View clinical trials related to Diagnosis.
Filter by:The primary goal of this study is to estimate the effectiveness of a medical decision support system based on artificial intelligence in the endoscopic diagnosis of benign tumors. Researchers will compare Adenoma detection rate between "artificial intelligence - assisted colonoscopy" and "conventional colonoscopy" groups to evaluate the clinical effectiveness of artificial intelligence model.
The goal of this prospective, diagnostic observational study is to learn about how imaging based markers for components of liver disease appear in children with obesity. It aims to determine whether the imaging markers (ultrasound and MRI) for liver disease can be tools to improve diagnostics for liver affection in children with obesity and to ascertain how the markers are related to multiple clinical measures, for example BMI and serology measure, and treatment effects over time.
This clinical trial was designed as a prospective, multicenter, multi-reader multi-case (MRMC), superiority, parallel-controlled study. Participants who met the trial criteria and signed the informed consent form were enrolled. The trial group involved diagnoses of caries on panoramic radiographs using an artificial intelligence-assisted diagnostic system, while the control group involved diagnoses made by dental practitioners specializing in operative dentistry and endodontics with five years of experience, who interpreted oral panoramic radiographs to determine the presence and severity of caries.
Gestational diabetes mellitus (GDM) is a condition that can affect pregnant women during pregnancy and may cause complications for the mother and the baby. Therefore, early and accurate detection is necessary to provide the woman and the baby with better health outcomes. Currently, the most commonly used criteria to detect GDM is the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criterion. However, there is a suggestion that it results in over-diagnosis of GDM, and newer methods of diagnosis have been proposed. One such proposal is to have more than a binary outcome of assessment of dysglycemia in pregnancy. The investigator group created this criterion known as the National Priorities Research Program (NPRP) criterion. This clinical trial compares the IADPSG to the NPRP criteria in pregnant women in Qatar to determine if this newer method mitigates overdiagnosis and more accurately identifies women at risk of complications.
After neoadjuvant therapy, the primary lesion in breast cancer patients may experience tumor regression, which increases the difficulty of distinguishing between breast cancer and adjacent tissues. Raman spectroscopy is a form of scattering spectroscopy, which offers rapid and sensitive analysis, delivering detailed biochemical information and molecular signatures of internal molecular components within the sample. This study aims to discern between cancer and adjacent tissues after neoadjuvant therapy in breast cancer patients using label-free Raman spectroscopy.
The aim of this study is to propose an intelligent diagnosis and treatment system for for pelvic floor dysfunction in elderly women. The main question it aims to answer: 1) How can the investigators find out early if older women have different pelvic floor muscle functions? 2）How can the investigators give personalized treatment plans based on differences in pelvic floor function? Participants will be assigned different training programs by the system. The investigators will compare the treatment effects and costs of older women with pelvic floor dysfunction using and not using the system. All the participants will be offered examinations for pelvic floor function and different treatments. All examinations and treatments are non-invasive.
The aim of this Study is to collect radiologist feedback to support the further development and improvement of the imaging modes implemented on the embedded software in the SuperSonic® Ultrasound System (including the probe).
This study aims to validate a novel antibiotic susceptibility test (InSignia) for gonorrhoea in patient clinical samples. The hypothesis is that the InSignia test will be able to detect transcriptional responses after incubation in antibiotic for susceptible strains and not resistant strains. Furthermore, this study will also add to our understanding on the performance of this test in various clinical specimens.
Non-small cell lung cancer (NSCLC), occupying a disquieting position as the second most prevalent and deadliest neoplasm worldwide, afflicts an estimated 30% of its patients with intracranial metastatic spread. Among these, leptomeningeal metastasis (LM) is an exceptionally surreptitious and perilous manifestation, often evading timely and accurate diagnosis. The clinical landscape is further complicated by the presence of patients who, due to various reasons, are unable to undergo lumbar puncture, a procedure crucial for the investigation of LM. Moreover, even when cerebrospinal fluid (CSF) analysis via conventional cytological and immunohistochemical methods is attempted, a definitive diagnosis of LM may remain elusive in a subset of cases. Intrathecal chemotherapy, particularly via the administration of pemetrexed, which has demonstrated both notable efficacy and an acceptable safety profile when delivered directly into the cerebrospinal space, constitutes a cornerstone of treatment for NSCLC-LM. Despite its importance, the lack of robust, validated biomarkers to gauge the therapeutic response to such interventions represents a significant knowledge gap. This deficit is compounded by the inherent challenges associated with CSF samples, including their limited availability and the suboptimal sensitivity and high resource demands of current ctDNA assessment techniques. To address these pressing diagnostic and monitoring needs in NSCLC-LM management, the investigator proposes a forward-looking, non-interventional clinical study harnessing the power of cutting-edge proteomic technologies. These platforms, characterized by their high throughput, exquisite sensitivity, and minimal sample volume requirements, offer a promising avenue for elucidating the intricacies of chemotherapy response in intrathecal therapy. The study aims to provide valuable insights into improving diagnostic accuracy for LM in NSCLC patients and to establish a more rigorous framework for assessing treatment efficacy in individuals undergoing intrathecal chemotherapy, ultimately contributing to enhanced patient care and personalized therapeutic strategies.
72 adult patients who underwent lumbar spine anteroposterior DXA and QCT examinations at Qianfoshan Hospital in Shandong Province from January 2019 to December 2022 were selected, with an interval of no more than 3 months between the two examinations for the same patient. 1. Record the patient's age, gender, height, and weight; Review the patient's past medical history (especially whether there is a history of brittle fractures, whether there is a history of using drugs that affect bone metabolism, etc.). 2. Retrieve the bone density values of the anterior lumbar vertebrae 1 to 4 measured by GE Healthcare Lunar Prodigy dual energy X-ray absorptiometry from the database, and take the average (DXA bone density value). According to the diagnostic criteria of the Diagnosis and Treatment Guidelines for Primary Osteoporosis (2022), determine whether the patient has normal bone mass, decreased bone mass, or osteoporosis. 3. Identify the lumbar spine bone density values (QCT bone density values) measured by the GE Gemstone CTHD750 CT instrument from the database. According to the diagnostic criteria of the Chinese Quantitative CT (QCT) Diagnosis Guidelines for Osteoporosis (2018), determine whether the patient has normal bone mass, decreased bone mass, or osteoporosis. 4. Statistical analysis was conducted on the normal bone density, bone loss, and number of osteoporosis diagnosed by DXA and QCT respectively, in order to explore the differences in the detection rates of osteoporosis between these two monitoring methods. The data was analyzed and processed using SPSS 21.0 statistical software, and the count data was expressed as a rate (%) χ 2-test, P<0.05 indicates statistically significant difference; Explore whether the difference in detection rates between the two is related to factors such as weight; Calculate the detection rates of osteoporosis using two detection methods in patients who have experienced brittle fractures, and preliminarily determine which detection method is more accurate in determining osteoporosis.