Medical algorithm (51 résultats)
Algorithm For Management Of Atrial Fibrillation: Proceedings Of The Prairie Cardiovascular Center, Ltd., 1995 Annual Symposium At Memorial Medical Center, Springfield, Illinois
Schneider, Joel A.; Katholi, Richard E.; Woods, W. Thomas (Editors)
Edité par Greendell Publishing, Decatur, Illinois, 1996
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Langue : anglais
Edité par Independently published, 2026
Série : Livre 8 sur 13 - The Unreliable Witness Perception Series
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Taschenbuch. Etat : Neu. Classification of Medical Data with HTM Cortical Learning Algorithms | Examination of the proposed HTM algorithm with real medical data | Thomas Muders | Taschenbuch | 88 S. | Englisch | 2013 | AV Akademikerverlag | EAN 9783639491920 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher…Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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paperback. Etat : New. Paperback.Pub Date:2021-12-01 Pages:163 Language:Chinese Publisher:Tsinghua University Press Medical Surgery Resource Scheduling Model and Algorithm is based on optimal scheduling theory. and takes hospital operating room and other related resources as the research object. Operations research. systems engi…neering. statistics and other methods have established a set of theories and methods for optimal scheduling of surgical resources. The main contents include operating room operation manageme.
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Taschenbuch. Etat : Neu. Boundary Detection in Medical Images | Boundary Detection in Medical Images Using Edge Following Algorithm Based on Intensity and Texture Gradient Features. | Swapnali Karole (u. a.) | Taschenbuch | 84 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783330009448 | Verantwortliche Person für… die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Taschenbuch. Etat : Neu. Canny Operator Based DRLSE Algorithm for Medical Image Segmentation | Biomedical Image Processing | Dipali Dhake (u. a.) | Taschenbuch | 76 S. | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202520324 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078…Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Taschenbuch. Etat : Neu. IMPLEMENTING RC5 ENCRYPTION ALGORITHM | THROUGH A WEB BASED MEDICAL CONSULTATION SYSTEM | Osama Khashan | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639243239 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbiete…r: preigu.
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Taschenbuch. Etat : Neu. Topology Simplification Algorithm for Segmentation of Medical Scans | Application to the Segmentation of Brain MRI Images | Sylvain Jaume | Taschenbuch | 132 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838317625 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen… 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
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Taschenbuch. Etat : Neu. Novel Algorithm for Medical Image Compression | The way for advanced medical imaging | Robinson Paul (u. a.) | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786204955131 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]p…reigu[dot]de | Anbieter: preigu.
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Taschenbuch. Etat : Neu. Fuzzy C-Means Clustering for Clinical Knowledge Discovery in Databases | Optimizing FCM using Genetic Algorithm for use by Medical Experts in Diagnostic Systems and Data Integration with SchemaSQL | Latha Parthiban | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639341430 | Verantwortliche Per…son für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -High Quality Content by WIKIPEDIA articles! A medical algorithm is any computation, formula, statistical survey, nomogram, or look-up table, useful in healthcare. Medical algorithms include decision tree approaches to healthcare treatme…nt (i.e., if symptoms A, B, and C are evident, then use treatment X) and also less clear-cut tools aimed at reducing or defining uncertainty. Medical algorithms are part of a broader field which is usually fit under the aims of medical informatics and medical decision making. Medical decisions occur in several areas of medical activity including medical test selection, diagnosis, therapy and prognosis, and automatic control of medical equipment. In relation to logic-based and artificial neural network-based medical expert systems, which are also computer applications to the medical decision making field, algorithms are less complex in architecture, data structure and user interface. Medical algorithms are not necessarily implemented using digital computers. 92 pp. Englisch.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Medical image segmentation is one of the most important parts of clinical diagnostic tools.The distance regularization effect eliminates the need for reinitialization and thereby avoids its induced numerical errors. DRLSE in which the r…egularity of the level set function is intrinsically maintained during the level set evolution. The level set evolution is derived as the gradient flow that minimizes energy functional with a distance regularization term and an external energy that drives the motion of the zero level set toward desired locations. The distance regularization term is defined with a potential function such that the derived level set evolution has a unique forward-and-backward (FAB) diffusion effect, which is able to maintain a desired shape of the level set function. Canny operator used to determine the edges and edge directions. Then used a new variation level set formulation that is DRLSE .The algorithm combines the advantages of canny operator which can orient the boundary accurately and the idea that DRLSE algorithm continuously evolves the boundary in image space. Compared different types of Color medical images by using various parameters. 76 pp. Englisch.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In recent days the health industry has collected vast amounts of patient data, which unfortunately is not produced in order to give some hidden information, and thus to make effective decisions, which are connected with the base of the…patient's data and are subjected to data mining. This work has developed a Decision Support in Heart Disease Prediction System (HDPS) using data mining modelling techniques namely Naïve Bayes and K-means, which are one of the most popular techniques. Using of medical data such as age, sex, blood pressure, blood sugar levels, chest pain etc. we can predict the likelihood of the patient. Most hospitals today use decision-support systems, but to get the results of the disease are largely limited i.e., Determine based on gender, marital status and who have been treated for heart failure. Solutions are always made in a hospital based on intuition and experience of doctors, and not on the rich knowledge data that are hidden in the database. This process leads to undesirable biases, errors and unnecessary health care costs, which affects the quality of services provided to patients.This will help make the diagnostic process more objective and more reliable. 56 pp. Englisch.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 56 pp. Englisch.
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! A medical algorithm is any computation, formula, statistical survey, nomogram, or look-up table, useful in healthcare. Medical algorithms include decision tree approaches to healthcare treatment (i….e., if symptoms A, B, and C are evident, then use treatment X) and also less clear-cut tools aimed at reducing or defining uncertainty. Medical algorithms are part of a broader field which is usually fit under the aims of medical informatics and medical decision making. Medical decisions occur in several areas of medical activity including medical test selection, diagnosis, therapy and prognosis, and automatic control of medical equipment. In relation to logic-based and artificial neural network-based medical expert systems, which are also computer applications to the medical decision making field, algorithms are less complex in architecture, data structure and user interface. Medical algorithms are not necessarily implemented using digital computers.
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Finding the correct boundary in noisy images is still a difficult task. This paper introduces a new edge following technique for boundary detection in noisy images. Utilization of the proposed technique is exhibited via its application to va…rious types of medical images. Proposed technique can detect the boundaries of objects in noisy images using the information from the intensity gradient via the vector image model and the texture gradient via the edge map. In this technique magnitude and directions, both are considered while calculating vector information. The vector details of image give idea about edge. Texture details are used to derive edge map. Not only magnitude of image but direction is also considered so gives better result as compared to previous methods.
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In recent days the health industry has collected vast amounts of patient data, which unfortunately is not produced in order to give some hidden information, and thus to make effective decisions, which are connected with the base of the patie…nt's data and are subjected to data mining. This work has developed a Decision Support in Heart Disease Prediction System (HDPS) using data mining modelling techniques namely Naïve Bayes and K-means, which are one of the most popular techniques. Using of medical data such as age, sex, blood pressure, blood sugar levels, chest pain etc. we can predict the likelihood of the patient. Most hospitals today use decision-support systems, but to get the results of the disease are largely limited i.e., Determine based on gender, marital status and who have been treated for heart failure. Solutions are always made in a hospital based on intuition and experience of doctors, and not on the rich knowledge data that are hidden in the database. This process leads to undesirable biases, errors and unnecessary health care costs, which affects the quality of services provided to patients.This will help make the diagnostic process more objective and more reliable.
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Medical image segmentation is one of the most important parts of clinical diagnostic tools.The distance regularization effect eliminates the need for reinitialization and thereby avoids its induced numerical errors. DRLSE in which the regula…rity of the level set function is intrinsically maintained during the level set evolution. The level set evolution is derived as the gradient flow that minimizes energy functional with a distance regularization term and an external energy that drives the motion of the zero level set toward desired locations. The distance regularization term is defined with a potential function such that the derived level set evolution has a unique forward-and-backward (FAB) diffusion effect, which is able to maintain a desired shape of the level set function. Canny operator used to determine the edges and edge directions. Then used a new variation level set formulation that is DRLSE .The algorithm combines the advantages of canny operator which can orient the boundary accurately and the idea that DRLSE algorithm continuously evolves the boundary in image space. Compared different types of Color medical images by using various parameters.
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In recent days the health industry has collected vast amounts of patient data, which unfortunately is not produced in order to give some hidden information, and thus to make effective decisions, which are connected with the base of the patie…nt's data and are subjected to data mining. This work has developed a Decision Support in Heart Disease Prediction System (HDPS) using data mining modelling techniques namely Naïve Bayes and K-means, which are one of the most popular techniques. Using of medical data such as age, sex, blood pressure, blood sugar levels, chest pain etc. we can predict the likelihood of the patient. Most hospitals today use decision-support systems, but to get the results of the disease are largely limited i.e., Determine based on gender, marital status and who have been treated for heart failure. Solutions are always made in a hospital based on intuition and experience of doctors, and not on the rich knowledge data that are hidden in the database. This process leads to undesirable biases, errors and unnecessary health care costs, which affects the quality of services provided to patients.This will help make the diagnostic process more objective and more reliable.
