medical algorithm (45 résultats)

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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.

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.

Taschenbuch. Etat : Neu. Medical Diagnosis of Cardiac Disease using Naïve Bayes Algorithm | Domala Kishore Babu (u. a.) | Taschenbuch | 56 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786136524337 | Verantwortliche Person für die EU: LAP Lambert Academic Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.

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.

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 | Anbieter: preigu.

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]preigu[dot]de | Anbieter: preigu.

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 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. 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 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. 92 pp. Englisch.

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 regularity 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.

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.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 56 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 132 pp. Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Babu Dr.Domala KishoreDr.D KISHORE BABU received Ph.D Doctorate in Computer Science and Engineering from JNTU,Kakinada Andhra Pradesh. He is currently working as professor in the department of computer science and engineering in Ins.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Medical imaging has started to take advantage of digital technology, opening the way for advanced medical imaging and teleradiology. Medical images, however, require large amounts of memory. At over 1 million bytes per image, a typical hospital needs a staggering amount of memory storage of over one trillion bytes per year and transmitting an image over a network, even the promised superhighway could take minutes which is too slow for interactive teleradiology. This calls for image compression to reduce significantly the amount of data needed to represent an image. To meet this challenge, we developed a hybrid compression scheme that provides almost lossless compression with easily hardware realizable due to its simplicity having the better results of PSNR, MSE, and COC. 96 pp. Englisch.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Medical data analysis is an important task and the lives of patients often depend on it. However, the analysis itself is often repetitive and time-consuming. Algorithms for this tasks need to have a very high success rate and need to be understandable to work with their parameters. This work will examine a general algorithm for various data types: The Hierarchical Temporal Memory learning algorithm (HTM). It is proposed to be very flexible and to work on any kind of data. The HTM algorithm was implemented and tested with two datasets: Medical images on the one hand and ECG recordings on the other. The proposed algorithm is only presented with a limited data input method and a small input size by its authors. These properties needed to be modified to support a bigger amount of data and also various data types. This is done with an own implementation of the HTM algorithm. The results of this work are analyzed and thoughts and ideas for future development are given at the end.

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 various 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.

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.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jaume SylvainSylvain Jaume graduated in 2004 with a PhD in Electrical Engineering from Universite catholique de Louvain (UCL). From 2005 to 2009 he worked at Kitware Inc. and Siemens Corporate Research USA. He now holds a dual appoin.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Medical imaging has started to take advantage of digital technology, opening the way for advanced medical imaging and teleradiology. Medical images, however, require large amounts of memory. At over 1 million bytes per image, a typical hospital needs a stag.