標(biāo)題: Titlebook: Artificial Intelligence in Medicine; 15th Conference on A John H. Holmes,Riccardo Bellazzi,Niels Peek Conference proceedings 2015 Springer [打印本頁] 作者: 瘦削 時(shí)間: 2025-3-21 17:25
書目名稱Artificial Intelligence in Medicine影響因子(影響力)
書目名稱Artificial Intelligence in Medicine影響因子(影響力)學(xué)科排名
書目名稱Artificial Intelligence in Medicine網(wǎng)絡(luò)公開度
書目名稱Artificial Intelligence in Medicine網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Artificial Intelligence in Medicine被引頻次
書目名稱Artificial Intelligence in Medicine被引頻次學(xué)科排名
書目名稱Artificial Intelligence in Medicine年度引用
書目名稱Artificial Intelligence in Medicine年度引用學(xué)科排名
書目名稱Artificial Intelligence in Medicine讀者反饋
書目名稱Artificial Intelligence in Medicine讀者反饋學(xué)科排名
作者: grenade 時(shí)間: 2025-3-21 23:48
Miguel Alonso,Alan Kramer,Javier Rodrigonce of the three main “stakeholder” communities: researchers, clinicians and patients/carers. The ability to harness such data is essential for the integration of medical information to support clinical decision making and medical research.作者: magenta 時(shí)間: 2025-3-22 00:44
https://doi.org/10.1007/978-3-658-07764-8od is evaluated on predicting 30-day hospital readmission for pediatric patients from California and provides evidence that a knowledge-based approach outperforms traditional methods and that the newly proposed method is competitive with state-of-the-art methods.作者: 啜泣 時(shí)間: 2025-3-22 04:52 作者: disciplined 時(shí)間: 2025-3-22 11:46
Kurt Moser,Alfred Schmid,Hermann Leharon local anomalies using a Latent Dirichlet Allocation (LDA)-based probabilistic model. The proposal was evaluated in the study of unstable angina CTP, testing 12,152 patient traces from the Chinese PLA General Hospital.作者: 吵鬧 時(shí)間: 2025-3-22 16:03
https://doi.org/10.1007/978-3-658-30875-9ime intervals where specific order sets are recommended in the CPOE. We evaluate our algorithm using real patient data from a pediatric hospital, and demonstrate that data-driven order sets have the potential to dominate existing, consensus order sets in terms of usability and cognitive workload.作者: Meditative 時(shí)間: 2025-3-22 18:49 作者: THE 時(shí)間: 2025-3-22 23:46
https://doi.org/10.1007/978-3-658-44750-2s; hence preserves the privacy of the dwellers, reduces costs and eliminates the need to remember to wear a device. Our results indicate a good performance for fall detection with an overall F-score of 94%.作者: dearth 時(shí)間: 2025-3-23 02:58 作者: scotoma 時(shí)間: 2025-3-23 07:03 作者: arabesque 時(shí)間: 2025-3-23 12:09 作者: Minikin 時(shí)間: 2025-3-23 14:56
Data Driven Order Set Development Using Metaheuristic Optimizationime intervals where specific order sets are recommended in the CPOE. We evaluate our algorithm using real patient data from a pediatric hospital, and demonstrate that data-driven order sets have the potential to dominate existing, consensus order sets in terms of usability and cognitive workload.作者: Tailor 時(shí)間: 2025-3-23 21:55
Distributed Learning to Protect Privacy in?Multi-centric Clinical Studiesg tools. We tested this approach on a large dataset and we described results, in terms of convergence and performance; we also provide considerations about the features of an IT architecture designed to support distributed learning computations.作者: 無能的人 時(shí)間: 2025-3-23 22:28 作者: 連鎖 時(shí)間: 2025-3-24 05:13 作者: 厭倦嗎你 時(shí)間: 2025-3-24 09:03 作者: 神圣不可 時(shí)間: 2025-3-24 13:00 作者: 字謎游戲 時(shí)間: 2025-3-24 17:43 作者: 主動(dòng) 時(shí)間: 2025-3-24 19:12
A Genomic Data Fusion Framework to Exploit Rare and Common Variants for Association Discoverygnificant association with the disease. Collapsed data have been also used as features for prediction models. We found that the use of protein-protein interactions as model features increases the area under ROC curve (+1.5%) if compared to the solely gene-based approach.作者: 縮減了 時(shí)間: 2025-3-25 03:08
0302-9743 ning; uncertainty and Bayesian networks; text mining; prediction in clinical practice; and knowledge representation and guidelines.978-3-319-19550-6978-3-319-19551-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 誘導(dǎo) 時(shí)間: 2025-3-25 05:08 作者: indenture 時(shí)間: 2025-3-25 10:49
https://doi.org/10.1007/978-3-658-44750-2 discuss the challenges posed by analyzing these data and discuss how we address them. As a case study, we apply our methodology to Dutch pathology data for discovering possible causes of two rare diseases: cholangitis and breast angiosarcomas.作者: 承認(rèn) 時(shí)間: 2025-3-25 15:22 作者: 負(fù)擔(dān) 時(shí)間: 2025-3-25 19:39
Mining Hierarchical Pathology Data Using Inductive Logic Programming discuss the challenges posed by analyzing these data and discuss how we address them. As a case study, we apply our methodology to Dutch pathology data for discovering possible causes of two rare diseases: cholangitis and breast angiosarcomas.作者: Missile 時(shí)間: 2025-3-25 22:07
Conference proceedings 2015 2015. The 19 revised full and 24 short papers presented were carefully reviewed and selected from 99 submissions. The papers are organized in the following topical sections: process mining and phenotyping; data mining and machine learning; temporal data mining; uncertainty and Bayesian networks; te作者: BOLUS 時(shí)間: 2025-3-26 03:34
0302-9743 e, AIME 2015, held in Pavia, Italy, in June 2015. The 19 revised full and 24 short papers presented were carefully reviewed and selected from 99 submissions. The papers are organized in the following topical sections: process mining and phenotyping; data mining and machine learning; temporal data mi作者: 因無茶而冷淡 時(shí)間: 2025-3-26 04:39
From Great War to Fascist Warfare,s counted 682 million patient records that have been converted to a common format known at the OMOP Common Data Model [1]. While this number includes duplicates and records that have not been made broadly available to researchers, its scale demonstrates that converting the world population to a common format is feasible.作者: 我不怕犧牲 時(shí)間: 2025-3-26 11:12 作者: 填滿 時(shí)間: 2025-3-26 13:25 作者: aplomb 時(shí)間: 2025-3-26 16:57
Contextualisation of Biomedical Knowledge Through Large-Scale Processing of Literature, Clinical Narn to structured databases that store expert-curated information, unstructured and semi-structured data is a huge and often most up-to-date resource of medical knowledge. These include scientific literature, clinical narratives and social media, which typically capture findings, knowledge and experie作者: 老巫婆 時(shí)間: 2025-3-26 23:21 作者: 不妥協(xié) 時(shí)間: 2025-3-27 05:11
Predictive Monitoring of Local Anomalies in?Clinical Treatment Processesstaff and hospital managers for determining the efficient medical service delivered to individual patients, and for promptly handling unusual treatment behaviors in CTPs. Existing studies mainly focused on the detection of large deviations of CTPs, called of global anomalous inpatient traces. Howeve作者: Nomogram 時(shí)間: 2025-3-27 07:34 作者: NEEDY 時(shí)間: 2025-3-27 12:55 作者: 鋼筆記下懲罰 時(shí)間: 2025-3-27 15:58 作者: 偏見 時(shí)間: 2025-3-27 19:52 作者: 人類 時(shí)間: 2025-3-27 23:28
What if Your Floor Could Tell Someone You Fell? A Device Free Fall Detection Methodts. In this study we investigate a device free method to detect falls by using simple batteryless radio frequency identification (RFID) tags in a smart RFID enabled carpet. Our method extracts information from the tags and the environment of the carpeted floor and applies machine learning techniques作者: Neuralgia 時(shí)間: 2025-3-28 04:13 作者: AMOR 時(shí)間: 2025-3-28 08:37
A Genomic Data Fusion Framework to Exploit Rare and Common Variants for Association Discoverypsing approach by including genes, protein domains, pathways and protein-protein interactions data. We applied the collapsing technique to a data set of epileptic (85 cases) and healthy (61 controls) subjects. The method retrieved 4 genes, 5 domains, 33 gene interactions and 14 pathways showing a si作者: 慢跑 時(shí)間: 2025-3-28 10:59 作者: Medicaid 時(shí)間: 2025-3-28 15:26
Updating Stochastic Networks to Integrate Cross-Sectional and Longitudinal Studiese or disease process. These cross-sectional studies provide a snapshot of these disease processes over a large number of people but do not allow us to model the temporal nature of disease, which is essential for modelling detailed prognostic predictions. Longitudinal studies on the other hand, are u作者: Eulogy 時(shí)間: 2025-3-28 20:49 作者: 拉開這車床 時(shí)間: 2025-3-28 23:03 作者: 疾馳 時(shí)間: 2025-3-29 04:51 作者: 縮減了 時(shí)間: 2025-3-29 09:19
Conceptual Modeling of Clinical Pathways: Making Data and Processes ConnectedIn this paper, we propose a framework for seamless conceptual modeling of both data and processes, and the seamless integration of temporalities for both clinical data and clinical tasks. Moreover, we apply our approach to model the clinical pathway for managing patients with ROSC (Return Of Spontaneous Circulation) in a real ICU clinical setting.作者: glans-penis 時(shí)間: 2025-3-29 11:52 作者: motivate 時(shí)間: 2025-3-29 19:16
Miguel Alonso,Alan Kramer,Javier Rodrigon to structured databases that store expert-curated information, unstructured and semi-structured data is a huge and often most up-to-date resource of medical knowledge. These include scientific literature, clinical narratives and social media, which typically capture findings, knowledge and experie作者: 假設(shè) 時(shí)間: 2025-3-29 20:03
Contingency, Choice and the Historian,physicians to annotate condition severity are time-consuming and costly. Previously, a passive learning algorithm called CAESAR was developed to capture severity in EHRs. This approach required physicians to label conditions manually, an exhaustive process. We developed a framework that uses two Act作者: 注入 時(shí)間: 2025-3-30 01:59 作者: 蒼白 時(shí)間: 2025-3-30 07:55 作者: SKIFF 時(shí)間: 2025-3-30 08:27 作者: AUGER 時(shí)間: 2025-3-30 16:02
https://doi.org/10.1007/978-3-658-19079-8be used to support statistical studies, and for identifying causal relations. To use these data, which are spread across hospitals, efficient merging techniques as well as policies to deal with this sensitive information are strongly needed. In this paper we introduce and empirically test a distribu作者: 使人煩燥 時(shí)間: 2025-3-30 16:41
https://doi.org/10.1007/978-3-658-44750-2rk exploring how to apply machine learning and data mining techniques to these data in order to extract novel clinical relationships. From a learning perspective, these pathology data possess a number of challenging properties, in particular, the temporal and hierarchical structure that is present w作者: 不再流行 時(shí)間: 2025-3-31 00:44
https://doi.org/10.1007/978-3-658-44750-2ts. In this study we investigate a device free method to detect falls by using simple batteryless radio frequency identification (RFID) tags in a smart RFID enabled carpet. Our method extracts information from the tags and the environment of the carpeted floor and applies machine learning techniques作者: 異端 時(shí)間: 2025-3-31 01:08
