43 results about "Nomogram" patented technology

A method and system for calculating ocular incision positions to address astigmatism in an eye. The present design includes providing biometric information, determining an incision location:and angle based on the biometric information and a nomogram such as a Donnenfeld nomogram, relating astigmatism conditions and incision conditions, and presenting the incision location and angle to a user, such as via a graphical user interface. The design is intended to be employed on a general purpose computer and the utility employed, an LRI (Limbal Relaxation Incision) calculator utility may be executed to compute the desired results based on a set of eye measurement inputs.

Decades of investigations were focused on finding “gold standard” for evaluation of plasma dilution and osmolality, blood loss evaluation and prediction of bleeding or transfusion induced changes in hematocrit and hemoglobin concentration. Addressing deficiencies of existing methods, the current invention created new combined mathematical-physiological model applicable to manually operated nomograms and software in medical monitors. The mathematical model HBS Trends is used in blood transfusion and infusion therapy nomogram—HBS Nomogram—which is based on blood hemoglobin concentration and hematocrit. It is also an easy and practical tool for recording and dynamical interpretation of plasma osmolality, blood hemoglobin concentration, hematocrit and mean corpuscular hemoglobin concentration. The HBS Nomogram is a practical system for organizing blood test results in a patient's medical records. It can be used alone or, in line with existing guidelines for infusion and transfusion therapy making them more practical, cost effective and time saving in decision making.

The present invention relates to the aerodynamic design of moving blades, pertaining to later stages of axial steam turbines where the inlet flow is non-uniform over the blade height. The claim made herein is a set of six invented transonic blade profiles which can be used to develop various type of 3D twisted blades for axial steam turbine. The aerodynamic characteristics of these 6 base profiles are evaluated herein as a function of stagger angle and pitch/chord ratios. The aerodynamic characteristics invented herein is for a group of six base profiles which are to be used for creation of three dimensional blades made of varying cross-sections and twisted over the blade height while ensuring the centers of gravity of these sections lie in a radial line. Each of the blades, sections from hub to tip is twisted differently from desired outlet angle. Thus the nomograms can be used to develop quickly a first level design of a 3D blade making use of 2D base profiles whose performance is shown in the form of nomograms.

The invention relates to the technical field of safety assessment of pressure vessels with defects, in particular to a method for determining defects of a multilayer binding vessel by acoustic emission. Acoustic emission detection is carried out according to the structural features of the vessel so as to determine the defects. The method comprises the following steps of: (1) activating defects under overpressure, synchronously monitoring the defects in the vessel by acoustic emission, determining the overpressure during activating the defects and positioning the activated defect parts; (2) simplifying activated defects which cannot be determined by ultrasonic phased array rechecking according to the development direction of an acoustic emission event; (3) obtaining the stress distribution of the simplified defect parts by utilizing finite element calculation or a nomogram obtained on the basis of the finite element calculation so as to ensure that the simplified defects are on a maximum stress wall surface vertical to the simplified defects; and (4) based on defect simplification conditions, the stress of the simplified defect parts and material fracture toughness, reversely reasoning nominal initial sizes and tolerance sizes of the defects according to a fracture mechanics theory. The method has reliable detection means and reasonable simplification process and provides a foundation for the safety assessment of multilayer binding vessels.

The present invention provides a system for accurately predicting the prognosis of gastric cancer patients. The system is based on the Nomogram prognostic prediction model constructed by the present invention. Compared with the traditional TNM staging system, the system has high accuracy, individualized prediction, and conforms to Prognostic features of gastric cancer with Chinese characteristics.

The invention relates to a prognosis prediction model for patients with hilar cholangiocarcinoma. Specifically, the present invention provides a carrier for postoperative prognosis of patients with hilar cholangiocarcinoma, which is used to calculate risk factor scores and patient 3-year survival rate Y3 and/or 5-year survival rate Y5; Wherein, the risk factors include at least the patient's age X, and the fraction of the patient's age, the 3-year survival rate and the 5-year survival rate satisfy the relationship described in the article. The present invention systematically investigates the clinical and pathological characteristics that affect the prognosis of patients with hilar cholangiocarcinoma, and the effect of patients after surgical treatment, evaluates the key factors that affect the survival and prognosis of patients with hilar cholangiocarcinoma, and establishes a method for patients with hilar cholangiocarcinoma. The list of survival prognosis is used to evaluate the 3-year and 5-year survival rate of patients after surgery, and to screen out high-risk groups for intervention to improve the survival prognosis of patients.

The invention discloses a prediction method and system for latent N2 lymph node metastasis of surrounding NSCLC, and the method comprises the steps: collecting the imaging omics features and clinicalpathological features of a primary lesion in a clinical staging N1 stage and a pulmonary portal lymph node at the same side in PET-CT; establishing a Nomogram model by utilizing the imaging omics characteristics and the clinical pathological characteristics; scoring a patient in clinic based on the Nomogram model to obtain a corresponding risk probability coefficient; and utilizing the risk probability coefficient to predict and evaluate the probability of occurrence and transfer of the latent N2 lymph node. According to the invention, the image omics features are extracted through the convolutional neural network, so the accuracy and reliability of the classification or prediction of the imaging omics are further improved; the Nomogram based on the imaging omics can provide personalized information about whether lymph node metastasis exists or not according to the actual situation of each non-small cell lung cancer patient more visually and more accurately, so the unnecessary medicalexamination and operation of the patient are avoided.

A 3-gene prognostic panel has been identified that together accurately predicted the outcome of low Gleason score prostate tumors as either truly indolent or at a high risk of becoming aggressive. The 3-gene prognostic panel was validated on independent cohorts confirmed its independent prognostic value, as well as its ability to improve prognosis with currently used clinical nomograms. Expression of the 3-gene prognostic panel was determined by quantifying mRNA or protein encoded by the panel (collectively referred to as “prognostic biomarkers”). The prognostic biomarkers were discovered to be up-regulated in indolent tumors and down-regulated in aggressive forms of prostate cancer.

The invention belongs to the field of biological medicine and molecular biology, relates to establishment and application of a disease-related factor scoring parameter analysis model, in particular toa progression appendicitis nomogram prediction system, which comprises model software, and is characterized in that the model software consists of a back-end database, a model algorithm and a front-end graphical user interface; the model algorithm is realized through computer programming of a scoring analysis model, a predictor is analyzed through logistic regression, and a Nomogram is adopted toestablish the model; the predictor comprises a fibrin degradation product, C-reactive protein and Na < + >. The established Nomogram diagnosis nomogram based on multivariate logistic regression analysis can help determine the risk index of the appendicitis in the progression stage according to the score in clinical practice; furthermore, the method can be used for analyzing scoring parameters ofserum markers of the progressive appendicitis and the early appendicitis, and is beneficial to identification of the progressive appendicitis and the early appendicitis.

The invention provides a constructing method of a practical model for evaluating hepatitis B hepatopathy NK cell functions. The method includes the steps of firstly, grouping hepatitis B hepatopathy patients into chronic hepatitis active stage patients and chronic hepatitis inactive stage patients, detecting the frequency distribution of peripheral blood NK cells and subsets of the peripheral blood NK cells through the flow cytometry, and carrying out comparison; secondly, detecting the level of the peripheral blood NK cells and cytokines secreted by the subsets of the peripheral blood NK cells through the flow cytometry, and carrying out comparison; thirdly, collecting clinical indexes of the patients, and conducting correlation analysis on the clinical indexes and NK cell immunity evaluation indexes; fourthly, using NK cell function activeness and NK cell hypofunction as the feedback variables, and screening out indexes correlated to NK cell function states of the patients through a multi-variable logistic regression model; fifthly, constructing the evaluating model; sixthly, constructing a nomogram.

A system and method are provided for simulating a Laser Induced Optical Breakdown (LIOB) protocol to establish a surgical LIOB treatment for a patient. In the system, a library of finite element models characterizing various visual defects in corneas are programmed into a computer. Further, a library of nomograms indicating specific LIOB protocols for correcting respective visual defects are programmed into the computer. As a result, a model and a corresponding nomogram may be selected in view of a patient's diagnostic information. Further, the selected model may be individualized with the diagnostic information to more precisely characterize the patient's visual defects. Thereafter, the computer simulates the indicated LIOB protocol on the individualized model in order to achieve a desired corneal configuration. When the desired corneal configuration is achieved, the final treatment plan may be determined.

The invention belongs to the technical field of operation risk diagnosis and prediction models, and discloses a thoracotomy risk diagnosis and prediction model in thoracoscope lung cancer resection and a construction system. The construction system of the thoracoscope lung cancer resection transfer thoracotomy risk diagnosis and prediction model comprises a data acquisition module, a risk diagnosis model construction module, a data preprocessing module, a data fusion module, a data set training module, a model verification and optimization module, a central control module, a risk diagnosis and prediction module, a data storage module, and an update display module. According to the method, on the basis of tens of thousands of data of the thoracic surgery department of the West China hospital, a risk diagnosis and prediction model for lung cancer thoracoscopic surgery transfer thoracotomy is established through machine learning algorithms such as classical logistic regression, an artificial neural network and a random forest, and after some indexes are input on the basis of an established webpage version nomogram, the size of the chest opening risk in the thoracoscope lung cancer resection can be predicted on line.

An electronic nomogram includes an image data storing unit for storing nomogram image data of a coordinate plane having a first axis and a second axis; an instruction receiving unit for receiving an instruction specifying a position of a point graphic displayed on a nomogram; a numerical value acquiring unit for acquiring first and second numerical values; a calculation unit for calculating a value of a calculation result of a predetermined function that uses as arguments the first and second numerical values; an image generation unit for generating point graphic image data at a position specified by the received instruction and generating as calculation result image data, image data of the value of the calculation result of the function; and an image display unit for displaying the nomogram image data, the point graphic image data and the calculation result image data.

The invention discloses a method for predicting preeclampsia onset risk in early pregnancy, and relates to the technical field of preeclampsia onset risk prediction. The method comprises the following steps: feature information of a body sample of a safe pregnant woman being obtained in advance; performing multi-factor Logistic regression analysis on the obtained feature information of the female subject sample to establish a prediction model, and representing the prediction model by a nomogram; and performing individualized prediction of preeclampsia based on the nomogram. According to the method, the prediction performance is excellent, the column diagram of the prediction model is simple and clear, powerful support can be provided for clinical decision making of clinicians, intervention measures are taken as soon as possible for pregnant women with the high preeclampsia attack risk, very important prenatal and postnatal care significance is achieved, the occurrence risk of intrauterine growth limitation of premature infants and fetuses can be reduced. Economic and mental burdens of society and families are reduced.

The invention provides a method for predicting a diopter adjustment value (Nomogram value) in an SMILE (Small Incision Lenticule Extraction) refractive surgery based on a Softmax regression algorithm.The method comprises the steps that screening, discretization and other pretreatment are carried out on original data, the discretized Nomogram value serves as a category label; a Softmax hypothesisfunction and parameter matrixes of the Softmax hypothesis function are initialized, and a gradient descent method is utilized to obtain the parameter matrix minimizing a cost function; the optimal parameter matrix is substituted into the Softmax hypothesis function to obtain a regression model; and the regression model is utilized to predict a Nomogram reference value applied in an SMILE surgery plan. The method can predict the Nomogram value of a new case more accurately and more stably within the range of the error that the SMILE surgery allows, and provide reference and help for doctors tomake surgery plans.

The invention discloses a construction method of a chronic hepatitis B cirrhosis prediction model and a chronic hepatitis B cirrhosis prediction method. The existing liver fibrosis and liver cirrhosis prediction method cannot be widely applied due to the cost problem, and the prediction effect is not accurate enough. A construction method of a chronic hepatitis B cirrhosis prediction model and a chronic hepatitis B cirrhosis prediction method are disclosed, an ROI is delimited in a right portal vein level CT plain scan image of a liver, the Chinese meaning of the ROI is an interested area, radiomics features are extracted in the delimited ROI, and the extracted radiomics features comprise first-order statistics, texture features and wavelet transform; selecting radiomics characteristics by using repeatability between observers and repeatability between the observers and lasso regression; establishing a preliminary image omics model by using a support vector machine, and combining a pure image omics model and the serum index independent prediction factor to construct a prediction model based on a nomogram of image omics. According to the method, non-invasive liver cirrhosis prediction can be carried out by combining the CT image with the serum index independent prediction factor.

The invention provides a system for precisely predicting prognoses of patients with gastro-entero-pancreatic neuroendocrine tumors. The system is based on a Nomogram prognosis prediction model constructed by the invention; the system has the characteristics of high precision and individualized prediction, and conforms to gastro-entero-pancreatic neuroendocrine tumors prognosis prediction with Chinese characteristics compared with a traditional TNM (Tumor-node-metastasis) staging system. Meanwhile, the system has good guidance effect on selection of patient individualized treatment strategies,design of new drug clinical tests and standardization of consistency of the enrolled patients in clinical work.