標(biāo)題: Titlebook: Artificial Intelligence and Data Mining in Healthcare; Malek Masmoudi,Bassem Jarboui,Patrick Siarry Book 2021 Springer Nature Switzerland [打印本頁(yè)] 作者: T-Lymphocyte 時(shí)間: 2025-3-21 19:18
書(shū)目名稱Artificial Intelligence and Data Mining in Healthcare影響因子(影響力)
書(shū)目名稱Artificial Intelligence and Data Mining in Healthcare影響因子(影響力)學(xué)科排名
書(shū)目名稱Artificial Intelligence and Data Mining in Healthcare網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱Artificial Intelligence and Data Mining in Healthcare網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱Artificial Intelligence and Data Mining in Healthcare被引頻次
書(shū)目名稱Artificial Intelligence and Data Mining in Healthcare被引頻次學(xué)科排名
書(shū)目名稱Artificial Intelligence and Data Mining in Healthcare年度引用
書(shū)目名稱Artificial Intelligence and Data Mining in Healthcare年度引用學(xué)科排名
書(shū)目名稱Artificial Intelligence and Data Mining in Healthcare讀者反饋
書(shū)目名稱Artificial Intelligence and Data Mining in Healthcare讀者反饋學(xué)科排名
作者: 牢騷 時(shí)間: 2025-3-22 00:02
Lattice Images and Structure Imagesnt of hours awarded to a team of surgeons or a given specialty, the duration of shifts, and the availability of a specific operating room for a specific team. Simulation tests on a typical case using real data are performed by both methods. The results allow us to conclude as to the superiority of t作者: dysphagia 時(shí)間: 2025-3-22 04:07 作者: 痛打 時(shí)間: 2025-3-22 06:12 作者: inscribe 時(shí)間: 2025-3-22 10:10
https://doi.org/10.1007/978-3-031-67260-6aging diseases, providing better care which leads to having better outcomes including elimination of unnecessary costs and increasing patient satisfaction..In this work, we focus on one of the main clustering methods of machine learning approaches, namely mixture models. These capable techniques hav作者: Condense 時(shí)間: 2025-3-22 14:55 作者: 經(jīng)典 時(shí)間: 2025-3-22 18:02 作者: 耕種 時(shí)間: 2025-3-23 01:03
Optimized Medical Image Compression for Telemedicine Applications,and normalized correlation coefficient (NCC) are quantitative measures used to evaluate the performance of the proposed algorithm and well-known existing medical image compression methods. The results showed that the quality of the reconstructed images using the proposed algorithm is much better tha作者: COMMA 時(shí)間: 2025-3-23 04:58
Online Variational Learning Using Finite Generalized Inverted Dirichlet Mixture Model with Feature rning of finite generalized inverted Dirichlet (GID) mixture model for clustering medical images data by simultaneously using feature selection and image segmentation. The model allows one to adjust the mixture model parameters, number of components and features weights to tackle the challenge of ov作者: Alienated 時(shí)間: 2025-3-23 06:32
Entropy-Based Variational Inference for Semi-Bounded Data Clustering in Medical Applications,aging diseases, providing better care which leads to having better outcomes including elimination of unnecessary costs and increasing patient satisfaction..In this work, we focus on one of the main clustering methods of machine learning approaches, namely mixture models. These capable techniques hav作者: conifer 時(shí)間: 2025-3-23 10:24 作者: facetious 時(shí)間: 2025-3-23 15:20 作者: 作嘔 時(shí)間: 2025-3-23 19:08
Artificial Intelligence for Healthcare Logistics: An Overview and Research Agenda,gning, providing and improving healthcare services. As a basis, we provide a framework for the classification of artificial intelligence. For the analysis, we distinguish between the care levels (primary, secondary and tertiary care), the planning levels (strategic, tactical and operational), as wel作者: Pituitary-Gland 時(shí)間: 2025-3-24 00:22
AI/OR Synergies of Process Mining with Optimal Planning of Patient Pathways for Effective Hospital-ining methods, a picture of the current reality is drawn while prescriptive planning methods try to decide what should happen. As the economical pressure of hospitals is rising, they should focus on optimizing their operations by using these approaches. Within a hospital, most of the relevant decisi作者: Chameleon 時(shí)間: 2025-3-24 05:37 作者: Constrain 時(shí)間: 2025-3-24 07:52 作者: 串通 時(shí)間: 2025-3-24 12:18 作者: excursion 時(shí)間: 2025-3-24 16:36
An Immune Memory and Negative Selection to Visualize Clinical Pathways from Electronic Health Recorcal pathways from patient-centric electronic health record (EHR) data. The analysis of patients records can lead to better understanding and condoling pathologies. The proposed algorithmic methodology consists of designing a system of control and analysis of patient records based on an analogy betwe作者: 粗糙 時(shí)間: 2025-3-24 21:21 作者: Interdict 時(shí)間: 2025-3-25 00:51 作者: 領(lǐng)先 時(shí)間: 2025-3-25 03:20
Entropy-Based Variational Inference for Semi-Bounded Data Clustering in Medical Applications,st in applying numerous machine learning approaches to extract the implicit patterns, acquire information and retrieve latent meaningful knowledge. Such powerful statistical tools have been applied in various fields of science..One of the vital domains where these techniques could be potentially dep作者: 松果 時(shí)間: 2025-3-25 10:20 作者: 檔案 時(shí)間: 2025-3-25 12:24 作者: PURG 時(shí)間: 2025-3-25 16:23 作者: 滔滔不絕的人 時(shí)間: 2025-3-25 22:10
https://doi.org/10.1007/978-3-031-56262-4ysis, we distinguish between the care levels (primary, secondary and tertiary care), the planning levels (strategic, tactical and operational), as well as the user types (doctors, nurses, technicians, patients, etc.). Based on the results, we provide a research agenda with open topics and future challenges.作者: ZEST 時(shí)間: 2025-3-26 02:49 作者: Cardioplegia 時(shí)間: 2025-3-26 06:57 作者: FOLD 時(shí)間: 2025-3-26 08:33
Advanced Transmission Electron Microscopyho share the same EHR information. This methodology demonstrates its ability to simultaneously process data and is able to provide information for understanding and identifying the path of patients as well as predicting the path of future patients.作者: Unsaturated-Fat 時(shí)間: 2025-3-26 16:31 作者: implore 時(shí)間: 2025-3-26 18:24
An Immune Memory and Negative Selection to Visualize Clinical Pathways from Electronic Health Recorho share the same EHR information. This methodology demonstrates its ability to simultaneously process data and is able to provide information for understanding and identifying the path of patients as well as predicting the path of future patients.作者: 原始 時(shí)間: 2025-3-27 00:51
Book 2021ered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection..The content will be valuable for researchers and postgraduate students in computer science, information technology,作者: 膠狀 時(shí)間: 2025-3-27 04:57 作者: 賄賂 時(shí)間: 2025-3-27 06:21
Malek Masmoudi,Bassem Jarboui,Patrick SiarryPresents recent work on healthcare management and engineering using AI and data mining techniques.Valuable for researchers and postgraduate students in computer science, information technology, indust作者: Parallel 時(shí)間: 2025-3-27 11:30
http://image.papertrans.cn/b/image/162189.jpg作者: osteocytes 時(shí)間: 2025-3-27 16:30
https://doi.org/10.1007/978-3-030-45240-7Computational Intelligence (CI); Artificial Intelligence (AI); Healthcare; Patient Management; Machine L作者: 神化怪物 時(shí)間: 2025-3-27 18:44
978-3-030-45242-1Springer Nature Switzerland AG 2021作者: Asparagus 時(shí)間: 2025-3-27 23:48
https://doi.org/10.1007/978-3-031-56262-4gning, providing and improving healthcare services. As a basis, we provide a framework for the classification of artificial intelligence. For the analysis, we distinguish between the care levels (primary, secondary and tertiary care), the planning levels (strategic, tactical and operational), as wel作者: 就職 時(shí)間: 2025-3-28 03:24
,Nuclear Excitation by?Electron Capture,ining methods, a picture of the current reality is drawn while prescriptive planning methods try to decide what should happen. As the economical pressure of hospitals is rising, they should focus on optimizing their operations by using these approaches. Within a hospital, most of the relevant decisi作者: Handedness 時(shí)間: 2025-3-28 10:08 作者: 網(wǎng)絡(luò)添麻煩 時(shí)間: 2025-3-28 12:30 作者: 樹(shù)上結(jié)蜜糖 時(shí)間: 2025-3-28 15:35 作者: 管理員 時(shí)間: 2025-3-28 21:50
Advanced Transmission Electron Microscopycal pathways from patient-centric electronic health record (EHR) data. The analysis of patients records can lead to better understanding and condoling pathologies. The proposed algorithmic methodology consists of designing a system of control and analysis of patient records based on an analogy betwe作者: Gastric 時(shí)間: 2025-3-29 02:29
