Clinical trials: Deep Learning
Ophthalmic Imaging, Deep Learning
Diagnostic Performance of an AI-based Model for TCM Constitution Classification Using Ophthalmic Imaging
To evaluate the diagnostic performance of a multimodal deep learning model for identifying biased Traditional Chinese Medicine (TCM) constitutions using ophthalmic imaging
- Conditions
- Ophthalmic Imaging, Deep Learning, Artificial Intelligence (AI), Traditional Chinese Medicine Constitution
- Trial name
- NCT07127939
- Testing
- AI-based Ocular Diagnosis Model for TCM Constitutions
- Where
- China
- Volunteers
- 1,024 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital of Nanchang University
Facet Joints; Degeneration ; Deep Learning ;Artificial Intelligence
Application of Multitask Deep Learning Model in Grading the Severity of Spinal Facet Joint Degeneration
Spinal facet joint osteoarthritis is a disease with high incidence among people over 40 years old. It is a disease characterized by a series of degenerative pathological changes and clinical features of synovium, articular…
- Trial name
- NCT05635006
- Where
- China
- Volunteers
- 1,132 people
- Sponsor
- Hai Lv
Esophageal Squamous Cell Carcinoma, Neoadjuvant Immunochemotherapy
Deep Learning Model Predicts Pathological Complete Response of Esophageal Squamous Cell Carcinoma Following Neoadjuvant Immunochemotherapy
This study aims to develop and validate a deep learning model to predict pathological complete response (pCR) in patients with esophageal squamous cell carcinoma who have undergone neoadjuvant immunochemotherapy.
- Conditions
- Esophageal Squamous Cell Carcinoma, Neoadjuvant Immunochemotherapy, Pathological Complete Response, Deep Learning
- Trial name
- DL-ESCC (NCT07088354)
- Testing
- The high-throughput extraction of large amounts of quantitative image features from medical images
- Where
- China
- Volunteers
- 300 people
- Sponsor
- Tongji Hospital
Esophageal Squamous Cell Cancer (SCC), Recurrent Laryngeal Nerve Palsy
CT and Endoscopic Biopsy Image-Based Deep Learning for Predicting Left Recurrent Laryngeal Nerve Lymph Node Metastasis in Esophageal Cancer
The goal of this observational study is to develop a predictive model for left recurrent laryngeal nerve (RLN) lymph node metastasis using deep learning algorithms.
- Conditions
- Esophageal Squamous Cell Cancer (SCC), Recurrent Laryngeal Nerve Palsy, Deep Learning, Postoperative Complication
- Trial name
- NCT07074535
- Where
- China
- Volunteers
- 500 people
- Sponsor
- Daping Hospital and the Research Institute of Surgery of the Third Military Medical University
Bladder Cancer, Staging
Bladder Cancer Staging and Prediction of New Adjuvant Chemotherapy Efficacy Based on Deep Learning and Transfer Learning in Ultrasound-Magnetic Resonance-Pathology Multimodal Multiscale
Bladder cancer is the most common malignant tumor of the urinary system. The presence or absence of muscle invasion in early bladder cancer is an independent prognostic factor.
- Conditions
- Bladder Cancer, Staging, Deep Learning, Neoadjuvant Chemotherapy
- Trial name
- MICS-BC (NCT07051083)
- Testing
- Risk Stratification
- Where
- China
- Volunteers
- 480 people
- Sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Heart Failure, Cardiomyopathies
Validation of the Prognostic Impact of a Retinal Photograph-based Cardiovascular Disease Risk Stratification System in de Novo HFrEF
"Despite significant advances in pharmacologic and device-based therapies, heart failure (HF) remains a major public health burden, with persistently high rates of hospitalization, impaired quality of life, and excess…
- Conditions
- Heart Failure, Cardiomyopathies, Retinal Photograph, Deep Learning
- Trial name
- NCT06978998
- Where
- South Korea
- Volunteers
- 100 people
- Sponsor
- Yonsei University
Cancer Diagnosis, Liver Cancer, Adult
Raman Spectroscopy-Based Deep Learning Model for Early Pan-Cancer Early Diagnosis
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.
- Conditions
- Cancer Diagnosis, Liver Cancer, Adult, Cancer Screening, Colorectal Cancer (CRC)
- Trial name
- NCT06822413
- Testing
- No Interventions
- Where
- 4 sites in China
- Volunteers
- 600 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine
Artificial Intelligence (AI), Deep Learning
The Construction and Effect Verification of a Deep Learning-based Automated Semantic Segmentation Model for Medical Imaging
Hepatocellular Carcinoma(HCC) is a common disease in China, ranking as the fourth most prevalent malignant tumor and the third leading cause of cancer-related deaths in the country.
- Conditions
- Artificial Intelligence (AI), Deep Learning, Laparoscopic Surgery
- Trial name
- NCT06864702
- Testing
- Whether the patient received diagnosis and treatment at Zhujiang Hospital of Southern Medical University and retained medical images such as abdominal
- Where
- China
- Volunteers
- 220 people, healthy volunteers welcome
- Sponsor
- Zhujiang Hospital
Deep Learning, Sarcopenia
Application of Artificial Intelligence Algorithm Based on CT Imaging for Muscle Parameter Measurement
To establish an artificial intelligence model for automated diagnosis of sarcopenia based on CT imaging
- Conditions
- Deep Learning, Sarcopenia, Computed Tomography, Body Composition
- Trial name
- NCT06845462
- Where
- China
- Volunteers
- 1,080 people, healthy volunteers welcome
- Sponsor
- RenJi Hospital
Heart Failure, Deep Learning
Artificial Intelligence in Detecting Cardiac Function
The Korotkoff Sounds（KS）, which have been in use for over a century, are widely regarded as the gold standard for measuring blood pressure.
- Trial name
- NCT06444425
- Where
- China
- Volunteers
- 685 people
- Sponsor
- The Fourth Affiliated Hospital of Zhejiang University School of Medicine
Artificial Intelligence, Deep Learning
Feasibility of Gadolinium Contrast Reduced Brain MRI: the Potential of Deep Learning
MRI scans were performed using 3 different 1.5T scanners with an eight-channel head coils. Following a 3D pre-contrast T1w scan, a low-dose contrast-enhanced 3D T1w scan was obtained using 20% (0.02 mmol/kg) of the standard…
- Trial name
- NCT06462924
- Testing
- DeepGad
- Volunteers
- healthy volunteers welcome
- Sponsor
- DeepMeds
Hepatocellular Carcinoma (HCC), Liver Transplantation
Validation of the TRAIN-AI for the Risk of HCC Recurrence After Liver Transplantation
Liver transplantation (LT) is the best treatment option for patients with early stages of hepatocellular carcinoma (HCC).1 However, the use of LT depends on maintaining a balance between the risk of post-transplant recurrence or…
- Conditions
- Hepatocellular Carcinoma (HCC), Liver Transplantation, Deep Learning Model
- Trial name
- TRAIN-AI (NCT06799468)
- Testing
- liver transplantation
- Volunteers
- 1,769 people
- Sponsor
- European Hepatocellular Cancer Liver Transplant Group
Hepatocellular Carcinoma (HCC), Radiofrequency Ablation
Ga-68 Dolacga PET Scan in HCC Under RFA
This study aims to investigate the use of Ga-68 Dolacga PET scan technology to assess treatment response and liver function changes in patients of early-stage liver cancer receiving RFA.
- Conditions
- Hepatocellular Carcinoma (HCC), Radiofrequency Ablation, PET Scan, Computed Tomography
- Trial name
- HCC; RFA (NCT06792097)
- Testing
- Ga-68 Dolacga PET scan
- Volunteers
- 10 people
- Sponsor
- National Taiwan University Hospital
Facet Joint Pain; Low Back Pain, Facet Joints; Degeneration ; Deep Learning ;Artificial Intelligence
Quantitative Assessment of Lumbar Facet Joint Degeneration, A Retrospective Study.
Observational study The purpose of this observational study was to understand the quantitative assessment of the degree of degeneration of lumbar facet joints, and to improve the Weishaupt grading system by using gray-scale curve…
- Conditions
- Facet Joint Pain; Low Back Pain, Facet Joints; Degeneration ; Deep Learning ;Artificial Intelligence, Facet Joint Disease
- Trial name
- NCT06786611
- Testing
- MRI
- Where
- China
- Volunteers
- 48 people, healthy volunteers welcome
- Sponsor
- Shanghai Changzheng Hospital
Deep Learning, Artificial Intelegence
Development of a Scoring and Prediction Model for Weaning Success in ARDS Patients Using Ventilation Parameters Combined with Artificial Intelligence and Deep Learning Techniques
This study aims to develop an AI-supported scoring model to optimize the weaning processes of ARDS patients from mechanical ventilation.
- Conditions
- Deep Learning, Artificial Intelegence, ARDS (Acute Respiratory Distress Syndrome)
- Trial name
- NCT06751693
- Where
- Turkey (Türkiye)
- Volunteers
- 25,000 people
- Sponsor
- Bakirkoy Dr. Sadi Konuk Research and Training Hospital
Peripheral Vein, Arterial Wave Reflections
Deep Learning Model for Predicting a Peripheral Venous Waveform-based Pulse Pressure Variation
Pulse pressure variation is a monitoring index that indicates the response to fluid therapy in patients receiving mechanical ventilation, and is used as a reference for patients with unstable hemodynamic conditions.
- Conditions
- Peripheral Vein, Arterial Wave Reflections, Pulse Pressure Variation, Stroke Volume Variation
- Trial name
- NCT06734650
- Testing
- peripheral waveform collection
- Where
- South Korea
- Volunteers
- 150 people, healthy volunteers welcome
- Sponsor
- Seoul National University Bundang Hospital
Deep Learning, Corneal Disease
Artificial Intelligence for Screening of Multiple Corneal Diseases
This study developed a deep learning algorithm based on anterior segment images and prospectively validated its ability to identify corneal diseases.The effectiveness and accuracy of this algorithm was evaluated by sensitivity…
- Conditions
- Deep Learning, Corneal Disease, Screening
- Trial name
- NCT06211218
- Testing
- Cornea diseases diagnosed by artificial intelligence algorithm
- Where
- China
- Volunteers
- 3,000 people
- Sponsor
- Tianjin Eye Hospital
Focus on Developing a Deep Learning Model to Predict the Recurrence Risk of Stage IA Invasive Lung Adenocarcinoma After Sub-lobar Resection
Deep Learning Model to Predict the Recurrence of Stage IA Invasive Lung Adenocarcinoma After Sub-lobar Resection
This study aims to develop a deep learning model based on noncontrast CT images to predict the recurrence risk of stage IA invasive lung adenocarcinoma after sub-lobar resection，which can serve as potential tool to assist…
- Trial name
- DL-Rec-ILA (NCT06659601)
- Where
- China
- Volunteers
- 9 people
- Sponsor
- First Affiliated Hospital of Chongqing Medical University
Artificial Intelligence, Deep Learning
Development and Demonstration of Intelligent Assessment Based on Multi-modal Information Fusion for Tumor Risk and Diagnosis and Treatment
To improve the accuracy of risk prediction, screening and treatment outcome of cancer, we aim to establish a medical database that includes standardized and structured clinical diagnosis and treatment information, image features…
- Conditions
- Artificial Intelligence, Deep Learning, Lung Cancer, Lung; Node
- Trial name
- NCT06653478
- Testing
- No Intervention
- Where
- China
- Volunteers
- 3,000 people, healthy volunteers welcome
- Sponsor
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Endometrial Cancer, Cervical Cancer
Implementation of Surgical Safety and Intraoperative Metastasis Identification Through Deep Learning: Multicentric Video Collection for Minimally Invasive Sentinel Lymph Node Dissection in Uterine Malignancies
The loco-regional metastatic or non-metastatic status of lymph nodes (LN) is critical for the therapeutic management of most cancer patients.
- Conditions
- Endometrial Cancer, Cervical Cancer, Deep Learning, Artificial Intelligence
- Trial name
- LYSE (NCT06619002)
- Testing
- Sentinel lymph node sampling
- Where
- 2 sites in Italy
- Volunteers
- 100 people
- Sponsor
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS