moncefem/clinical-trials-ai-2000-2025 huggingface dataset:
Investigation of the Relationship Between Nurses' Attitudes Toward Artificial Intelligence and Their Critical Thinking Dispositions
Trial ID: NCT07134374
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2025-08-20
Completion date: 2025-10-01
Sponsor: TC Erciyes University
Conditions: Nurses
Locations: Turkish Ministry of Health, Adana City Training and Research Hospital
Countries: Turkey (Türkiye)
Enrollment: 294
Age range: 18 Years - None
Sex: ALL

Summary:
The integration of artificial intelligence (AI) into healthcare is gaining momentum, particularly in areas such as diagnosis, treatment planning, and patient monitoring. While AI offers the promise of increased efficiency and support for evidence-based care, its success depends not only on technology but also on the attitudes and cognitive skills of healthcare professionals. Nurses, who are at the center of patient care, are expected to interact with AI systems. This may require nurses to adapt to new roles and develop critical thinking skills to interpret AI outputs correctly. Despite the growing importance of these factors, no study has examined the relationship between nurses' attitudes toward AI and their critical thinking tendencies. This study, conducted among nurses at Adana City Training and Research Hospital, aims to examine this relationship and contribute to educational and professional development strategies that support the safe and effective use of AI in nursing practice.

Eligibility criteria:
Inclusion Criteria:

* Nurses who are actively working in a university hospital,
* Have at least 6 months of professional experience, and
* Are willing to participate in the research.

Exclusion Criteria:

* Refusal to Participate: Nurses who declined to participate in the study or who did not wish to sign the informed consent form.
* On Leave: Nurses who are on leave, annual leave, maternity leave, or parental leave during the conduct of the study.
* Communication Barriers: Nurses with language barriers that significantly impair their ability to read and understand the questionnaire or who are known to have severe cognitive impairments.

Outcomes:
Attitude Toward Artificial Intelligence; Critical Thinking Disposition; The Relationship Between Attitude Toward Artificial Intelligence and Critical Thinking Disposition
Development and Validation of an Artificial Intelligence Platform for the Analysis of Sperm Samples and Prediction of Their Clinical Potential
Trial ID: NCT07456397
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2026-03-18
Completion date: 2028-02
Sponsor: Fecundis Lab SL
Conditions: Infertility (IVF Patients); ICSI; IVF Outcomes; Male Infertility; Reproductive Issues
Interventions: Swim-up; Density gradient centrifugation; HyperSperm
Locations: Eugin Barcelona; Fertty; CIRH; Fertilab Barcelona; Natuvitro
Countries: Spain; Spain; Spain; Spain; Spain
Enrollment: 500
Age range: 18 Years - 60 Years
Sex: ALL

Summary:
Prospective, multicenter research study with a split-sample design on semen samples, without intervention, to develop an artificial intelligence platform for the analysis of sperm samples and prediction of their clinical potential, in 500 semen samples, in an in vitro study over 24 months.

Eligibility criteria:
Male participants:

Inclusion Criteria:

* Ability to provide a semen sample via masturbation
* Semen sample intended for use in an IVF/ICSI cycle

Exclusion Criteria:

* Current diagnosis of a sexually transmitted infection (STI)
* Previous diagnosis of hepatitis A, B, C, D, or HIV
* Prior participation in this study
* Participation in a clinical trial involving an intervention within the last 3 months

Female participants:

Inclusion Criteria:

* Urdengoing an IVF/ICSI cycle with partner or donor semen

Exclusion Criteria:

* Prior participation in this study
* Participation in a clinical trial involving an intervention within the last 3 months

Outcomes:
Predictive performance of AI models for reproductive outcomes
A Volunteer Study to Collect Imaging Data for the Development of Identifying Probe Pressure as Part of ScanNav Assist Automated Dating Scan
Trial ID: NCT05963243
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2023-08-01
Completion date: 2024-01-12
Sponsor: IntelligentUltrasound Limited
Conditions: Ultrasound
Interventions: Ultrasound Scans
Locations: Hodge House
Countries: United Kingdom
Enrollment: 60
Age range: 18 Years - None
Sex: ALL

Summary:
The goal of this observational study is to collect data in the form of ultrasound recordings from healthy volunteers, to aid the development of an Artificial Intelligence model that can identify ultrasound probe pressure.

Eligibility criteria:
Inclusion Criteria:

1. Male or female, at least 18 years of age;
2. Able to comprehend and sign the Informed Consent prior to enrolment in the study.

Exclusion Criteria:

1. Aged \<18 years of age;
2. Unwilling or unable to provide informed consent.

Outcomes:
Ultrasound scan recordings
Assessing the Impact of an Artificial Intelligence-Based Model for Intracranial Aneurysm Detection in CT Angiography on Patients' Diagnosis and Outcomes: The IDEAL Study - A Web-Based Multicenter, Double-Blinded Randomized Controlled Trial
Trial ID: NCT06118840
Status: RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2024-05-20
Completion date: 2026-12
Sponsor: Jinling Hospital, China
Conditions: Intracranial Aneurysm; CT Angiography; Deep Learning; Double Bind Interaction
Interventions: True-AI-integrated intracranial aneurysms diagnosis strategy; Sham-AI-integrated intracranial aneurysms diagnosis strategy
Locations: The First Affiliated Hospital of University of Science and Technology of China; The First Affiliated Hospital of Wannan Medical College; Guizhou Provincial People's Hospital; First Affiliated Hospital of Zhengzhou University; Shiyan People's Hospital; Research Institute Of Medical Imaging Jinling Hospital; Affiliated Hospital of Xuzhou Medical University; The First Hospital of Jilin University; Shandong Provincial Hospital Affiliated to Shandong First Medical University; Yidu Central Hospital Affiliated to Shandong Second Medical University; The First Affiliated Hospital of Kunming Medical University; Hainan General Hospital; The First People's Hospital of Kashgar Region; University Second Hospital; First People's Hospital of Lianyungang; Ma'anshan People's Hospital; BenQ Medical Center, Affiliated BenQ Hospital of Medical School, Nanjing Medical University; Long Gang Central Hospital of Shenzhen; The Affiliated Suqian First Hospital of Nanjing Medical University; Tianjin Medical University General Hospital; General Hospital of Ningxia Medical University
Countries: China; China; China; China; China; China; China; China; China; China; China; China; China; China; China; China; China; China; China; China; China
Enrollment: 6450
Age range: 18 Years - None
Sex: ALL

Summary:
This study (IEDAL study) intends to prospectively enroll more than 6450 patients who will undergo head CT angiography (CTA) scanning in the outpatient clinic. It will be carried out in 21 hospitals in more than 10 provinces in China. The patient's head CTA images will be randomly assigned to the True-AI and Sham-AI group with a ratio of 1:1, and the patients and radiologists are unaware of the allocation. The primary outcomes are sensitivity and specificity of detecting intracranial aneurysms. The secondary outcomes focus on the prognosis and outcomes of the patients.

Eligibility criteria:
Inclusion Criteria:

* Adult inpatients and outpatients who are scheduled for head CTA scanning.

Exclusion Criteria:

* Age under 18 years.
* Patients with contraindications to CTA.
* Modified Rankin Scale (mRS) score \> 3.
* Refuse to sign informed consent.
* Participation in other clinical studies of intracranial aneurysms.
* Patients with failed head CTA scanning or incomplete image data, or poor image quality.

Outcomes:
To compare diagnostic sensitivity of intracrnial aneurysms between intervention and control arm.; To compare diagnostic specificity of intracrnial aneurysms between intervention and control arm.
Histopathological Analysis of Renal Biopsies With Dynamic Full-field Optical Coherence Tomography, a Comparison to Conventional Histopathological Findings for the Diagnosis of Either Acute Kidney Injury or Chronic Kidney Disease in Routine Practices
Trial ID: NCT05728216
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2022-11-01
Completion date: 2028-11-30
Sponsor: Centre Hospitalier William Morey - Chalon sur Saône
Collaborators: Centre Hospitalier Universitaire Dijon
Conditions: Acute Kidney Injury; Chronic Kidney Diseases; Tomography, Optical Coherence
Interventions: Dynamic full-field optical coherence tomography analysis of kidney biopsy
Locations: Centre Hospitalier William Morey - Chalon sur Saône
Countries: France
Enrollment: 50
Age range: 18 Years - None
Sex: ALL

Summary:
Kidney biopsy play a key role for the investigation of either acute kidney injury or chronic kidney disease. Despite possible complications due to the invasive nature of the biopsy, such procedure is still essential in a number of clinical situations to improve the diagnosis specificity of kidney disease, better inform about its prognosis and guide the management of a future treatment. Pursuing the idea to improve both performance and rapidity associated with the histopathological analysis of kidney biopsy, with a possible recourse to artificial intelligence-based renal pathology, the present study intends to assess the impact of direct histopathological examination of kidney biopsy with dynamic full-field optical coherence tomography in routine practices for the diagnosis of either acute kidney injury or chronic kidney disease.

Eligibility criteria:
Inclusion Criteria:

* patients \> 18 years of age with suspected acute kidney injury requiring biopsy in the nephrology department
* patients \> 18 years of age with suspected chronic kidney disease requiring biopsy in the nephrology department

Exclusion Criteria:

* inability to perform dynamic full-field optical coherence tomography observation at the moment of kidney biopsy

Outcomes:
Histopathological analysis of elementary lesions in nephropathology with dynamic full-field optical coherence tomography
Clinical Study of Ultrasonic Artificial Intelligence and Fine Needle Aspiration in Qualitative Diagnosis of Thyroid Nodules
Trial ID: NCT05407506
Status: UNKNOWN
Study type: INTERVENTIONAL
Phase: NA
Start date: 2022-06
Completion date: 2024-06
Sponsor: Luo Dingcun
Conditions: Thyroid Nodule
Interventions: THYROID AI
Enrollment: 1000
Age range: 18 Years - 75 Years
Sex: ALL

Summary:
To study the value of thyroid artificial intelligence diagnosis system and fine needle puncture in the diagnosis of benign and malignant thyroid nodules, so as to provide evidence-based medical evidence for the diagnosis of benign and malignant thyroid nodules by artificial intelligence.

Eligibility criteria:
Inclusion Criteria:

* (1) Age 18-75 years old, regardless of gender; (2) The nodules were observed with complete transverse and longitudinal standard sections; (3) The nodules were observed and underwent thyroid fine needle aspiration, including cytology and BRAF gene mutation detection; (4) Patients voluntarily entered the study after informed consent.

Exclusion Criteria:

* (1) If the observed nodule is less than 2mm or more than 50mm, the artificial intelligence system cannot recognize it; (2) Uncontrolled subacute thyroiditis and hyperthyroidism; (3) Previous thyroid surgery or radiofrequency ablation of thyroid nodules; (4) History of neck trauma.

Outcomes:
THYROID AI
Artificial Intelligence-Based APP for Home Oral Muscles Exercises for Healthy Adults
Trial ID: NCT05549648
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2022-08-01
Completion date: 2023-05-30
Sponsor: The University of Hong Kong
Conditions: Oral Manifestations
Interventions: Home oral excrise
Locations: Faculty of Dentisry, the University of Hong Kong
Countries: Hong Kong
Enrollment: 92
Age range: 50 Years - 90 Years
Sex: ALL

Summary:
Hong Kong and Japan are similar in terms of facing the super-ageing society. Maintaining oral function in elderly is particularly important because it affects social, physical and mental health to the people and to the society. By using technology seems to be one of the solutions in dealing with this. Thus, this project aims at using state-of-the-art Age-tech that have been used in Japan to implement "Oral Frailty" concept in Hong Kong. Through identifying oral biomechanical in elderly population, the investigators expect the situation can be improved, and the data analysed and collected can be useful and impactful that can influence the dental communities around Southeast Asia and the globe.

Eligibility criteria:
Inclusion Criteria:

* Population with aged (50-90 y.o.) neurologically healthy citizens in Hong Kong who have at least 1 occluding paired molars.
* Can read Traditional Chinese and communicate in Cantonese
* Possessed a smartphone with internet access and was able to use it on their own or with the help of at least one family member
* passed the Montreal Cognitive Assessment 5-Minute Protocol (Hong Kong Version)

Exclusion Criteria:

* Subject who was under 50 or unable to give consent.
* Subject who has Cerebrovascular accident, Head and Neck Cancers, Neurologic Diseases, and other severe systemic diseases.
* Subject who is receiving radiotherapy and chemotherapy.
* Subject who was medically unfit.
* Subject who has no molar.

Outcomes:
Occlusal force assessment; Masticatory efficiency; Tongue function assessment; Dry mouth; Oral health-related quality of life
Validation of a Medical-grade Wearable Device with Interpretable Artificial Intelligence System for the Obstructive Sleep Apnea-hypopnea Syndrome (OSAHS) Screening
Trial ID: NCT06351878
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2024-02-28
Completion date: 2024-08-23
Sponsor: PranaQ Pte. Ltd.
Conditions: Obstructive Sleep Apnea
Locations: Duke University
Countries: United States
Enrollment: 200
Age range: 20 Years - None
Sex: ALL

Summary:
A validation study has been designed to assess the performance of a home sleep test device, TipTraQ, for screening sleep apnea. The study involves participants wearing the TipTraQ device on their fingertip during a traditional sleep test, known as polysomnography (PSG), conducted in a sleep center. The performance of the device will then be evaluated by comparing the results from the TipTraQ system with those from the traditional sleep test.

Eligibility criteria:
Inclusion Criteria:

Subjects from the age of 20 and older that have an indication for an in-lab PSG study in the Duke University Hospital. The subject should be able to understand the study and sign the informed consent before being enrolled in the study. During the study period, the subject can withdraw from the study anytime.

Exclusion Criteria:

Subjects with the following medical conditions will be excluded from this study:

1. Heart transplant
2. Heart failure, New Youk Heart Association (NYHA) classification III or IV
3. Chronic Obstructive Lung Disease, Global Initiative for Chronic Obstructive Lung Disease (GOLD) categorization 3 or 4
4. Chronic opioid medication user Devastating Severe strokes, with the modified Rankin score (mRS)≥4
5. Tracheostomy
6. Incapable of comprehending and signing the informed consent and questionnaires, including but not limited to subjects with severe Alzheimer's, unconscious by head trauma, or of someone with limited mental capacity
7. Cannot correctly follow the order to use the TipTraQ device

Outcomes:
Apnea Hypopnea Index(AHI); Oxygen Desaturation Index(ODI); Total Sleep Time(TST)
Development and Validation of an Artificial Intelligence-assisted Diagnostic System for Ophthalmic Pathologies
Trial ID: NCT07497815
Status: NOT_YET_RECRUITING
Study type: OBSERVATIONAL
Start date: 2026-05-01
Completion date: 2029-05-01
Sponsor: Marisse Masis-Solano
Collaborators: Iriscience Inc
Conditions: Macular Degeneration; Diabetic Retinopathy (DR); Glaucoma; Keratoconus; Cataract
Interventions: No interventions
Locations: Centro Ocular; Asociados de Mácula y Vítreo de Costa Rica
Countries: Costa Rica; Costa Rica
Enrollment: 15000
Age range: 18 Years - None
Sex: ALL

Summary:
This is a retrospective, multicenter, observational study designed to develop and validate an artificial intelligence (AI) system capable of detecting and classifying major ophthalmic diseases (glaucoma, cataract, diabetic retinopathy, and other retinal pathologies) in the Costa Rican population. The study will use approximately 15,000 existing medical images from digital archives of two ophthalmic centers in Costa Rica, without active participant recruitment or capture of new images.

The primary motivation is that AI systems developed in other countries (primarily Asian, European, or North American populations) do not necessarily perform with the same accuracy when applied to Latin American populations. This study seeks to establish a precedent for the importance of locally validating any medical AI technology before clinical implementation.

Eligibility criteria:
Inclusion Criteria:

* Image corresponds to patient ≥18 years of age at time of capture
* Image modality is one of: fundus photography, posterior segment OCT, anterior segment photography, automated perimetry, or video-OCT
* Image quality sufficient for diagnostic interpretation (adequate resolution, focus, illumination, complete visualization of anatomical area of interest, no major artifacts)
* Minimum clinical data available (age or age group, sex, and diagnosis or clinical indication)
* Image captured during routine clinical care (not specifically for research)
* No patient objection to use of medical data for research (when applicable per center policy)

Exclusion Criteria:

CLINICAL:

* Images from eyes with recent intraocular surgery (\<3 months)
* Images from eyes with severe ocular trauma distorting anatomy
* Images from patients with rare or unique ocular pathologies not allowing generalization
* Images post-recent laser treatment where acute changes may confuse analysis

TECHNICAL:

* Severely degraded image quality (extreme blur, severe under/overexposure, major artifacts preventing interpretation)
* Duplicate images of same eye on same date
* Images with missing or clearly erroneous metadata
* Images in non-standard or corrupted formats that cannot be processed

Sex/Gender: All Minimum Age: 18 Years Maximum Age: No limit Accepts Healthy Volunteers: Yes (images of healthy eyes without pathology are included as controls)

Outcomes:
Area Under ROC Curve (AUC); Specificity
AI Medical Interviewing and Diagnostic System Performance Evaluation: One-Shot Vision Differential Diagnosis (OSVDE) and Multi-Step Conversational Non-Inferiority (MSCNE) Evaluation.
Trial ID: NCT07470463
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2026-03-19
Completion date: 2026-09-19
Sponsor: Magic Health Inc. (d.b.a. Nolla Health)
Conditions: Differential Diagnosis; Diagnostic Accuracy
Interventions: AI Diagnostic System (AIMD.1)
Locations: Nolla Health (Magic Health Inc.)
Countries: United States
Enrollment: 30
Age range: 18 Years - None
Sex: ALL

Summary:
This study evaluates the diagnostic performance of a multimodal artificial intelligence (AI) system (AIMD.1) using de-identified medical images and semi-synthetic patient simulations. The study combines retrospective analysis of existing publicly available image datasets with prospective data collection from licensed clinicians who complete diagnostic evaluation tasks.

In the One-Shot Vision Differential Evaluation (OSVDE) stage, clinicians review individual de-identified medical images and generate a ranked list of potential diagnoses based solely on visual features. In the Multi-Step Conversational Non-Inferiority Evaluation (MSCNE) stage, clinicians complete diagnostic assessments using semi-synthetic patient simulations derived from de-identified medical images. Clinician performance will be compared with the AI system on the same diagnostic tasks.

Human participants consist solely of licensed clinicians who provide diagnostic responses. Medical images and simulated cases are study materials and are not considered study participants. No identifiable patient data are used, and the AI system is evaluated in an offline research environment and is not used for clinical decision-making or patient care.

Eligibility criteria:
Inclusion Criteria:

* Active license in Dermatology, Internal Medicine, Otolaryngology, Gynecology, Orthopedics, Pediatrics, Geriatrics, Emergency Medicine, Ophthalmology, Psychiatry, Endocrinology, Family Medicine, or a closely related specialty
* Age 18 years or older
* Ability to complete diagnostic evaluation sessions remotely using a computer or tablet with reliable internet access

Exclusion Criteria:

* Loss of active license in an eligible specialty
* Inability to complete the evaluation session remotely

Outcomes:
Top-1 Diagnostic Accuracy
A Randomized Controlled Trial of an Avatar-based Supportive Care Intervention for Patients Undergoing Outpatient Stem Cell Transplantation
Trial ID: NCT06564233
Status: RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2024-10-21
Completion date: 2026-11-29
Sponsor: Victor Wang
Collaborators: Dana-Farber Cancer Institute; care.coach corporation
Conditions: Hematopoietic Stem Cell Transplantation; Cancer
Interventions: care.coach Avatar™
Locations: Dana-Farber Cancer Institute
Countries: United States
Enrollment: 90
Age range: 19 Years - None
Sex: ALL

Summary:
The overall goal of this study is to assess the efficacy of the care.coach Avatar™ in improving anxiety and quality of life for patients undergoing outpatient transplant. After care.coach Avatar™ content and scheduling ("digital intervention" or "program") has been optimized for outpatient allogeneic hematopoietic stem cell transplantation (HCT), a randomized controlled trial (RCT) will be conducted of the digital versus usual supportive care program for outpatient HCT recipients. Potential improvements in anxiety and quality of life will be evaluated, with the intent of increasing comfortability with outpatient transplant and expanding the population of eligible patients willing to receive their transplants in an outpatient setting.

Eligibility criteria:
Inclusion Criteria:

* Age 18+
* Seen for outpatient RIC HCT (prior to D0, generally D-6).

Exclusion Criteria:

* Deemed by clinical staff or research assistant (RA) to be unable to converse with an avatar, due to: severe, uncorrectable hearing or vision impairment; severe speech impairment that precludes understanding by staff (or by the avatar).
* Not fluent in English.

Outcomes:
HADS-A