[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"leadSponsorName\":\"National Defense Medical Center, Taiwan\",\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:":332},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,12,0,[8,51,77,101,131,162,188,212,238,259,281,307],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":16,"sex":17,"minAge":18,"maxAge":19,"enrollmentInfo":20,"targetDuration":4,"studyType":23,"phases":24,"briefSummary":26,"conditions":27,"keywords":31,"overallStatus":38,"whyStopped":4,"lastUpdateSubmitDate":39,"lastUpdatePostDateStruct":40,"startDateStruct":43,"completionDateStruct":45,"leadSponsor":47,"locationsCount":50},"100591961","effects-of-intelligent-parent-child-bonding-intervention-on-the-physical-psychological-and-social-health-of-parents-of-premature-infants-during-hospitalization-and-return-home-100591961",false,"NCT06987227","Effects of Intelligent Parent-child Bonding Intervention on the Physical, Psychological and Social Health of Parents of Premature Infants During Hospitalization and Return Home","Effects of a Smart Parent-child Bonding Intervention on the Physical, Psychological, and Social Health of Parents of Preterm Infants During Hospitalization and Home Return: a Randomized Controlled Trial","Inclusion Criteria: 1. Parents of premature infants born less than 37 weeks of age; 2. Parents of premature infants aged 20 or above and able to communicate in Mandarin and Taiwanese; 3. Parents of premature infants agree to participate in this study and sign the research consent form; 4. The child is currently in the Pediatric and Neonatal Intensive Care Center\n\nExclusion Criteria: 1. The premature baby has congenital abnormalities or is in critical condition and cannot survive; 2. The parents cannot use mobile phones or other Internet devices; 3. The parents have a history of mental illness, intellectual disability or substance abuse.",true,"ALL","20 Years","80 Years",{"count":21,"type":22},360,"ESTIMATED","INTERVENTIONAL",[25],"NA","The study purpose is to construct and validate the effects of \"intelligent parent-child bonding intervention\" on the physical, psychological and social health of parents of premature infants.",[28,29,30],"Parents of Premature Infants","Intelligent Intervention","Parent-child Connection",[32,33,34,35,36,37],"physical health","psychological health","parents of premature infants","social health","Intelligent intervention","parent-child connection","RECRUITING","2026-05-03",{"date":41,"type":42},"2026-05-07","ACTUAL",{"date":44,"type":42},"2025-05-25",{"date":46,"type":22},"2028-03-31",{"name":48,"class":49},"National Defense Medical Center, Taiwan","OTHER",1,{"id":52,"slug":53,"hasResults":11,"nctId":54,"briefTitle":55,"officialTitle":56,"acronym":4,"eligibilityCriteria":57,"healthyVolunteers":11,"sex":17,"minAge":58,"maxAge":4,"enrollmentInfo":59,"targetDuration":4,"studyType":23,"phases":61,"briefSummary":62,"conditions":63,"keywords":4,"overallStatus":38,"whyStopped":4,"lastUpdateSubmitDate":68,"lastUpdatePostDateStruct":69,"startDateStruct":71,"completionDateStruct":73,"leadSponsor":75,"locationsCount":76},"100584312","the-impact-of-artificial-intelligence-electrocardiography-on-occlusion-myocardial-infarction-management-under-the-value-based-payment-system-100584312","NCT06887699","The Impact of Artificial Intelligence Electrocardiography on Occlusion Myocardial Infarction Management Under the Value-Based Payment System","A Randomized Clinical Trial Investigating the Impact of Artificial Intelligence Electrocardiography on Occlusion Myocardial Infarction Management Under the Value-Based Payment System","Inclusion Criteria:\n\n* Patients in the emergency department\n* Patients received at least 1 ECG examination.\n\nExclusion Criteria:\n\n* The patients received ECG at the period of inactive AI-ECG system.\n* Patients with a history of coronary angiography within the past 3 days.","18 Years",{"count":60,"type":22},212000,[25],"This trial will prospectively evaluate the impact of integrating AI-ECG within the pay-for-performance program on improving the diagnosis, treatment, and clinical outcomes of occlusion myocardial infarction patients by promoting accurate and timely diagnoses through financial incentives.",[64,65,66,67],"OMI - Occlusion Myocardial Infarction","Artificial Intelligence (AI)","Electrocardiogram","Cost-effectiveness Analysis","2026-04-06",{"date":70,"type":42},"2026-04-09",{"date":72,"type":42},"2025-08-01",{"date":74,"type":22},"2028-06-30",{"name":48,"class":49},3,{"id":78,"slug":79,"hasResults":11,"nctId":80,"briefTitle":81,"officialTitle":82,"acronym":83,"eligibilityCriteria":84,"healthyVolunteers":16,"sex":17,"minAge":18,"maxAge":85,"enrollmentInfo":86,"targetDuration":88,"studyType":89,"phases":4,"briefSummary":90,"conditions":91,"keywords":4,"overallStatus":38,"whyStopped":4,"lastUpdateSubmitDate":93,"lastUpdatePostDateStruct":94,"startDateStruct":96,"completionDateStruct":98,"leadSponsor":100,"locationsCount":50},"100630467","home-based-outpatient-multicenter-evaluation-using-electrocardiogram-home-ecg-100630467","NCT07488052","Home-based Outpatient Multicenter Evaluation Using Electrocardiogram (HOME-ECG)","Prospective Multicenter Validation of a Home-Based Artificial Intelligence Enabled Single-Lead Electrocardiogram for Detecting Low Ejection Fraction and Structural Heart Disease","HOME-ECG","Inclusion Criteria:\n\n* Age 20 years or older\n* Single-lead ECG recorded using a study-compatible device\n* Ability to comply with study procedures and, when applicable, provide informed consent according to local institutional review board (IRB) requirements\n* No transthoracic echocardiography performed within 90 days before the index ECG\n\nExclusion Criteria:\n\n* ECG signal quality insufficient for prespecified AI analysis\n* No transthoracic echocardiography available within 30 days after the index ECG\n* Echocardiography unavailable or technically inadequate for determining left ventricular ejection fraction (EF)","90 Years",{"count":87,"type":22},5000,"3 Months","OBSERVATIONAL","This prospective multicenter observational study will validate the accuracy of a previously developed artificial intelligence-enabled single-lead electrocardiogram (AI-ECG) model for identifying low ejection fraction and other structural heart disease phenotypes. Adult participants receiving a model-compatible single-lead electrocardiogram (ECG) (Apple Watch and QOCA ECG102D) and transthoracic echocardiography at five hospitals in Taiwan will be enrolled between March 1, 2026 and June 30, 2026. Model predictions will be compared with echocardiographic reference standards obtained within 30 days after the index ECG.",[92],"Heart Failure","2026-03-21",{"date":95,"type":42},"2026-03-25",{"date":97,"type":42},"2026-03-01",{"date":99,"type":22},"2026-09-30",{"name":48,"class":49},{"id":102,"slug":103,"hasResults":11,"nctId":104,"briefTitle":105,"officialTitle":106,"acronym":107,"eligibilityCriteria":108,"healthyVolunteers":11,"sex":17,"minAge":109,"maxAge":110,"enrollmentInfo":111,"targetDuration":4,"studyType":23,"phases":113,"briefSummary":114,"conditions":115,"keywords":118,"overallStatus":38,"whyStopped":4,"lastUpdateSubmitDate":123,"lastUpdatePostDateStruct":124,"startDateStruct":126,"completionDateStruct":128,"leadSponsor":130,"locationsCount":50},"100599061","a-deep-learning-enabled-electrocardiogram-for-detecting-pulmonary-hypertension-100599061","NCT07079592","A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension","A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension: A Randomized Controlled Trial","ADDPH","Inclusion Criteria:\n\n* Men or women, ≥ 50 to 85 years of age\n* At least one 12-lead ECG within 3 months\n\nExclusion Criteria:\n\n* A diagnosis of PH WHO Groups 1, 2, 3, 4, or 5\n* A diagnosis of hypertrophic cardiomyopathy, restrictive cardiomyopathy, constrictive pericarditis, cardiac amyloidosis, or infiltrative cardiomyopathy\n* Prior heart, lung, or heart-lung transplants\n* Any systolic pulmonary artery pressure \\>50 mmHg by echocardiography before\n* Echocardiography in 3 months before index ECG","50 Years","85 Years",{"count":112,"type":22},8666,[25],"This study aims to validate the use of an artificial intelligence-enabled electrocardiogram (AI-ECG) to screen for elevated PAP. We hypothesize that the AI-ECG model can early identify patients with pulmonary hypertension in high-risk patients, prompting further evaluation through echocardiography, potentially resulting in improving cardiovascular outcomes.",[65,116,117],"Artificial Intelligence (AI) in Diagnosis","Hypertension, Pulmonary",[119,120,121,122],"Artificial intelligence","electrocardiogram","deep learning","pulmonary hypertension","2026-02-23",{"date":125,"type":42},"2026-02-24",{"date":127,"type":22},"2026-02",{"date":129,"type":22},"2026-06-15",{"name":48,"class":49},{"id":132,"slug":133,"hasResults":11,"nctId":134,"briefTitle":135,"officialTitle":136,"acronym":4,"eligibilityCriteria":137,"healthyVolunteers":16,"sex":17,"minAge":58,"maxAge":19,"enrollmentInfo":138,"targetDuration":4,"studyType":23,"phases":140,"briefSummary":141,"conditions":142,"keywords":145,"overallStatus":153,"whyStopped":4,"lastUpdateSubmitDate":154,"lastUpdatePostDateStruct":155,"startDateStruct":157,"completionDateStruct":159,"leadSponsor":161,"locationsCount":4},"100621621","development-and-evaluation-of-an-intelligent-parent-infant-connection-based-intervention-to-strengthen-family-resilience-in-preterm-infant-care-100621621","NCT07373002","Development and Evaluation of an Intelligent Parent-Infant Connection-Based Intervention to Strengthen Family Resilience in Preterm Infant Care","Development, Optimization, and Effectiveness Evaluation of an Intelligent Parent-Infant Connection-Based Family Resilience Intervention: A Longitudinal Study of Parental Psychosocial Health From Hospitalization to Post-Discharge in Preterm Infants","Inclusion Criteria:\n\n* The infant is born prematurely with a gestational age of less than 37 weeks.\n* At least one parent of the premature infant is aged 18 years or older and can communicate in Mandarin or Taiwanese.\n* The parent(s) have provided informed consent to participate in the study.\n* The parent(s) are able to comply with the data collection procedures (participation of both parents is encouraged but not required).\n\nExclusion Criteria:\n\n* The premature infant has major congenital anomalies or is assessed by clinicians as unlikely to survive.\n* The parent(s) are unable to use a smartphone or internet-connected device due to technical, cognitive, or other limitations.\n* The parent(s) have a known history of severe psychiatric disorders, intellectual disabilities, or substance abuse, and are assessed by the research team as being unable to comply with the study procedures or intervention requirements.",{"count":139,"type":22},300,[25],"This study aims to develop, optimize, and evaluate the effectiveness of a family resilience intervention centered on intelligent parent-infant connection for parents of preterm infants. Using a longitudinal randomized controlled trial design, it examines the intervention's impact on parental psychosocial health, parenting efficacy, family resilience, and parent-infant interaction from NICU hospitalization to six months post-discharge.",[143,144,28,29],"Family Resilience","Parent-Infant Bonding",[146,147,148,149,150,151,152,143,144],"Psychosocial Health","Digital Health Intervention","Salivary Cortisol","Neonatal Intensive Care Unit (NICU)","Physical Health","Social Health","Mental Health","NOT_YET_RECRUITING","2026-01-22",{"date":156,"type":42},"2026-01-28",{"date":158,"type":22},"2026-04-01",{"date":160,"type":22},"2029-07-31",{"name":48,"class":49},{"id":163,"slug":164,"hasResults":11,"nctId":165,"briefTitle":166,"officialTitle":166,"acronym":167,"eligibilityCriteria":168,"healthyVolunteers":11,"sex":17,"minAge":58,"maxAge":4,"enrollmentInfo":169,"targetDuration":4,"studyType":23,"phases":170,"briefSummary":171,"conditions":172,"keywords":174,"overallStatus":153,"whyStopped":4,"lastUpdateSubmitDate":180,"lastUpdatePostDateStruct":181,"startDateStruct":183,"completionDateStruct":185,"leadSponsor":187,"locationsCount":4},"100616601","ai-enabled-ecg-stratification-and-timing-of-potassium-lowering-therapy-in-patients-with-hyperkalemia-a-target-trial-emulation-study-100616601","NCT07307729","AI-Enabled ECG Stratification and Timing of Potassium-Lowering Therapy in Patients With Hyperkalemia: A Target Trial Emulation Study","AIDE-K","Inclusion Criteria:\n\n1. patients visit to emergency department\n2. serum potassium ≥5.5 mEq\u002FL\n3. had a standard 12-lead ECG performed within 1 hour of the qualifying potassium measurement\n\nExclusion Criteria:\n\n1. potassium-lowering therapy administered before the index blood draw\n2. no potassium-lowering therapy initiated within 4 hours after the index draw\n3. duplicate encounters\n4. missing key covariates",{"count":87,"type":22},[25],"Hyperkalemia is a common and potentially life-threatening electrolyte disorder, yet there is limited evidence guiding the optimal timing of potassium-lowering therapy in routine clinical practice. Although electrocardiographic (ECG) abnormalities are recommended to inform treatment decisions, such findings are often subtle and difficult to recognize consistently by clinicians.\n\nThis study aims to emulate a target trial to evaluate the association between the timing of potassium-lowering therapy (timely versus delayed initiation) and short-term mortality among patients with laboratory-confirmed hyperkalemia presenting to the emergency department. In addition, the study examines whether artificial intelligence-enabled ECG (AI-ECG) stratification identifies patient subgroups that may differentially benefit from earlier treatment.\n\nUsing observational electronic health record data from multiple healthcare systems, including publicly available critical care databases and institutionally governed hospital datasets, treatment strategies are compared using causal inference methods designed to approximate randomized assignment. The primary outcome is 90-day all-cause mortality.\n\nThe results of this study are intended to inform clinical decision-making regarding treatment timing in hyperkalemia and to evaluate the potential role of AI-ECG as a risk stratification tool in real-world settings.",[173],"Hyperkalaemia",[175,120,176,177,178,179],"artificial intelligence","emergency department","hyperkalemia","potassium","treatment","2025-12-15",{"date":182,"type":42},"2025-12-29",{"date":184,"type":22},"2026-01-01",{"date":186,"type":22},"2026-03-31",{"name":48,"class":49},{"id":189,"slug":190,"hasResults":11,"nctId":191,"briefTitle":192,"officialTitle":193,"acronym":194,"eligibilityCriteria":195,"healthyVolunteers":11,"sex":17,"minAge":196,"maxAge":85,"enrollmentInfo":197,"targetDuration":4,"studyType":23,"phases":199,"briefSummary":200,"conditions":201,"keywords":4,"overallStatus":38,"whyStopped":4,"lastUpdateSubmitDate":204,"lastUpdatePostDateStruct":205,"startDateStruct":207,"completionDateStruct":209,"leadSponsor":211,"locationsCount":50},"100609642","proactive-risk-evaluation-for-cardiac-implantable-electronic-device-strategy-using-ai-ecg-100609642","NCT07217236","Proactive Risk Evaluation for Cardiac Implantable Electronic Device Strategy Using AI-ECG","Evaluation of an Artificial Intelligence-Enhanced Electrocardiogram Strategy Versus Standard Care to Identify Patients Requiring Cardiac Implantable Electronic Devices: A Randomized Controlled Trial","PRECISE-AI","Inclusion Criteria:\n\n* At least one 12-lead ECG within 1 year\n\nExclusion Criteria:\n\n* Diagnosis of sick sinus syndrome\n* Diagnosis of high-grade or complete atrioventricular block\n* Diagnosis of ventricular tachycardia or ventricular fibrillation\n* Post CIED implant\n* Heart rate below 40 beats per minute by 12-lead ECG","65 Years",{"count":198,"type":22},11492,[25],"The goal of this clinical trial is to learn whether an artificial intelligence-enhanced electrocardiogram (AI-ECG) strategy improves timely intervention of patients requiring cardiac implantable electronic devices (CIEDs), compared with standard clinical care.",[65,202,203],"Cardiac Implantable Electrical Devices","Conduction Disorder of the Heart","2025-12-05",{"date":206,"type":42},"2025-12-12",{"date":208,"type":42},"2025-11-01",{"date":210,"type":22},"2026-10-31",{"name":48,"class":49},{"id":213,"slug":214,"hasResults":11,"nctId":215,"briefTitle":216,"officialTitle":217,"acronym":218,"eligibilityCriteria":219,"healthyVolunteers":11,"sex":17,"minAge":220,"maxAge":221,"enrollmentInfo":222,"targetDuration":4,"studyType":23,"phases":224,"briefSummary":225,"conditions":226,"keywords":4,"overallStatus":38,"whyStopped":4,"lastUpdateSubmitDate":230,"lastUpdatePostDateStruct":231,"startDateStruct":233,"completionDateStruct":235,"leadSponsor":237,"locationsCount":50},"100581255","leveraging-ai-ecg-technology-for-early-notification-and-tracking-of-af-development-100581255","NCT06847932","Leveraging AI-ECG Technology for Early Notification and Tracking of AF Development","Leveraging AI-ECG Technology for Early Notification and Tracking of AF Development: a Randomized Control Trial","LATENT","Inclusion Criteria:\n\n* Patients in the inpatient department or the outpatient department\n* Patients need to have at least one electrocardiogram within one year\n\nExclusion Criteria:\n\n* Diagnosis of atrial fibrillation\u002Fatrial flutter\n* History of atrial fibrillation\u002Fatrial flutter catheter ablation\n* Patients with cardiac implantable electronic devices\n* Any documented electrocardiogram showed atrial fibrillation\u002Fatrial flutter and pacing rhythm\n* History of received rhythm control medications for atrial arrhythmia, including Class I and Class III antiarrhythmic drugs\n* Any reasons indicate for anti-coagulant agents, including vitamin K antagonist and non-vitamin K antagonist oral anticoagulant","40 Days","85 Days",{"count":223,"type":22},14726,[25],"Our study aimed to use an AF-predict AI-ECG alert system to help physicians identify patients who need to wear a continuous cardiac rhythm monitor for new diagnoses of atrial fibrillation (AF), atrial flutter (AFL), or atrial arrhythmia with high AF risk, including premature atrial complexes (PAC) ≥ 500\u002F24hr, burst PACs \\> 20 beats, non-sustained AF\u002FAFL.",[227,228,229,65,66],"Atrial Fibrillation (AF)","Premature Atrial Complexes","Atrial Arrhythmias","2025-11-16",{"date":232,"type":42},"2025-11-19",{"date":234,"type":42},"2025-07-01",{"date":236,"type":22},"2026-10-01",{"name":48,"class":49},{"id":239,"slug":240,"hasResults":11,"nctId":241,"briefTitle":242,"officialTitle":243,"acronym":4,"eligibilityCriteria":244,"healthyVolunteers":11,"sex":17,"minAge":245,"maxAge":110,"enrollmentInfo":246,"targetDuration":4,"studyType":23,"phases":248,"briefSummary":249,"conditions":250,"keywords":4,"overallStatus":38,"whyStopped":4,"lastUpdateSubmitDate":252,"lastUpdatePostDateStruct":253,"startDateStruct":255,"completionDateStruct":256,"leadSponsor":258,"locationsCount":50},"100594750","the-valve-ai-trial-100594750","NCT07023510","The VALVE-AI Trial","VALidation of Screening Valvular Heart Disease Using Electrocardiogram Powered by Artificial Intelligence: A Randomized Controlled Trial","Inclusion Criteria:\n\n* At least one 12-lead ECG within 1 year\n* Age 60-85 years of age\n\nExclusion Criteria:\n\n* Documented echocardiography within 3 years before indexed ECG\n* Any known valvular heart disease\n* History of any valvular surgery\n* Post-heart transplant","60 Years",{"count":247,"type":22},8648,[25],"The goal of this clinical trial is to learn if an artificial intelligence-powered electrocardiogram (AI-ECG) can help detect moderate or severe valvular heart diseases (VHD) in adults. The main question it aims to answer is:\n\n．Can AI-ECG screening identify patients with significant heart valve diseases who may benefit from early echocardiography? Researchers will compare the rate of moderate or severe VHD detection between the experimental group and the control group to see if AI-ECG improve the detection rate of significant VHD.\n\nParticipants will:\n\n* Be classified as high- or low-risk for VHD using an AI-ECG system\n* In the experimental group, high-risk participants will receive echocardiography based on AI-ECG results\n* In the control group, usual clinical care will be provided without routine echocardiography for AI-ECG high-risk results.",[251],"Valvular Heart Disease Patients","2025-06-23",{"date":254,"type":42},"2025-06-26",{"date":234,"type":22},{"date":257,"type":22},"2026-07-01",{"name":48,"class":49},{"id":260,"slug":261,"hasResults":11,"nctId":262,"briefTitle":263,"officialTitle":264,"acronym":4,"eligibilityCriteria":265,"healthyVolunteers":16,"sex":17,"minAge":58,"maxAge":266,"enrollmentInfo":267,"targetDuration":4,"studyType":23,"phases":269,"briefSummary":270,"conditions":271,"keywords":4,"overallStatus":153,"whyStopped":4,"lastUpdateSubmitDate":274,"lastUpdatePostDateStruct":275,"startDateStruct":277,"completionDateStruct":278,"leadSponsor":280,"locationsCount":4},"100579848","a-mobile-chatbot-with-arcs-v-motivation-theory-on-learning-motivation-100579848","NCT06829628","A Mobile Chatbot with ARCS-V Motivation Theory on Learning Motivation","The Effects of Teaching Strategies Integrating a Mobile Chatbot with ARCS-V Motivation Theory on Learning Motivation and Performance in Medical-Surgical Nursing","Inclusion Criteria:\n\n* Second-year Nursing students\n* Taking an adult nursing course\n* Aged 18 or older\n* Willing to voluntarily participate in this study\n\nExclusion Criteria:\n\n* Students auditing the course","21 Years",{"count":268,"type":22},100,[25],"This study will implement a smartphone chatbot in medical-surgical nursing education to enhance nursing students' learning motivation and academic performance. T",[272,273],"Nursing Education Research","Chatbot-Based Training","2025-02-14",{"date":276,"type":42},"2025-02-17",{"date":276,"type":22},{"date":279,"type":22},"2025-07-31",{"name":48,"class":49},{"id":282,"slug":283,"hasResults":11,"nctId":284,"briefTitle":285,"officialTitle":286,"acronym":4,"eligibilityCriteria":287,"healthyVolunteers":11,"sex":17,"minAge":58,"maxAge":4,"enrollmentInfo":288,"targetDuration":4,"studyType":23,"phases":290,"briefSummary":291,"conditions":292,"keywords":297,"overallStatus":153,"whyStopped":4,"lastUpdateSubmitDate":299,"lastUpdatePostDateStruct":300,"startDateStruct":302,"completionDateStruct":304,"leadSponsor":306,"locationsCount":4},"100578920","ai-driven-personalized-exercise-feedback-program-on-exercise-adherence-in-traumatic-brain-injury-100578920","NCT06817564","AI-driven Personalized Exercise Feedback Program on Exercise Adherence in Traumatic Brain Injury","Effects of an AI-driven Personalized Exercise Feedback Program on Exercise Adherence and Health Outcomes in Patients with Traumatic Brain Injury","Inclusion Criteria:\n\n* Eligible participants are patients aged over 18 with mild TBI (GCS 13-15)\n* who can walk independently,\n* reside in the Greater Taipei area,\n* and possess sufficient Chinese or Taiwanese language proficiency to understand the trial\n* complete self-administered questionnaires.\n\nExclusion Criteria:\n\n* Exclusion criteria include individuals with severe medical conditions (e.g., respiratory failure, epilepsy, psychiatric disorders), musculoskeletal or neurological impairments\n* hindering physical activity in the 6-minute walk test,\n* cognitive impairments (MMSE \\\u003C 24),\n* frontal lobe injuries or penetrating injury causing significant psychological dysfunction.\n* Patients regularly engaging in moderate-to-high-intensity aerobic exercise or participating in other studies will also be excluded to avoid bias.",{"count":289,"type":22},125,[25],"This study aims to develop and evaluate an AI-driven Personalized Exercise Feedback Program (AI-PEF) to enhance exercise adherence and health outcomes in mTBI patients.\n\nMethods: AI-PEF integrates the transtheoretical model and self-determination theory with machine learning algorithms to provide real-time, personalized feedback. A phased randomized controlled trial will be conducted: Phase I evaluates feasibility and acceptability through Delphi methods with expert consensus and patient feedback; Phase II validates preliminary outcomes with 30 participants in a 2-arm randomized trial; and Phase III assesses the program's impact on adherence, sleep quality, depressive symptoms, and quality of life with 90 participants in a 3-arm randomized trial.",[293,294,295,296],"Traumatic Brain Injury","Exercise","AI (Artificial Intelligence)","Digital Health",[298],"AI-Driven Personalized Exercise Program","2025-02-08",{"date":301,"type":42},"2025-02-12",{"date":303,"type":22},"2025-03-01",{"date":305,"type":22},"2031-08-31",{"name":48,"class":49},{"id":308,"slug":309,"hasResults":11,"nctId":310,"briefTitle":311,"officialTitle":312,"acronym":4,"eligibilityCriteria":313,"healthyVolunteers":11,"sex":17,"minAge":109,"maxAge":110,"enrollmentInfo":314,"targetDuration":4,"studyType":23,"phases":316,"briefSummary":317,"conditions":318,"keywords":321,"overallStatus":153,"whyStopped":4,"lastUpdateSubmitDate":325,"lastUpdatePostDateStruct":326,"startDateStruct":328,"completionDateStruct":329,"leadSponsor":331,"locationsCount":50},"100567640","itbs-in-mci-and-mild-ad-100567640","NCT06670820","iTBS in MCI and Mild AD","The Effects of Intermittent Theta-burst Stimulation on Cognitive Function in Patients With Mild Cognitive Impairment and Mild Alzheimer's Disease and the Role of Brain-Derived Neurotrophic Factor","Inclusion Criteria:\n\n* Clinical diagnosis of MCI (overall Clinical Dementia Rating of 0.5)\n* Clinical diagnosis of mild Alzheimer's Disease (overall Clinical Dementia Rating of 0.5 or 1)\n\nExclusion Criteria:\n\n* History of stroke\n* History of uncontrol seizure\n* History of significant head trauma followed by persistent neurologic deficit or known structural brain abnormality\n* Mental illness\n* Drug abuse",{"count":315,"type":22},80,[25],"This study aims to examine the effects of iTBS on cognitive function in individuals with MCI or mild AD, with a secondary objective of exploring prefrontal TBS mechanisms for cognitive function and the effect of iTBS on BDNF.",[319,320],"Mild Cognitive Impairment (MCI)","Mild Alzheimer Disease",[322,323,324,320],"rTMS","iTBS","Mild Cognitive Impairment","2024-10-31",{"date":327,"type":42},"2024-11-01",{"date":325,"type":22},{"date":330,"type":22},"2028-12-31",{"name":48,"class":49},""]