9 results about "Scientific study" patented technology

The application of unilateral or bilateral permanent prostheses to the labium majus in the external genitalia of women for reconstructive and aesthetic purposes may make it appear fuller. The labium majus may lose its fullness and symmetry due to menopause, rapid weight gain and loss, traumas, cancers, and infectious diseases. Aesthetic interventions (e.g., hyaluronic acid filler injection and fat grafting) aiming to provide the labium majus with fullness have become very popular in recent years. The hyaluronic acid filler is used for reconstructive purposes to achieve fullness in labium majus. However, the maximum amount that can be injected is 3 mL, which is often insufficient for the desired outcome and its effect lasts for a maximum of 1 year. Autologous fat grafting is administered by taking 18–120 mL of fat from patients themselves; however, its effect usually lasts 1 to 4 years. The application of a prosthesis will provide labium majus with fullness and this effect will be long-lasting. The outer edge of the prosthesis is convex and the inner edge is concave. In male genitalia, prostheses have been used since 1950 to provide the testicles with fullness. Scientific studies have shown that these prostheses positively affect self-confidence and body perception indices in men.

1. Name of the product in this design: Animal Ventilator. 2. Intended use of this design: for scientific research experiments in clinical medicine and veterinary medicine, respiratory therapy and emergency care for animals, etc. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention discloses a data acquisition and analysis system, belongs to the field of data acquisition and analysis, and provides services and assistance for medical staff and government decision makers by fully utilizing various information including treatment schemes, medication data, inspection data, examination data, image data, epidemiological data and the like. And important support is provided for scientific research of novel coronavirus. The invention is constructed according to the characteristics of pneumovirus, has strong specialty, and connects the epidemiological data with the treatment scheme, examination data, examination data, medication data and image data of the patient according to the identification number or the identity card number of the patient in the data acquisition and analysis process. Public health data and hospital internal information system data are fused, and the COVID-19 virus can be comprehensively known.

Oncology faces a digital chasm in its quest for personalized treatments. Despite the adoption of electronic health records (EHR), most hospitals are ill-equipped for data science research. Embodiments herein describe a continuously learning infrastructure through which multimodal health data are systematically organized and data quality is assessed with the goal of applying artificial intelligence to address unmet clinical needs. Embodiments describe systems and methods for improved cancer prognostics, including by obtaining electronic medical records and performing natural language processing thereon. Additional embodiments apply term frequency inverse document frequency to identify terms that are predictive for cancer survival. Additional embodiments are capable of performing in silico clinical trials based on information comprised in a collection of health records.

The disclosure provides technology for developing evidence-based treatment formulations. In an example implementation an evidence data structure is configured to encode findings of scientific studies in an evidence data structure. The evidence data structure is configured to structurally relate respective studies to corresponding studied diseases and corresponding studied doses of studied nutrients investigated to treat the corresponding studied diseases. In response to receiving an identifier of a disease in a patient corresponding to a first studied disease encoded in the evidence data structure, the disclosed technology can develop one or more treatment formulations for the patient by comparing a quantity of a nutrient contained in selected formulation ingredients to a studied dose of a studied nutrient investigated to treat the first studied disease encoded in the evidence data structure.

The technical scheme of the invention discloses an orthopedics-related drug patent value evaluation system, which is characterized by comprising an orthopedics-related drug evaluation reference standard data acquisition module; an orthopedic related drug patent data integration module; a multi-source data feature construction module; an orthopedic related drug patent comprehensive value evaluation model; and an evaluation and result output module. According to the system disclosed by the invention, traditional patent evaluation indexes such as law, economy and technology can be combined with clinical effects, scientific research, medicine and health policies, supervision systems and the like of orthopedic drugs, so that dynamic evaluation and prospective prediction of the patent values of the orthopedic related drugs are realized. Meanwhile, multi-source data acquisition and an advanced machine learning algorithm are introduced, data scientificity and rationality are improved by using multiple model methods, an evaluation system exclusive to the orthopedics-related pharmaceutical industry is constructed, a closed-loop process of achievement transformation-patent value evaluation is formed, and scientificity, adaptability and practicability of evaluation results are ensured.

The invention provides a CFD and PIV data fusion-based biliary tract flow multi-parameter intelligent prediction method. The method comprises the following steps of constructing a multi-modal data set according to each biliary tract structure model and PIV + CFD joint supervision data corresponding to the biliary tract structure model; coding each biliary tract structure model; training a deep learning model by using each encoded biliary tract structure model and the plurality of key fluid dynamic parameters so as to obtain a trained deep learning model; obtaining a to-be-predicted biliary tract structure model, and obtaining a plurality of key fluid dynamic parameters of internal flow behaviors of the to-be-predicted biliary tract structure model through the trained deep learning model; the method has the beneficial effects that a structure-flow mapping model is constructed, that is, nonlinear mapping from the biliary tract form to the fluid parameters is learned based on a graph neural network or convolutional neural network architecture, so that a rapid online prediction mechanism is realized, and clinical personalized pathological analysis or clinical medical science research and evaluation requirements are facilitated.

The application discloses a small-scale perception enhanced human posture estimation method, which draws on the shortcomings of previous models, optimizes the performance of small-scale targets, selects a more accurate Top-down structure, discards the heat map representation method, and uses SimCC based on one-dimensional vector representation to more accurately locate the key points of small-scale targets, and a TAA module is further proposed based on the SimCC-baseline, and the effectiveness of the TAA module is verified through an ablation experiment, and finally good results are achieved in the overall AP. The performance of small-scale targets greatly limits the improvement of the overall accuracy of the model, and most of the previous networks ignore this point, so the SSA-Net has practical application value and scientific research value.

This invention discloses the application of ergothioneine as a biomarker in the preparation of diagnostic products for rheumatoid arthritis (RA), belonging to the biomedical field. This invention uses high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS / MS) to detect the content of ergothioneine in samples, thereby achieving the diagnosis of RA in patients. Analysis showed that the area under the curve (AUC) of ergothioneine in distinguishing between the RA and OA groups was 0.7880, while the AUC in distinguishing between the RA and HC groups was 0.8804, indicating its good diagnostic value. This invention provides a novel biomarker for RA, offering a basis for further examination by clinicians, and has significant scientific research and clinical application value, providing a practical means for diagnosing RA.