View clinical trials related to Artificial Intelligence.
Filter by:Digestive endoscopy center of the second affiliated hospital of medical college of zhejiang university and engineers of naki medical co., ltd. in Hong Kong independently developed an ai-assisted diagnostic model of digestive endoscopy in the early stage, namely the deep learning model.The deep learning model through the early stage of the study, is able to identify lesions of digest tract.The sensitivity for the diagnosis of some diseases, such as colon polyps, is 99%. On the one hand, this auxiliary diagnostic model can guide endoscopic examination for beginners; on the other hand, it can improve the detection rate of lesions and reduce the rate of missed diagnosis; on the other hand, the overall operating efficiency of the endoscopic center is improved, which is conducive to the quality control of endoscopic examination. Now the AI-assisted diagnostic model has been further improved, and it is planned to carry out further clinical verification in the digestive endoscopy center of our hospital. It is connected to the endoscopic system of our hospital and used simultaneously with the existing image-text system of endoscopy to compare the practicability, sensitivity and specificity of AI-assisted diagnosis model in the diagnosis of digestive tract diseases, and focus on the quality control of endoscopic examination.
The standard treatment for non-operative cervical cancer is concurrent external radiation therapy and chemotherapy followed by brachytherapy. During the period of radiotherapy, organ movement and tumor shrinkage may lead to insufficient or excessive radiation dose for the tumor and organs at risk. Adaptive radiotherapy can use images information acquired during treatment as feedback to reduce errors. Total 122 cases of cervical cancer with stage IB2-IVA will be randomly enrolled. Concurrent external volumetric rotational intensity modulated radiotherapy and chemotherapy followed by image-guided adaptive brachytherapy is the treatment strategies of control group patients. Concurrent adaptive external volumetric rotational intensity modulated radiotherapy and chemotherapy followed by image-guided adaptive brachytherapy is the treatment strategies of experimental group patients. CT repositioning will be performed after 15fractions of external radiotherapy, then new target volume will be contoured and new radiotherapy plan will be formulated with the assistance of artificial intelligence program. New radiotherapy plan will be performed from the 17th fraction external radiotherapy. Information on side effects, survival, dosimetry, imaging, clinical features, and cost-effectiveness will be collected. The statistical analysis is as follows, First is the difference in grade 3 side effects between the two groups. Second is 2-year PFS and OS differences between the two groups. Third is relationship between dosimetric differences and prognosis. Fourth one is to analyze the prognostic and predictive factors of adaptive radiotherapy from the patient's clinical characteristics, Positron emission tomography-computed tomography(PET/CT), Magnetic Resonance Imaging(MRI) and other multimodal information. Fifth is cost-benefit analysis of Artificial Intelligence(AI).
Probe-based confocal laser endomicroscopy (pCLE) is an endoscopic technique that enables real-time histological evaluation of gastrointestinal mucosa during ongoing endoscopy examination. It can predict the classification of Colorectal Polyps accurately. However this requires much experience, which limits the application of pCLE. The investigators designed a computer program using deep neural networks to differentiate hyperplastic from neoplastic polyps automatically in pCLE examination.
At present, Watson for Oncology has been applied in 14 countries worldwide, including China, the United States, Holland, Thailand, India, Korea, Poland, Slovakia and Bangladesh. In a double-blind study involving 362 patients in India, treatment recommendations from Watson for Oncology (WFO) performed a high degree of consistency with their multidisciplinary tumor board. The investigators would recruit cancer patients diagnosed as lung cancer, breast cancer, gastric cancer, colon cancer， rectal cancer，cervical cancer or ovarian cancer according to the criteria of Watson for Oncology ，using the updated version of Watson for Oncology to explore the concordance of therapeutic regimen between WFO and physicians in the Affiliated Hospital of Qingdao University.
the algorithm of artificial intelligent to diagnose myocardial infarction through prior surgery Electrocardiogram was established. The accuracy of using artificial intelligent to diagnose acute ST-segment elevation myocardial infarction and judge criminal vascular was evaluated.