標(biāo)題: Titlebook: Data Science for Healthcare; Methodologies and Ap Sergio Consoli,Diego Reforgiato Recupero,Milan Pet Book 2019 Springer Nature Switzerland [打印本頁] 作者: Neogamist 時(shí)間: 2025-3-21 18:10
書目名稱Data Science for Healthcare影響因子(影響力)
書目名稱Data Science for Healthcare影響因子(影響力)學(xué)科排名
書目名稱Data Science for Healthcare網(wǎng)絡(luò)公開度
書目名稱Data Science for Healthcare網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Science for Healthcare被引頻次
書目名稱Data Science for Healthcare被引頻次學(xué)科排名
書目名稱Data Science for Healthcare年度引用
書目名稱Data Science for Healthcare年度引用學(xué)科排名
書目名稱Data Science for Healthcare讀者反饋
書目名稱Data Science for Healthcare讀者反饋學(xué)科排名
作者: 約會(huì) 時(shí)間: 2025-3-21 23:58 作者: Bernstein-test 時(shí)間: 2025-3-22 03:31 作者: Outwit 時(shí)間: 2025-3-22 04:45
Making Effective Use of Healthcare Data Using Data-to-Text Technologyl to measure and help achieving these improvements in healthcare delivery. Consequently, a data influx from various clinical, financial, and operational sources is now overtaking healthcare organizations and their patients. The effective use of this data, however, is a major challenge. Clearly, text作者: abnegate 時(shí)間: 2025-3-22 10:18
Clinical Natural Language Processing with Deep Learningavailable across healthcare networks. The huge amount of data inspires research and development focused on novel clinical natural language processing (NLP) solutions to optimize clinical care and improve patient outcomes. In recent years, deep learning techniques have demonstrated superior performan作者: 腐敗 時(shí)間: 2025-3-22 15:32
Ontology-Based Knowledge Management for Comprehensive Geriatric Assessment and Reminiscence Therapy dementia and supporting caregivers in their activity to assess patients’ cognitive status. Examples of knowledge-intensive tasks are the comprehensive geriatric assessment (CGA) and the delivery of reminiscence therapy. In order to enable these tasks, MARIO features a set of abilities implemented b作者: 腐敗 時(shí)間: 2025-3-22 21:03
Assistive Robots for the Elderly: Innovative Tools to Gather Health Relevant Datae way healthcare is delivered. In the research and commercial field, robotic technologies have been used for physical and cognitive rehabilitation, surgery, telemedicine, drug delivery, and patient management. Robots are currently used across a range of environments, including hospitals, homes, scho作者: Regurgitation 時(shí)間: 2025-3-22 23:23 作者: probate 時(shí)間: 2025-3-23 02:12
A Flexible Knowledge-Based Architecture for Supporting the Adoption of Healthy Lifestyles with Persu it can significantly contribute to the prevention of chronic diseases deriving from incorrect diet and lack of physical activity. In this chapter, we present the use of Semantic Web technologies to build an architecture for supporting the monitoring of people and for persuading them to follow healt作者: 逗它小傻瓜 時(shí)間: 2025-3-23 07:09 作者: 尊嚴(yán) 時(shí)間: 2025-3-23 09:52 作者: Panther 時(shí)間: 2025-3-23 17:09
Using Process Analytics to Improve Healthcare Processesllected by modern process-aware (healthcare) information systems provide a wealth of data and can be used to analyze the adherence to these protocols. Process mining is a young research area combining data science (machine learning, data mining, etc.) and business process management. Its main contri作者: antedate 時(shí)間: 2025-3-23 21:15 作者: ear-canal 時(shí)間: 2025-3-24 01:55 作者: mucous-membrane 時(shí)間: 2025-3-24 03:17 作者: BRACE 時(shí)間: 2025-3-24 09:04
Candela González-Arias,Gertrudis Peread comparing in detail the performance of different classification techniques. We demonstrate the value of our approach on the concrete problem of building a classifier for predicting biochemical recurrence, indicating potential cancer relapse after prostate cancer treatment, from clinical patient data.作者: parsimony 時(shí)間: 2025-3-24 13:48
Contact Force Models for Granular Materialsdenosine (MTA) accumulation as a result of the loss of activity of the enzyme S-methyl-5.-thioadenosine phosphorylase (MTAP) is correctly predicted by the Nash equilibrium approach under tight regulation of adenine. Several examples are presented to elucidate the key ideas in modeling cancer metabolism using the Nash equilibrium approach.作者: 膠狀 時(shí)間: 2025-3-24 18:04
Assistive Robots for the Elderly: Innovative Tools to Gather Health Relevant Datative of this chapter is to investigate how this can happen given the current state of the art in the field. We will focus our argument on how they can be used as valuable agents for the acquisition of novel data, relevant to the healthcare and well-being domain.作者: 遭遇 時(shí)間: 2025-3-24 20:39
Visual Analytics for Classifier Construction and Evaluation for Medical Datad comparing in detail the performance of different classification techniques. We demonstrate the value of our approach on the concrete problem of building a classifier for predicting biochemical recurrence, indicating potential cancer relapse after prostate cancer treatment, from clinical patient data.作者: 證實(shí) 時(shí)間: 2025-3-25 01:22 作者: 知識(shí) 時(shí)間: 2025-3-25 04:08 作者: MORPH 時(shí)間: 2025-3-25 10:59 作者: travail 時(shí)間: 2025-3-25 14:11 作者: PACK 時(shí)間: 2025-3-25 16:19 作者: 痛苦一生 時(shí)間: 2025-3-25 21:57 作者: gusher 時(shí)間: 2025-3-26 03:52 作者: 鄙視 時(shí)間: 2025-3-26 04:24
The Role of Deep Learning in Improving HealthcareChallenges, in broad adoption of DL, are commonly related to some of its main drawbacks, particularly lack of interpretability and transparency. We discuss the drawbacks and limitations of DL technology that specifically come to light in the domain of healthcare. We also address the need for a consi作者: allude 時(shí)間: 2025-3-26 10:16 作者: scotoma 時(shí)間: 2025-3-26 15:50
Clinical Natural Language Processing with Deep Learningequirement for rigorous de-identification and anonymization to ensure patient data privacy. This tutorial chapter will present an overview of how deep learning techniques can be applied to solve NLP tasks in general, followed by a literature survey of existing deep learning algorithms applied to cli作者: 2否定 時(shí)間: 2025-3-26 19:36 作者: collagenase 時(shí)間: 2025-3-26 23:19
Overview of Data Linkage Methods for Integrating Separate Health Data SourcesIn many practices, such identifiers are simply lacking meaning that one has to resort to variables that are not necessarily unique to a person which makes the task of linking data far more challenging. To make things worse, these linking variables come with errors due to misspellings, coding differe作者: 誰在削木頭 時(shí)間: 2025-3-27 01:27
Data Visualization in Clinical Practicet undergone thorough external validation or because circumstances have changed since the model was developed..We can allow for the doctor to stay in charge of any inferences made from data through visualization instead of mere presentation of, e.g., risk scores or survival probabilities from a train作者: 水土 時(shí)間: 2025-3-27 06:58 作者: tendinitis 時(shí)間: 2025-3-27 11:05 作者: 果仁 時(shí)間: 2025-3-27 15:10 作者: NEEDY 時(shí)間: 2025-3-27 19:18
Book 2019y intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book..??.作者: 沒花的是打擾 時(shí)間: 2025-3-27 22:52
Application Programming Interfacesce technologies in the healthcare sector. This contribution is based on a recent whitepaper (.) provided by the Big Data Value Association (BDVA) (.), the private counterpart to the EC to implement the BDV PPP (Big Data Value PPP) programme, which focuses on the challenges and impact that (Big) Data作者: painkillers 時(shí)間: 2025-3-28 05:52 作者: Deduct 時(shí)間: 2025-3-28 09:19
Case Study: Natural Language ProcessingChallenges, in broad adoption of DL, are commonly related to some of its main drawbacks, particularly lack of interpretability and transparency. We discuss the drawbacks and limitations of DL technology that specifically come to light in the domain of healthcare. We also address the need for a consi作者: 骨 時(shí)間: 2025-3-28 14:16 作者: amplitude 時(shí)間: 2025-3-28 17:19
HLA Polymorphism and Disease Susceptibilityequirement for rigorous de-identification and anonymization to ensure patient data privacy. This tutorial chapter will present an overview of how deep learning techniques can be applied to solve NLP tasks in general, followed by a literature survey of existing deep learning algorithms applied to cli作者: PHAG 時(shí)間: 2025-3-28 20:56
Genetic Variation in Populations,Web technologies. It consists of (1) a set of interconnected and modularized ontologies, meant to model all knowledge areas that are relevant for MARIO abilities, and (2) a set of software interfaces that provide high-level access to the ontology network and its associated knowledge base. Finally, w作者: insipid 時(shí)間: 2025-3-29 01:32
https://doi.org/10.1007/978-3-030-00817-8In many practices, such identifiers are simply lacking meaning that one has to resort to variables that are not necessarily unique to a person which makes the task of linking data far more challenging. To make things worse, these linking variables come with errors due to misspellings, coding differe作者: gospel 時(shí)間: 2025-3-29 04:42 作者: 巡回 時(shí)間: 2025-3-29 11:00 作者: ETHER 時(shí)間: 2025-3-29 13:55 作者: 他很靈活 時(shí)間: 2025-3-29 18:35
https://doi.org/10.1007/978-3-030-05249-2Data Science; Health Informatics; Machine Learning; Knowledge Management; Data Visualization; Process Ana作者: 震驚 時(shí)間: 2025-3-29 22:16 作者: BLANK 時(shí)間: 2025-3-30 01:48
Sergio Consoli,Diego Reforgiato Recupero,Milan PetConnects machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies to healthcare applications..Highlights the successful application of thes作者: 透明 時(shí)間: 2025-3-30 04:30 作者: 彩色 時(shí)間: 2025-3-30 11:37
Application Programming Interfacesion methods to emerge. Tapping into this data brings clinical research and clinical practice closer together, as data generated in ordinary clinical practice can be used towards rapid-learning healthcare systems, continuously improving and personalizing healthcare. In this context, the recent use of作者: 不能強(qiáng)迫我 時(shí)間: 2025-3-30 15:11 作者: 營養(yǎng) 時(shí)間: 2025-3-30 17:10 作者: Hypopnea 時(shí)間: 2025-3-31 00:24
HLA Polymorphism and Disease Susceptibilityl to measure and help achieving these improvements in healthcare delivery. Consequently, a data influx from various clinical, financial, and operational sources is now overtaking healthcare organizations and their patients. The effective use of this data, however, is a major challenge. Clearly, text
