia
Interventions: VR-Experienced + ASA VR Group; VR-Experienced + Standard Control Group; VR-Unexposed + ASA VR Group; VR-Unexposed + Standard Control Group
Locations: Universitas Airlangga
Countries: Indonesia
Enrollment: 200
Age range: None - None
Sex: ALL

Summary:
•Terminology Clarification: In the previous study (NCT06629844), the term ' virtual reality (VR)' referred to a 360-degree video viewed through a VR headset. This format offered an immersive experience but was non-interactive. In contrast, the current study uses an 'ASA VR' intervention, which is a scenario-driven, interactive virtual reality simulation. Participants take part in role-playing with an artificial intelligence (AI) character representing a person living with dementia. This distinction is crucial for understanding the study design and results, as the cognitive and experiential demands of the two formats differ greatly.

•Brief Summary: This nested 2x2 factorial quasi-experimental design study focuses on Indonesian nursing students and aims to examine the effectiveness of scenario-driven virtual reality (VR) dementia educational programs. The study uses a four-arm design to evaluate different combinations of interventions.

The study addresses the following research questions:

What is the effect of a Scenario-Driven VR dementia education program on improving participants' attitude, knowledge, intention to help people living with dementia, ageist attitudes, and participant satisfaction with the Scenario-Driven VR dementia education program?

Participants will voluntarily join a 30-minute class education program, with each participant attending only once. The program, integrated into the faculty's dementia-related courses, will be structured around a series of components, including an introduction, Scenario-Driven VR, a post-program questionnaire, and a conclusion.

Eligibility criteria:
Inclusion Criteria:

* Registered nursing students at Universitas Airlangga in the designated semester and courses (academic year 2025/2026).
* Provide informed consent.

Exclusion Criteria:

* Not enrolled in the specified semester/courses.
* Prior participation in a scenario-driven VR dementia education program similar to ASA VR that could influence outcomes.

Outcomes:
Primary Outcome Measure: Attitudes Toward People with Dementia Scale
The Development of an Artificial Intelligence Platform for Screening and Referral of Cognitive Dysfunction
Trial ID: NCT04236375
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2020-09-01
Completion date: 2025-07-30
Sponsor: Sun Yat-sen University
Conditions: Eye Movement Disorder; Cognitive Dysfunction
Locations: Zhongshan Ophthalmic Center
Countries: China
Enrollment: 1539
Age range: 45 Years - None
Sex: ALL

Summary:
There is association between eye movement disorder and cognitive dysfunction. Therefore, utilizing eye movement and screening for cognitive dysfunction is feasible. In the present study, the investigators will develop an artificial intelligence platform to screening for cognitive dysfunction by inspecting the function of eye movement. Futher more, based on the screening results, the platform will offer referral suggestions.

Eligibility criteria:
Inclusion Criteria:

* ①Subjects who are diagnosed as mild cognitive decline, Alzheimer's disease, Vascular dementia, Lewy body dementia, Frontotemporal dementia, other dementia and normal by neurologist.
* ②Subjects who can cooperate with the inspection.
* ③Subjects who agree to participate in the study and sign the consent form

Exclusion Criteria:

* ①Subjects who cannot do the inspection.
* ②Subjects who suffer from diseases that compromise the inspection.

Outcomes:
Area under the curve
Multinational Clinical Trial of Real-time Artificial Intelligence System (CadAI-B) for Breast Ultrasound: Prospective Clinical Validation Study
Trial ID: NCT06622967
Status: ACTIVE_NOT_RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2024-09-15
Completion date: 2024-12-31
Sponsor: JeeYeon Lee
Collaborators: Kyungpook National University Chilgok Hospital; BeamWorks Inc.
Conditions: Breast Neoplasm; Female
Interventions: CadAI-B
Locations: Kyungpook National University Chilgok Hospital
Countries: South Korea
Enrollment: 100
Age range: 20 Years - None
Sex: FEMALE

Summary:
The CadAI-B (Computer Aided Design Artificial Intelligence-Breast) system is a real-time AI diagnostic tool for breast ultrasound. It integrates with ultrasound devices to detect suspicious lesions, providing size, BI-RADS, and malignancy probability. After installation and user training, the system displays real-time breast conditions and automatically analyzes lesions when a freeze frame is set, showing results in seconds. This study will assess CadAI-B\&#39;s accuracy and reliability by comparing its findings with biopsy results.

Eligibility criteria:
Inclusion Criteria:

* Women aged 20 years or older
* Individuals scheduled to undergo breast ultrasound for diagnostic evaluation
* Patients whose Ground Truth can be determined through biopsy, surgery, or follow-up

Exclusion Criteria:

* Images containing artifacts that may affect the interpretation
* Presence of breast implants
* Significant breast trauma or mastitis at the time of the breast ultrasound that could cause distortion in image interpretation
* History of surgery or chemotherapy

Outcomes:
Lesion and Per-patient Diagnostic Performance
Design and Validation of an Artificial Intelligence System to Detect the Quality of Colon Cleansing Before Colonoscopy
Trial ID: NCT05553977
Status: UNKNOWN
Study type: OBSERVATIONAL
Start date: 2022-10-01
Completion date: 2023-05-30
Sponsor: Hospital Universitario de Canarias
Conditions: Cleansing Quality of the Colon
Interventions: Bowel preparation for colonoscopy; Colonoscopy
Locations: Department of Gastroenterology
Countries: Spain
Enrollment: 667
Age range: 18 Years - None
Sex: ALL

Summary:
The main purpose of the study is to design and validate a convolutional neural network (CNN) with the ability to discriminate between pictures of effluents with different qualities of bowel cleansing and in a second time to prospectively assess in a cohort of patients the agreement between the result of the last rectal effluent quality assessed by the CNN and the cleansing quality assessed during the colonoscopy assessed by a validated scale (Boston Bowel Preparation Scale, BBPS). Patients will be prepared with polyethylene glycol (PEG), PEG plus ascorbic acid (PEG-Asc) or sodium picosulfate-oxide magnesium solution (PS).

Eligibility criteria:
Inclusion Criteria:

* Age \>18, to sign the informed consent,
* Patients with indication of outpatient colonoscopy
* Patients ingesting the bowel preparation

Exclusion Criteria:

* Incomplete colonoscopy (except for poor bowel preparation)
* Contraindication for colonoscopy
* Allergies.
* Refusal to participate in the study or impairment to sign the informed consent.
* Colectomy (more than 1 segment)
* Dementia with difficulty in the intake of the preparation

Outcomes:
Effluent characteristics; Quality of bowel cleansing assessed by the Boston Bowel Preparation Scale
A Companion Trial in Silico: Computing Drug Response for Cancer Patients in Clinical Trials（PRincipal-001)
Trial ID: NCT05833802
Status: UNKNOWN
Study type: OBSERVATIONAL
Start date: 2023-02-15
Completion date: 2024-09-15
Sponsor: Peking University Cancer Hospital & Institute
Collaborators: Beijing Phil Rivers Technology
Conditions: Breast Cancer
Interventions: virtual anti-cancer drug
Locations: Shuhua Zhao
Countries: China
Enrollment: 25
Age range: 18 Years - 75 Years
Sex: ALL

Summary:
The goal of this observational study is to assess the performance of computational medicine technology in predicting patients response to anticancer drugs based on omics data.The main question it aims to answer is test consistency between the computing drug response and the response of real-world clinical trials. Participants will take part in silico.

Eligibility criteria:
Inclusion Criteria:

1. clinical diagnosis of triple-negative breast cancer
2. The subjects agreed to participate in the traditional clinical trial and signed informed consent.
3. The subjects agreed to participate in the virtual study and signed informed consent.

Exclusion Criteria:

1. Subjects do not meet the inclusion criteria of traditional clinical trial.
2. Subjects suffered from other cancer disease

Outcomes:
consistency
Study on Artificial Intelligence-Based Facial and Speech-Related Patterns in Parkinson's Disease and Their Digital Biomarkers
Trial ID: NCT07392411
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2023-07-25
Completion date: 2026-12-31
Sponsor: Beijing Tiantan Hospital
Conditions: Parkinson's Disease; Progressive Supranuclear Palsy(PSP); Multiple System Atrophy; Healthy Control
Interventions: video recording
Locations: 首都医科大学附属北京天坛医院
Countries: China
Enrollment: 720
Age range: 15 Years - 75 Years
Sex: ALL

Summary:
This research employs AI to analyze facial expressions and speech patterns, aiming to develop new digital tools for diagnosing and differentiating Parkinson's disease and similar disorders.

Eligibility criteria:
Inclusion Criteria:

1. Inclusion Criteria for Parkinson's Disease (PD) Group: (1) Diagnostic Criteria: Meet the diagnostic criteria for Parkinson's disease established by the Movement Disorder Society (MDS) in 2015. (2) Age Range: 18-75 years old. (3) Disease Severity: Early-stage PD: Hoehn-Yahr score ≤ 2.5 points. Mid-to-late-stage PD: Hoehn-Yahr score 2.5-5 points. (4) Consent for Data Collection: Willing to undergo facial expression video and speech audio recording. (5) Informed Consent: Signed informed consent form.
2. Inclusion Criteria for Parkinson's Plus Syndromes (MSA-P, PSP) Group: (1) Age Range: 18-75 years old. (2) Diagnostic Criteria: MSA patients must meet the diagnostic criteria established by the \[Chinese Expert Consensus on the Diagnosis of Multiple System Atrophy, 2017\]. PSP patients must meet the diagnostic criteria established by the \[Chinese Clinical Diagnostic Criteria for Progressive Supranuclear Palsy, 2016 Edition\]. (3) Consent for Data Collection: Willing to undergo facial expression video and speech audio recording. (4) Informed Consent: Signed informed consent form.

Exclusion Criteria:

1. History of cerebrovascular disease, head trauma, hydrocephalus, brain tumors, or intracranial surgery.
2. Presence of metal implants, cardiac pacemakers, or other metallic foreign bodies (applies to PD patients).
3. Severe dyskinesia in PD patients that would compromise cooperation with video/audio recording.
4. Mini-Mental State Examination (MMSE) score ≤ 24 points.

Outcomes:
Diagnostic Accuracy of the AI Model in Assessing [ Disease/Condition ] Severity
Artificial Intelligence-Enhanced Three-Dimensional Reconstruction of Combined Horizontal and Vertical Ridge Deficiencies Using Allogenic Dentin Block Versus Shell Tooth Graft Combined With Simultaneous Implant Placement
Trial ID: NCT06693921
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2024-11-17
Completion date: 2025-11-30
Sponsor: Kafrelsheikh University
Conditions: Bone Loss
Interventions: AI/guided block graft; AI/guided shell graft
Locations: Kafrelsheikh University; Walid Elamrousy
Countries: Egypt; Egypt
Enrollment: 22
Age range: 18 Years - 45 Years
Sex: ALL

Summary:
n the current study, AI-assisted 3D ridge augmentation of combined vertical and horizontal deficient ridges utilizing allogenic dentin block versus allogenic dentin shell graft will be assessed.

Eligibility criteria:
Inclusion Criteria:

* Insufficient vertical and horizontal bone contour for dental implant placement in the maxillary esthetic zone.

  * Volunteer for participating alveolar bone augmentation by allo-dentin graft technique.
  * Absence of any complicating systemic condition that may contraindicate surgical procedures.
  * Adequate oral hygiene.

Exclusion Criteria:

* Uncontrolled systematic disorders

  * diabetes mellitus
  * uncontrolled periodontal disease
  * history of head and neck radiotherapy
  * pregnancy
  * noncompliant patients
  * uncooperative individuals
  * those unable to attend the study follow-up appointments

Outcomes:
Horizontal buccolingual ridge width