[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"malignant-tumours\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:malignant-tumours":35},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":16,"sex":17,"minAge":4,"maxAge":4,"enrollmentInfo":18,"targetDuration":21,"studyType":22,"phases":4,"briefSummary":23,"conditions":24,"keywords":42,"overallStatus":53,"whyStopped":4,"lastUpdateSubmitDate":54,"lastUpdatePostDateStruct":55,"startDateStruct":58,"completionDateStruct":60,"leadSponsor":62,"locationsCount":65},"100579293","raman-spectroscopy-based-deep-learning-model-for-early-pan-cancer-early-diagnosis-100579293",false,"NCT06822413","Raman Spectroscopy-Based Deep Learning Model for Early Pan-Cancer Early Diagnosis","A Novel Raman Spectroscopy-Based Method for Pan-Cancers Early Diagnosis Supported by Deep Learning: A Prospective, Single-Arm, Multicentre Study","Inclusion Criteria:\n\n* Histopathological diagnosis of malignant tumors, including colorectal cancer, gastric cancer, hepatic cancer, pancreatic cancer, and esophageal cancer.\n* Patients in normal physiological conditions without any malignant tumors or precancerous lesions.\n* Patients with malignant tumor without recieving any interventions, including chemotherapy, surgery, radiotherapy, immunotherapy or other anti-tumor treatments.\n* Patients with a histopathological diagnosis of any precancerous lesions or non-malignant disease.\n\nExclusion Criteria:\n\n* Patients with metastatic tumors or in the condition with two or more kinds of malignant tumors at the same time\n* Post-cancer treatment patients.",true,"ALL",{"count":19,"type":20},600,"ESTIMATED","1 Year","OBSERVATIONAL","The goal of this observational study is to explore whether a Raman-based, deep learning-assisted approach can be used to develop an effective method for early pan-cancer screening. The study includes healthy individuals, patients at risk of cancer, and patients with diagnosed cancers. The main questions it aims to answer are:\n\n* Evaluating the deep-learning model's accuracy and specificity in identifying cancer-specific features in Raman spectral data and determining whether this method can accurately classify patients based on risk.\n* Identifying which model is more adaptable to the Raman spectrum\n* Providing an interpretable analysis of the model-generated diagnosis Participants are already being diagnosed and follow-up to determine the type of cancer.",[25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41],"Cancer Diagnosis","Liver Cancer, Adult","Cancer Screening","Colorectal Cancer (CRC)","Gastric Cancers","Normal Physiology","Pancreatic Cancer, Adult","Raman Spectroscopy","Deep Learning Model","Esophageal Cancer","Malignant Tumours","Precancerous Conditions","Pancreatitis","Adenoma Colon Polyp","Gastric Ulcer","Oesophagitis","Cirrhoses, Liver",[43,44,27,32,45,46,47,34,48,49,37,50,51,40,52],"Pan-cancer","Deep Learning Models","Colorectal Cancer","Pancreatic Cancer","Gastric Cancer","malignant tumour","Precancerous Condtions","Colorectal Adenoma","Gastirc Ulcer","Cirrhoses","RECRUITING","2025-04-19",{"date":56,"type":57},"2025-04-24","ACTUAL",{"date":59,"type":57},"2022-09-01",{"date":61,"type":20},"2025-07-28",{"name":63,"class":64},"Second Affiliated Hospital, School of Medicine, Zhejiang University","OTHER",4]