[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"prediction-model\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:prediction-model":39},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,5,0,[8,61,90,110,131],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":13,"acronym":4,"eligibilityCriteria":14,"healthyVolunteers":15,"sex":16,"minAge":17,"maxAge":18,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":23,"briefSummary":25,"conditions":26,"keywords":41,"overallStatus":49,"whyStopped":4,"lastUpdateSubmitDate":50,"lastUpdatePostDateStruct":51,"startDateStruct":54,"completionDateStruct":56,"leadSponsor":58,"locationsCount":5},"100636162","develop-and-evaluate-an-artificial-intelligence-assisted-prehabilitation-program-for-returning-to-work-and-cost-effectiveness-analysis-in-patients-with-oral-cancer-100636162",false,"NCT07562100","Develop and Evaluate An Artificial Intelligence Assisted Prehabilitation Program for Returning to Work and Cost-effectiveness Analysis in Patients With Oral Cancer","Inclusion Criteria:\n\n* Adult (\\> 20 years old and younger than 70 years old)\n* Newly diagnosed as OC and scheduled to receive cancer-related treatment\n* Able to use Mobile phone\n* Willing to sign an informed consent form after receiving a detailed explanation of the study's aims and procedures\n* Healthcare professionals involved in patients' care, including doctors, nurses, case managers, dietitians, rehabilitation therapists, and psychologists\n* Family members who are primary caregivers of the participating patients, engaged in different stages of medical care\n\nExclusion Criteria:\n\n* Risk populations for walking or performing exercise\n* Patients with cognitive impairment or psychiatric diseases",true,"ALL","20 Years","70 Years",{"count":20,"type":21},650,"ESTIMATED","INTERVENTIONAL",[24],"NA","The goal of this clinical trial is to develop and evaluate an Artificial Intelligence Assisted Prehabilitation Program (AI APP) for returning to work and cost-effectiveness analysis in patients with oral cancer (OC). The main questions it aims to answer are:\n\n* What kinds of needs are related to returning to work (RTW) in patients with OC from diagnosis to survival that we can incorporate into the development of AI APP to assist this population ?\n* How is the effect of the AI APP that based on findings from the first question for patients with OC on physical and psychological distress, fear of recurrence, self-efficacy in coping with cancer, communication, motor function, quality of life, and RTW?\n* How is the effect of the RTW AI prediction model to identify high-risk groups ? And how is the comprehensive cost effectiveness of benefits and quality of life of the AI APP for OC population?\n\nResearchers will compare patients without using AI APP to see if the AI APP works to assist with coping physical and psychological distress, communication, motor function, quality of life, and RTW issues for individuals with OC?\n\nParticipants will:\n\n* Be asked to fulfill a structural questionnaire, or engage in a semi-structured one-by-one interview or a focus group to assess their physical, psychological, and social support needs in the first stage.\n* Be invited to participant the pilot testing of AI APP in the second stage.\n* Be provided and trained by 3-month AI APP for 3 months or cared as usual in the third stage.\n* Complete a structural questionnaire and follow up one year, including the baseline (before using the AI app) and at 1-2 weeks, 3 months, 6 months, 9 months, and 12 months after the baseline.\n* Engage in one-by-one interview or a focus group to assess user experiences of the AI APP.",[27,28,29,30,31,32,33,34,35,36,37,38,39,40],"Oral Cancer","Psychological Distress","Communication Aids for Disabled","Physiotherapy","Return to Work","Prehabilitation","Physical Symptom Distress","Motor Function","Rehabilitation","Quality of Life","Cost Effectiveness","Artifical Intelligence","Prediction Model","Case Management, APP(Application)",[42,31,27,28,29,30,32,43,44,35,45,46,47,48],"Artificial Intelligence","Physical symptom distress","motor function","Quality of life","Cost effectiveness","prediction model","case management, APP(Application)","RECRUITING","2026-04-24",{"date":52,"type":53},"2026-05-01","ACTUAL",{"date":55,"type":53},"2024-09-27",{"date":57,"type":21},"2029-12-01",{"name":59,"class":60},"Taipei Veterans General Hospital, Taiwan","OTHER_GOV",{"id":62,"slug":63,"hasResults":11,"nctId":64,"briefTitle":65,"officialTitle":66,"acronym":4,"eligibilityCriteria":67,"healthyVolunteers":11,"sex":68,"minAge":17,"maxAge":69,"enrollmentInfo":70,"targetDuration":4,"studyType":72,"phases":4,"briefSummary":73,"conditions":74,"keywords":77,"overallStatus":49,"whyStopped":4,"lastUpdateSubmitDate":80,"lastUpdatePostDateStruct":81,"startDateStruct":83,"completionDateStruct":84,"leadSponsor":86,"locationsCount":89},"100600767","a-prediction-model-in-pregnant-women-with-aplastic-anemia-100600767","NCT07101770","A Prediction Model in Pregnant Women With Aplastic Anemia","Development and Validation of a Prediction Model for Adverse Pregnancy Outcomes in Women With Aplastic Anemia","Inclusion Criteria:\n\n1. pregnant women who had aplastic anemia before pregnancy\n2. pregnant women with newly diagnosed aplastic anemia during pregnancy\n\nExclusion Criteria:\n\n1. age less than 20 years\n2. without coagulation series results\n3. termination of pregnancy before 20 weeks of gestation\n4. multiple pregnancy","FEMALE","50 Years",{"count":71,"type":21},300,"OBSERVATIONAL","Aplastic anemia (AA) is a rare haematologic disorder characterized by bone marrow failure and pancytopenia. Its occurrence during pregnancy is exceedingly rare but poses significant risks, including maternal hemorrhage, infections, and perinatal complications such as preterm birth and fetal growth restriction. Consequently, pregnancy with AA is highly perilous for both mothers and infants. Early management is critical to ensure the health of both the mother and the baby. However, there are currently no predictive tools available to assess adverse outcomes in pregnant women with AA. Our center plans to conduct a multicenter, combined retrospective and prospective cohort study.",[75,76,39],"Aplastic Anemia","Pregnancy",[78,79,47],"aplastic anemia","pregnancy","2025-11-27",{"date":82,"type":53},"2025-12-01",{"date":80,"type":21},{"date":85,"type":21},"2030-12-31",{"name":87,"class":88},"Peking University People's Hospital","OTHER",1,{"id":91,"slug":92,"hasResults":11,"nctId":93,"briefTitle":94,"officialTitle":95,"acronym":4,"eligibilityCriteria":96,"healthyVolunteers":11,"sex":16,"minAge":4,"maxAge":4,"enrollmentInfo":97,"targetDuration":4,"studyType":72,"phases":4,"briefSummary":99,"conditions":100,"keywords":4,"overallStatus":49,"whyStopped":4,"lastUpdateSubmitDate":102,"lastUpdatePostDateStruct":103,"startDateStruct":105,"completionDateStruct":106,"leadSponsor":108,"locationsCount":89},"100591278","research-on-early-prediction-model-of-ischemic-cerebrovascular-disease-based-on-artificial-intelligence-technology-100591278","NCT06978348","Research on Early Prediction Model of Ischemic Cerebrovascular Disease Based on Artificial Intelligence Technology.","Establish an Artificial Intelligence Clinical Decision Support System for Patients With Carotid\u002FVertebral Artery Stenosis.","Inclusion Criteria:\n\nPatients undergoing vascular (carotid\u002Fvertebral artery) B-ultrasound\n\nExclusion Criteria:\n\nPatients with missing clinical data such as medical history, cerebrovascular ultrasound results and biochemical data",{"count":98,"type":21},244296,"Establish an artificial intelligence clinical decision support system for patients with carotid\u002Fvertebral artery cerebrovascular stenosis, early identification of patients who may have cerebral infarction. With the support of this project, it is expected that a secondary prevention clinical decision support system for chronic stroke will be established, which is likely to become an important auxiliary tool for the management of cerebrovascular diseases in the future.",[101,42,39],"Ischemic Cerebrovascular Disease","2025-05-10",{"date":104,"type":53},"2025-05-18",{"date":102,"type":53},{"date":107,"type":21},"2025-06-10",{"name":109,"class":88},"Shanghai Jiao Tong University School of Medicine",{"id":111,"slug":112,"hasResults":11,"nctId":113,"briefTitle":114,"officialTitle":114,"acronym":4,"eligibilityCriteria":115,"healthyVolunteers":11,"sex":16,"minAge":116,"maxAge":117,"enrollmentInfo":118,"targetDuration":4,"studyType":72,"phases":4,"briefSummary":120,"conditions":121,"keywords":4,"overallStatus":49,"whyStopped":4,"lastUpdateSubmitDate":122,"lastUpdatePostDateStruct":123,"startDateStruct":125,"completionDateStruct":127,"leadSponsor":129,"locationsCount":89},"100562028","development-and-validation-of-a-real-time-prediction-model-for-acute-kidney-injury-in-hospitalized-patients-100562028","NCT06597838","Development and Validation of a Real-time Prediction Model for Acute Kidney Injury in Hospitalized Patients","Inclusion Criteria:\n\n* Adult patients (18 years and older) admitted to five hospitals during the study period\n\nExclusion Criteria:\n\n* Have less than 2 documented serum creatinine (Scr) measurements during hospitalization\n* Being diagnosed with end-stage renal disease (ESRD)\n* Maintained on dialysis or had an initial Scr greater than or equal to 4.0 mg\u002FdL at admission\n* Developed AKI prior to admission or within 24 hours after admission\n* Length of stay shorter than 24 hours\n* Underwent kidney transplantation or nephrectomy during hospitalization\n* With all Scr measurements lower than or equal to 0.6 mg\u002FdL from 90 days prior to admission until discharge.","18 Years","100 Years",{"count":119,"type":21},161876,"Early prediction of acute kidney injury (AKI) may provide a crucial opportunity for AKI prevention. To date, no prediction model targeting AKI among general hospitalized patients in developing countries has been published. We developed a simple, real-time, interpretable AKI prediction model for general hospitalized patients from a large tertiary hospital in China, and validated it across five independent, geographically distinct, different tiered hospitals.",[39],"2024-09-12",{"date":124,"type":53},"2024-09-19",{"date":126,"type":53},"2023-02-28",{"date":128,"type":21},"2024-12-30",{"name":130,"class":88},"Peking University First Hospital",{"id":132,"slug":133,"hasResults":11,"nctId":134,"briefTitle":135,"officialTitle":135,"acronym":136,"eligibilityCriteria":137,"healthyVolunteers":11,"sex":16,"minAge":116,"maxAge":138,"enrollmentInfo":139,"targetDuration":141,"studyType":72,"phases":4,"briefSummary":142,"conditions":143,"keywords":147,"overallStatus":49,"whyStopped":4,"lastUpdateSubmitDate":152,"lastUpdatePostDateStruct":153,"startDateStruct":155,"completionDateStruct":157,"leadSponsor":159,"locationsCount":89},"100550808","early-identification-of-malignant-brain-edema-in-large-artery-occlusive-stroke-after-endovascular-therapy-embrace-study-100550808","NCT06451887","Early Identification of Malignant Brain Edema in laRge Artery oCclusive Stroke After Endovascular Therapy (EMBRACE Study)","EMBRACE","Inclusion Criteria:\n\n* (1)Age \\> 18 years old; (2)Onset of stroke to hospital admission \\\u003C 24 hours; (3)Admission with a head CT scan ruling out hemorrhage; (4)Patients undergoing CT perfusion scan before treatment; (5)Confirmation of internal carotid artery (ICA) or middle cerebral artery (MCA) occlusion or tandem occlusion by Digital Subtraction Angiography (DSA) and subsequent EVT; (6)complete 3-months follow-up.\n\nExclusion Criteria:\n\n* (1)Poor quality of preoperative CT perfusion imaging; (2)Posterior circulation occlusion or isolated anterior cerebral artery occlusion; (3)Presence of other severe diseases such as malignant tumors, severe organ failure, or other life-threatening conditions with an expected survival period of less than 90 days; (4)Incomplete imaging and clinical data.","80 Years",{"count":140,"type":21},1950,"3 Months","To design and validate a predictive model for malignant brain edema after endovascular thrombectomy.",[144,145,39,146],"Endovascular Therapy","Brain Edema","Ischemic Stroke",[148,149,150,151],"Endovascular therapy","Brain edema","Prediction model","Ischemic stroke","2024-06-06",{"date":154,"type":53},"2024-06-11",{"date":156,"type":53},"2024-04-01",{"date":158,"type":21},"2027-06",{"name":160,"class":88},"Zhejiang Provincial People's Hospital"]