moncefem/clinical-trials-ai-2000-2025 huggingface dataset:
Programming Cochlear Implant With Artificial Intelligence
Trial ID: NCT03700268
Status: UNKNOWN
Study type: INTERVENTIONAL
Phase: NA
Start date: 2017-09-04
Completion date: 2021-09
Sponsor: Cliniques universitaires Saint-Luc- Université Catholique de Louvain
Conditions: Deafness; Perception
Interventions: Manual intervention to programme Cochlear Implant electrodes
Locations: Cliniques Universitaires Saint-Luc
Countries: Belgium
Enrollment: 30
Age range: 18 Years - None
Sex: ALL

Summary:
This thesis project proposes to investigate the "state of the art" of the programming of the cochlear implant. In the center of audiophonologie Brussels, the classic 'manual programming' has been in use over 20 years and also the new way 'Artificial Intelligence programming'. The investigators want to compare, objectify, and control this new mode of programming.

The study is planned over 4 years, in order to test, randomized, 15 subjects with manual programming and 15 other subjects with Artificial Intelligence programming. To test the performance of Cochlear Implant patients, audiological, language auditory perception and questionnaire tests will be presented.

This research aims to determine the contribution and results of Artificial Intelligence programming.

Eligibility criteria:
Inclusion Criteria:

* unilateral cochlear implant
* post-lingual hearing loss
* a good command of French.

Exclusion Criteria:

* non deaf
* bilateral cochlear implant
* deaf without cochlear implant

Outcomes:
Evaluate Fox software efficiency
ClientBot: a Conversational Agent That Supports Skills Practice and Feedback for Motivational Interviewing for Alcohol Use Disorder (AUD)
Trial ID: NCT05479890
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2023-01-31
Completion date: 2024-11-10
Sponsor: Lyssn.io, Inc.
Collaborators: National Institute on Alcohol Abuse and Alcoholism (NIAAA); Prevention Research Institute
Conditions: Motivational Interviewing; Alcohol Use Disorder
Interventions: ClientBot
Locations: Prevention Research Institute
Countries: United States
Enrollment: 164
Age range: 18 Years - None
Sex: ALL

Summary:
This multi-stage study includes qualitative interviews, usability research, and a randomized training study of technology implementation in a real-world clinical setting. The proposed study will enhance and evaluate an artificial intelligence (AI) based, conversational agent (ClientBot) that simulates a realistic client with alcohol concerns and provides performance-based feedback to support counselor training. The research is in collaboration with PRI, which focuses on training alcohol and substance use counselors.

Eligibility criteria:
Inclusion Criteria:

* Clinician trainee participating in training with Prevention Research Institute (PRI)

Exclusion Criteria:

* None

Outcomes:
CASPI: Computer Assessment of Simulated Patient Interviews; CASPI: Computer Assessment of Simulated Patient Interviews; CASPI: Computer Assessment of Simulated Patient Interviews
Machine Learning Analysis of Lingual Colorimetry and MADRS Score in Acupuncture Patients: a Prospective Observational Study
Trial ID: NCT06899490
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2024-06-27
Completion date: 2026-06
Sponsor: Dr Benoit Bataille
Conditions: Anxiety Disorders
Locations: Cabinet Médical d'Acupuncture
Countries: France
Enrollment: 350
Age range: 18 Years - None
Sex: ALL

Summary:
This observational study aims to assess the potential relationship between tongue colorimetry (using standardized photographic techniques) and anxiety-depression scores measured by the Montgomery-Åsberg Depression Rating Scale (MADRS) in acupuncture patients. Data will be analyzed using machine learning methods to determine whether tongue color features correlate with MADRS scores, possibly contributing to a novel, non-invasive diagnostic tool for anxiety and depression assessment in clinical practice.

Participation involves only tongue photography and completion of questionnaires, without any invasive procedures or treatment modifications.

Eligibility criteria:
Inclusion Criteria:

* Patients aged 18 years or older
* Native French speakers
* No medical conditions or medications affecting tongue coloration
* Consulting for acupuncture with symptoms involving an anxious component

Exclusion Criteria:

* Presence of psychosis or substance abuse
* Eating or taking medication within one hour before the examination
* Refusal to complete the Montgomery-Åsberg Depression Rating Scale (MADRS) questionnaire
* Refusal to have their tongue photographed

Outcomes:
Correlation using Machine Learning between Tongue Colorimetric Features and MADRS Scores
Scientific Validity Assessment and Optimization of AI-Generated A3/A4 Type Questions for the Chinese Medical Licensing Examination: An Empirical Analysis Based on the "Answering-Generating" Closed Loop and Transformation of Competency Assessment
Trial ID: NCT07505862
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2025-10-01
Completion date: 2026-03-30
Sponsor: Guangdong Provincial People's Hospital
Conditions: AI (Artificial Intelligence)
Locations: Guangdong Provincial People's Hospital
Countries: China
Enrollment: 20
Age range: 18 Years - 60 Years
Sex: ALL

Summary:
This is a cross-sectional study that primarily employs quantitative analysis, supplemented by qualitative assessment. The research is conducted in two stages: Phase I consists of a model performance comparison experiment, and Phase II involves an item quality evaluation experiment. The entire study adheres to the principles of single-blinding, randomization, and standardization to ensure scientific rigor and reproducibility.

The single-blind design is implemented during the "standardized testing" phase, where the system intersperses AI-generated items with those authored by human experts. Participants remain blinded to the source of each item (AI-generated vs. human-authored) throughout the testing and scoring processes, thereby ensuring the objectivity of the evaluation results.

Eligibility criteria:
Inclusion Criteria:

* 1.Professional Status: Medical students currently enrolled in a Standardized Residency Training (SRT) program.

  2.Educational Background: Holders of a Bachelor of Medicine degree or higher, with foundational clinical knowledge.

  3.Informed Consent: Voluntarily participate in the study and provide written informed consent.

  4.Technical Competency: Proficient in using digital platforms to complete assessments and scoring.

Exclusion Criteria:

* 1.Conflict of Interest: Individuals involved in the AI model training, prompt engineering, or the creation of the human-authored question bank for this study.

  2.Inability to Complete: Presence of visual/auditory impairments or severe illness that precludes completion of the assessment within the specified time.

  3.Investigator's Discretion: Any other condition that, in the opinion of the investigator, renders the participant unsuitable for the study.

Outcomes:
Comparative Analysis of Item Accuracy
Artificial Intelligence in Colonic Polyp Detection
Trial ID: NCT05178095
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2020-09-30
Completion date: 2023-06-01
Sponsor: Sahlgrenska University Hospital
Conditions: Polyp of Colon; Adenoma Colon; Gastrointestinal Neoplasms
Interventions: Artificial intelligence; No Artificial Intelligence
Locations: Dr Per Hedenström
Countries: Sweden
Enrollment: 250
Age range: 40 Years - 90 Years
Sex: ALL

Summary:
A randomized, controlled study investigating the potential benefits of artificial intelligence (AI) in the detection of colonic polyps during outpatient colonoscopy. Randomization between the use of AI and no AI is performed before the study procedure.

Eligibility criteria:
Inclusion Criteria:

* All patients without IBD referred for colonoscopy

Exclusion Criteria:

* Age \< 40 years
* Not willing to participate

Outcomes:
ADR
Spatial and Temporal Characterization of Gliomas Using Radiomic Analysis
Trial ID: NCT06036381
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2024-02-15
Completion date: 2026-12
Sponsor: Tata Memorial Centre
Collaborators: Indian Statistical Institute, Kolkata
Conditions: Glioma
Interventions: Radiomic analysis of imaging - MRI, PET, CT
Locations: Tata Memorial Hospital
Countries: India
Enrollment: 1000
Age range: 1 Year - None
Sex: ALL

Summary:
Glioma are type of primary brain tumors arising within the substance of brain. Different type of gliomas are seen which are classified depending upon pathological examination and advanced molecular techniques, which help to determine the aggressiveness of the tumor and outcomes. Artificial intelligence uses advanced analytical process aided by computer which can be undertaken on the medical images. We plan to use artificial intelligence techniques to identify the abnormal areas within the brain representing tumor from the radiological images. Also, similar approach will be undertaken to classify gliomas with good or bad prognosis, to differentiate glioma from other type of brain tumors, and to detect response after treatment.

Eligibility criteria:
Inclusion Criteria:

* Patients with glioma or glioma-mimicking pathology with imaging available in TMC between January 2010 and December 2022.

Exclusion Criteria:

* Imaging done outside TMC.
* Motion artifacts or other artifacts causing image degradation.
* Size of tumor or region of interest \< 1 cm in the largest dimension

Outcomes:
Autosegmentation of tumor; Prognostication of gliomas
Appropriate Use of Blood Cultures in the Emergency Department Through Machine Learning: a Randomized Controlled Trial
Trial ID: NCT06163781
Status: RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2024-02-19
Completion date: 2027-07
Sponsor: Amsterdam UMC, location VUmc
Conditions: Artificial Intelligence; Machine Learning; Microbiology; Emergency Service, Hospital; Randomized Controlled Trial
Interventions: Blood culture prediction tool
Locations: Amsterdam UMC - location AMC
Countries: Netherlands
Enrollment: 7584
Age range: 18 Years - None
Sex: ALL

Summary:
The goal of this clinical trial is to study whether the use of our blood culture prediction tool is non-inferior to current practice and if it can improve certain outcomes in all adult patients presenting to the emergency department with a clinical indication for a blood culture analysis (according to the treating physician). The primary endpoint is 30-day mortality. Key secondary outcomes are:

* hospital admission rates
* in-hospital mortality
* hospital length-of-stay. In the intervention group, the physician will follow the advice of our blood culture prediction tool.

In the comparison group all patients will undergo a blood culture analysis.

Eligibility criteria:
Inclusion Criteria:

* Age \>= 18 years
* Have a clinical indication for a blood culture analysis (according to the treating physician)
* Have sufficient data recorded (laboratory results and vital sign measurements) for a prediction to be made (at least 20% of the needed parameters)

Exclusion Criteria:

* Central Venous Line (CVL) or Peripherally Inserted Central Catheter (PICC) in situ
* Neutrophil count \< 0.5 \* 109/L
* Candidemia or S. aureus bacteraemia in the past 3 months.
* Most likely diagnosis of endocarditis/spondylodiscitis/infected prosthetic material
* Pregnant or breastfeeding patients
* Not capable of giving informed consent

Outcomes:
30-day mortality
PROSPECTIVE EVALUATION OF HEARTFOCUS: A SOFTWARE SUPPORTING THE ACQUISITION OF CARDIAC ULTRASOUND EXAMS (HF-01)
Trial ID: NCT05874128
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2023-11-13
Completion date: 2024-08-16
Sponsor: DESKi
Conditions: Cardiac Disease
Interventions: Using HeartFocus software with AI guidance (Novices); Using HeartFocus software without AI-guidance
Locations: Lenox Hill Hospital; University Hospital of Bordeaux
Countries: United States; France
Enrollment: 240
Age range: 18 Years - None
Sex: ALL

Summary:
The study's objective is to evaluate if exams, performed with the HeartFocus software by novices, are of sufficient quality to visually analyze the left ventricular size, the left ventricular function, the right ventricular size, and the presence of non-trivial pericardial effusion.

Novices will be nurses without prior ultrasound experience who have received dedicated training on cardiac ultrasound and on Heartfocus software. Ultrasound exams will be limited to the acquisition of 10 reference views

Eligibility criteria:
Inclusion Criteria:

Patient (male or female) over 18 years old, Patient having an echocardiography examination scheduled in one of the two investigation centers.

Patient who has given his non-objection to participate in the research

Exclusion Criteria:

Patient subject to a measure of legal protection (safeguard of justice, guardianship or curatorship), Patient deprived of liberty by judicial or administrative decision, Patient being unable to give his non-objection, Pregnant or breastfeeding women, Patient with cardiac anatomy that does not allow reference electrocardiographic sections to be made (situs inversus, single ventricle, congenital anomalies, etc), Patient having benefited from prior echocardiographic exams whose reports mention poor or weak echogenicity, Patient having known chest deformity that has already been mentioned in previous reports or has been the subject of investigations (pectum excavatum), Patient who has undergone total or partial pneumectomy

Outcomes:
The Left Ventricular Size (Qualitative Visual Assessment); The Left Ventricular Function (Qualitative Visual Assessment); The Right Ventricle Size (Qualitative Visual Assessment); The Presence of Non-trivial Pericardial Effusion (Qualitative Visual Assessment)
The Effectiveness of Detecting Plaque on Tooth Surfaces Using Traditional and Artificial Intelligence Monitoring
Trial ID: NCT06511830
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2024-11-20
Completion date: 2026-06
Sponsor: University of Nebraska
Conditions: Plaque, Dental
Interventions: Dental Monitoring images
Locations: University of Nebraska Medical Center Dental College
Countries: United States
Enrollment: 50
Age range: 19 Years - 85 Years
Sex: ALL

Summary:
This study investigates the similarity between microbial plaque scores when assessing the entire dentition versus select teeth. The hypothesis posits that plaque buildup on single teeth mirrors that of the entire mouth, facilitating efficient plaque data collection and generalized deductions. Additionally, the research explores the potential of Dental Monitoring© photos in accurately identifying plaque indexes, aiming to enhance plaque evaluation efficiency in dental appointments. The null hypothesis suggests no significant difference between full dentition plaque scores and selected teeth. Results may streamline plaque tracking in patient appointments and enable remote monitoring, potentially detecting plaque accumulation issues earlier.

Eligibility criteria:
Inclusion Criteria:

* 19-85 years old
* Patient at the University of Nebraska Medical Center (UNMC) College of Dentistry
* One molar, premolar or canine pe quadrant

Exclusion Criteria:

* No permanent dental devices (braces, splints)
* Less than 20 non-restored teeth present in the dentition

Outcomes:
Presence of Visibly Detectable Plaque
Molecular and Cellular Characterization of MALT Lymphoma Across Anatomical Sites: Integrative Transcriptomic and Epigenetic Approaches
Trial ID: NCT07376330
Status: NOT_YET_RECRUITING
Study type: OBSERVATIONAL
Start date: 2026-04
Completion date: 2029-12
Sponsor: International Extranodal Lymphoma Study Group (IELSG)
Conditions: MALT Lymphoma
Locations: IRCCS Ospedale San Raffaele
Countries: Italy
Enrollment: 400
Age range: 18 Years - None
Sex: ALL

Summary:
Extranodal marginal zone lymphoma of mucosa-associated lymphoid tissue (MALT lymphoma) is an slow growing malignancy characterized by marked biological and clinical differences across different anatomical sites.

Using participants' samples and clinical information, this observational and non-interventional research aims to generate a comprehensive molecular and cellular atlas of MALT lymphoma. The results will enable the identification of biologically meaningful tumor subtypes, microenvironmental niches, and candidate biomarkers with potential relevance for the diagnosis, prognosis, and therapy of MALT lymphoma.

Eligibility criteria:
Inclusion Criteria:

1. Male or female adults 18 years or older
2. Diagnosis of extranodal marginal zone lymphoma of mucosa-associated lymphoid tissue on histology after Jan 1st, 2000.
3. Availability of tumor material from biopsies (either frozen or formalin-fixed paraffin-embedded) (FFPE).
4. Availability of the baseline and follow-up annotations.

Exclusion Criteria:

* None

Outcomes:
Molecular and spatial profiles of MALT lymphoma
Construction of an Artificial Intelligence Prognostic Prediction Model for Sepsis Based on Time Series Analysis
Trial ID: NCT06724120
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2020-01-01
Completion date: 2023-12-31
Sponsor: West China Hospital
Conditions: Sepsis; Prognostic Model; Artificial Intelligence; Individuality
Interventions: No interventions
Locations: Chi Zhang
Countries: China
Enrollment: 3641
Age range: 18 Years - None
Sex: ALL

Summary:
Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. It is one of the leading causes of death and disability worldwide, with an inpatient mortality rate of 10-20%. Sepsis is a severe complication in critically ill patients and can lead to septic shock and multiple organ dysfunction syndrome (MODS), usually triggered by severe trauma, surgery, and infections. Despite the availability of advanced diagnostic, therapeutic, and monitoring technologies, the incidence and mortality of sepsis remain high, posing a significant global challenge to the medical community. Over 49 million people worldwide develop sepsis annually, with approximately 11 million deaths, resulting in a mortality rate of about 15%-25%.

This study aims to develop a prognosis prediction model for sepsis patients using a neural network architecture (Transformer algorithm), based on time-series data. The primary outcome observed is the mortality outcome of sepsis patients. The goal of the research is to enhance the early identification of high-risk sepsis patients, thereby optimizing the timing of sepsis treatment and intervention and improving the accuracy of prognosis prediction for sepsis patients.

Eligibility criteria:
Inclusion Criteria:

* Patients clinically diagnosed with sepsis at West China Hospital of Sichuan University from January 2020 to December 2023

Exclusion Criteria:

* Under the age of 18;
* Gender unknown;
* Incorrect or invalid discharge diagnosis;
* The hospitalization time is less than 24 hours;
* Data information is missing by more than 30%.

Outcomes:
Biomarker level
Novel Subtypes and Treatment Strategies of Patients with Unresectable Mixed Hepatocellular Cholangiocarcinoma Based on Multimodal Data
Trial ID: NCT06849180
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2024-12-31
Completion date: 2026-02-28
Sponsor: Zhongda Hospital
Collaborators: Eastern Hepatobiliary Surgery Hospital; The First Affiliated Hospital of Zhengzhou University; Jiangsu Cancer Institute & Hospital; Yunnan Cancer Hospital; Zhejiang Cancer Hospital; Shanghai Zhongshan Hospital; Sun Yat-Sen University Cancer Center
Conditions: Combined Hepatocellular-cholangiocarcinoma; Combined Hepatocellular Carcinoma and Cholangiocarcinoma; Combined Hepatocellular and Cholangiocarcinoma
Interventions: Interventional therapies combined with or without systemic drugs
Locations: Zhongda Hospital
Countries: China
Enrollment: 198
Age range: 18 Years - None
Sex: ALL

Summary:
This study focused on exploring new comprehensive treatment strategies for patients with unresectable combined hepatocellular-cholangiocarcinoma, classifying patients with CHC subtypes based on the combination of artificial intelligence and multi-omics, and exploring the optimal treatment strategies for patients with different subtypes, helping clinicians to screen the most beneficial groups of various treatment schemes, and providing new ideas for safe treatment of high-risk patients.

Eligibility criteria:
Inclusion Criteria:

1. age ≥18 years; diagnosis of CHC confirmed by histology or cytology;
2. patients with unresectable or metastatic CHC diagnosed on the basis of unresectable CHC who have received prior local therapy, systemic therapy, or a combination of both and have at least one measurable lesion (RECIST v1.1);
3. survival time ≥ 3 months;
4. ECOG PS 0-2;
5. Child-Pugh A/B.

Exclusion Criteria:

1. pregnant women, lactating women, and men and women of childbearing age who are unwilling or unable to use effective contraception.
2. history of other malignant tumors within the past five years, unless these tumors have been completely treated and have been free of active disease for five years prior to the first dose and are at low risk of recurrence.
3. fully treated carcinoma in situ with no evidence of disease.
4. history of gastrointestinal bleeding or significant bleeding tendency (e.g., with known active ulcers, fecal occult blood, etc.) within the past six months that precludes inclusion in the study; gastroscopy is required if there is persistent fecal occult blood.
5. substantial organ transplantation or bone marrow transplantation within two years prior to the first dose, or active autoimmune disease requiring systemic therapy.
6. other conditions that the investigator deems unsuitable for inclusion in the study. Inadequate information, such as incomplete data from laboratory tests, missing or poor quality imaging data, no prognostic information, etc., that the investigator considers unsuitable for inclusion in the study.

Outcomes:
Overall Survival(OS)
Survival and cArdiovascular eVents in Patients With Acute Myocardial Infarction in Peking UNiversity First Hospital: A lonG-term Cohort Study
Trial ID: NCT06489080
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2024-03-01
Completion date: 2028-12-31
Sponsor: Peking University First Hospital
Conditions: Acute Myocardial Infarction; Coronary Artery Disease
Locations: Division of Cardiology, Peking University First Hospital
Countries: China
Enrollment: 10000
Age range: 18 Years - None
Sex: ALL

Summary:
This prospective and prospective cohort study aims to establish a long-term follow-up cohort of patients with acute myocardial infarction, and combine multi-omics studies, wearable devices, artificial intelligence technology, etc., to describe the clinical characteristics of patients with acute myocardial infarction and the changing trend of treatment strategies, and analyze the related influencing factors. Explore new biomarkers and indicators affecting recurrent cardiovascular events for accurate risk stratification and risk prediction; To evaluate the factors affecting lifestyle intervention, drug efficacy and safety, and their impact on outcome, and improve chronic disease management mode, in order to improve the quality of life and prognosis of patients.

Eligibility criteria:
Inclusion Criteria:

* Acute myocardial infarction is diagnosed meets the universal definition of acute myocardial infarction

Exclusion Criteria:

* Did not agree to participate in the study

Outcomes:
Major Adverse Cardiovascular Events