標題: Titlebook: Computational Intelligence Processing in Medical Diagnosis; Manfred Schmitt,Horia-Nicolai Teodorescu,Lakhmi C. Book 2002 Springer-Verlag B [打印本頁] 作者: 自由 時間: 2025-3-21 19:08
書目名稱Computational Intelligence Processing in Medical Diagnosis影響因子(影響力)
書目名稱Computational Intelligence Processing in Medical Diagnosis影響因子(影響力)學科排名
書目名稱Computational Intelligence Processing in Medical Diagnosis網(wǎng)絡公開度
書目名稱Computational Intelligence Processing in Medical Diagnosis網(wǎng)絡公開度學科排名
書目名稱Computational Intelligence Processing in Medical Diagnosis被引頻次
書目名稱Computational Intelligence Processing in Medical Diagnosis被引頻次學科排名
書目名稱Computational Intelligence Processing in Medical Diagnosis年度引用
書目名稱Computational Intelligence Processing in Medical Diagnosis年度引用學科排名
書目名稱Computational Intelligence Processing in Medical Diagnosis讀者反饋
書目名稱Computational Intelligence Processing in Medical Diagnosis讀者反饋學科排名
作者: negotiable 時間: 2025-3-21 21:24 作者: crescendo 時間: 2025-3-22 01:47 作者: Eosinophils 時間: 2025-3-22 05:11 作者: 戰(zhàn)役 時間: 2025-3-22 10:29
Generalizations and Extensions,ent an integrated approach involving both intelligent data analysis and knowledge acquisition from experts that supports the development and validation of operational protocols. The aim is to lower development cost through the use of machine learning and at the same time ensure high quality standard作者: 食料 時間: 2025-3-22 13:04
Generalizations and Extensions,pic in medical informatics. Here we present a method for prognosis of temporal courses, which combines temporal abstractions with Case-Based Reasoning. The method was originally generated for multiparametric time course prognosis of the kidney function. Recently, we have started to apply the same id作者: 食料 時間: 2025-3-22 18:11
Renewal Processes and Random Walks,suitable bedside decision support are needed to cope with this flood of information. A basic task here is the fast and correct detection of important patterns of change such as level shifts and trends in the data. We present approaches for automated pattern detection in online-monitoring data. Sever作者: canvass 時間: 2025-3-22 22:53
Generalizations and Extensions,abilitation circumstances evinced by traumatic injury. The potential effectiveness of such systems is addressed from several points of view. First, the ability of the underlying connectionist models to identify complex, highly nonlinear, and sometimes even counterintuitive patterns in trauma data is作者: occurrence 時間: 2025-3-23 01:58 作者: disrupt 時間: 2025-3-23 08:00
Limit Theorems for Stopped Random Walks,ers in medicine. Over the past 4 decades, since its inception, research techniques in the given field have proliferated. Approaches adopted have included the use of rule based approaches such as Decision Trees, Fuzzy Logic and Expert Systems, to the use of Multivariate Statistical Analysis. The past作者: insular 時間: 2025-3-23 09:54
Generalizations and Extensions,osis greater than 50% formed the dichotomous supervisory variable for the neural network. The network contained 19 and 30 elements in the input and middle layers respectively. A single output element corresponded to the supervisory variable. Patient records were ordered according to the date of the 作者: 外來 時間: 2025-3-23 13:57
Limit Theorems for Stopped Random Walks,ethodology. This chapter describes a modular neural network system which is being used for the detection and classification of breast cancer nuclei named Biopsy Analysis Support System (BASS). The system is based on a modular architecture where the detection and classification stages are independent作者: 氣候 時間: 2025-3-23 18:08 作者: Left-Atrium 時間: 2025-3-24 00:24 作者: Insul島 時間: 2025-3-24 03:43
Generalizations and Extensions, CAD can improve the accuracy of breast cancer detection and characterization by radiologists on mammograms. In this chapter, we discuss an important step — feature selection — in classifier design for CAD algorithms. Feature selection reduces the dimensionality of an available feature space and is 作者: 流眼淚 時間: 2025-3-24 09:55
https://doi.org/10.1007/978-0-387-87835-5In this chapter, we advocate the use of Computational Intelligence (CI) in diagnosis, in the context of using artificial intelligence in medicine and in health management. The methodological advantages, economic benefits, main trends and perspectives of using CI in health care and management are discussed.作者: 開花期女 時間: 2025-3-24 11:06
Renewal Processes and Random Walks,In intensive care units physicians are aware of a high lethality rate of septic shock patients. In this contribution we present typical problems and results of a retrospective, data driven analysis based on two neural network methods applied on the data of two clinical studies.作者: anatomical 時間: 2025-3-24 16:58 作者: endure 時間: 2025-3-24 19:24
Septic Shock Diagnosis by Neural Networks and Rule Based Systems,In intensive care units physicians are aware of a high lethality rate of septic shock patients. In this contribution we present typical problems and results of a retrospective, data driven analysis based on two neural network methods applied on the data of two clinical studies.作者: 變形詞 時間: 2025-3-25 01:19 作者: 帶來墨水 時間: 2025-3-25 07:22
978-3-7908-2509-1Springer-Verlag Berlin Heidelberg 2002作者: 焦慮 時間: 2025-3-25 10:56 作者: GROWL 時間: 2025-3-25 15:41 作者: corn732 時間: 2025-3-25 15:54 作者: preeclampsia 時間: 2025-3-25 23:35 作者: 頑固 時間: 2025-3-26 03:32 作者: Acquired 時間: 2025-3-26 04:43 作者: 表示向前 時間: 2025-3-26 09:20
Artificial Neural Network Models for Timely Assessment of Trauma Complication Risk,abilitation circumstances evinced by traumatic injury. The potential effectiveness of such systems is addressed from several points of view. First, the ability of the underlying connectionist models to identify complex, highly nonlinear, and sometimes even counterintuitive patterns in trauma data is作者: Certainty 時間: 2025-3-26 15:58 作者: harbinger 時間: 2025-3-26 20:52 作者: 減震 時間: 2025-3-26 23:21 作者: 象形文字 時間: 2025-3-27 02:30 作者: 冷漠 時間: 2025-3-27 06:42 作者: 夸張 時間: 2025-3-27 12:04 作者: Radiation 時間: 2025-3-27 16:10
Genetic Algorithms for Feature Selection in Computer-Aided Diagnosis, CAD can improve the accuracy of breast cancer detection and characterization by radiologists on mammograms. In this chapter, we discuss an important step — feature selection — in classifier design for CAD algorithms. Feature selection reduces the dimensionality of an available feature space and is 作者: constitutional 時間: 2025-3-27 19:54
Generalizations and Extensions,cutoff was applied to the 100 records of the test file. ROC analysis revealed that a cutoff of 0.30 maximized specificity while maintaining perfect sensitivity in the cutoff determination file. The cutoff of 0.30 also maintained perfect sensitivity in the test file, while the trained network made ou作者: 玷污 時間: 2025-3-27 22:58 作者: synovium 時間: 2025-3-28 05:11
Computational Intelligence Processing in Medical Diagnosis作者: enormous 時間: 2025-3-28 07:15
Neural Network Predictions of Significant Coronary Artery Stenosis in Women,cutoff was applied to the 100 records of the test file. ROC analysis revealed that a cutoff of 0.30 maximized specificity while maintaining perfect sensitivity in the cutoff determination file. The cutoff of 0.30 also maintained perfect sensitivity in the test file, while the trained network made ou作者: Nonporous 時間: 2025-3-28 13:45
Genetic Algorithms for Feature Selection in Computer-Aided Diagnosis,xamples illustrate the design of a fitness function for optimizing classification accuracy in terms of the receiver operating characteristics of the classifier, the dependence of GA performance on its evolution parameters, and the design of a fitness function tailored to a specific classification ta作者: 赦免 時間: 2025-3-28 15:46
1434-9922 n view of explaining to the practitioner the fundamental issues related to computational intelligence paradigms and to offer a fast and friendly-managed introduction to the most recent methods based on computer intelligence in medicine.978-3-7908-2509-1978-3-7908-1788-1Series ISSN 1434-9922 Series E-ISSN 1860-0808 作者: BUCK 時間: 2025-3-28 21:32
Generalizations and Extensions,s and other machine learning approaches. Several examples of practical medical applications are presented. Finally, we discuss several limitations that must be overcome to effectively apply data mining methods and results to patient care.作者: PACT 時間: 2025-3-29 00:35
Generalizations and Extensions,r ability to use standardized, widely available data and their capacity for reflecting local differences and changing conditions is exposed. Finally, the potential enhancements for such models are explored in the contexts of clinical decision support systems.作者: 紅腫 時間: 2025-3-29 03:12 作者: 高腳酒杯 時間: 2025-3-29 09:37 作者: OGLE 時間: 2025-3-29 12:35
Integrating Kernel Methods into a Knowledge-Based Approach to Evidence-Based Medicine,s for the protocol through empirical validation. We demonstrate our approach of integrating expert knowledge with data driven techniques based on our effort to develop an operational protocol for the hemodynamic system.作者: peptic-ulcer 時間: 2025-3-29 18:22 作者: 詞匯 時間: 2025-3-29 21:13
A Modular Neural Network System for the Analysis of Nuclei in Histopathological Sections,. Two different methods for the detection of nuclei are being used: the one approach is based on a feed forward neural network (FNN) which uses a block-based singular value decomposition (SVD) of the image, to signal the likelihood of occurrence of nuclei.作者: 反抗者 時間: 2025-3-29 23:55 作者: ELATE 時間: 2025-3-30 07:00
Generalizations and Extensions,s for the protocol through empirical validation. We demonstrate our approach of integrating expert knowledge with data driven techniques based on our effort to develop an operational protocol for the hemodynamic system.作者: TRAWL 時間: 2025-3-30 10:28 作者: 軍火 時間: 2025-3-30 15:07 作者: PHAG 時間: 2025-3-30 20:03 作者: Original 時間: 2025-3-30 22:14 作者: 反復無常 時間: 2025-3-31 04:25 作者: 變形詞 時間: 2025-3-31 08:07
