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Effective Application of Patient web Portal Tool for Storage and Return of Medical Records Results

Effective Application of Patient Web Portal Tool for Storage...

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international conference on Green technology and Sustainable Development (GTSD)

作者： Ngoc Nguyen-Chi Tuan Nguyen-thanh Ho Chi Minh City University of Technology (HCMUT) Vietnam National University Ho Chi Minh City (VNU-HCM) Ho Chi Minh City Vietnam

ISBN: (数字)9798350386073

ISBN: (纸本)9798350386080

the Picture Archiving and Communication System (PACS) is an indispensable part of a medical imaging diagnostic information system as well as the process of implementing electronic medical records (EMR). However, PACS currently only operates within hospitals or medical facilities. On the other hand, medical record data when digitized into digital images or related files is still fragmentary, and the function of returning results and sharing patient medical records is still difficult due to the lack of a common standard in data entry and storage. Taking advantage of the infrastructure of the PACS with virtualization and cloud computing technology, our novel solution for storing and returning medical records is proposed by digitizing medical record data according to the DICOM (Digital Image and Communication in Medicine) standard format. Accordingly, a Patient web Portal tool is integrated into medical information systems (HIS—Hospital information System, EMR) of hospitals, clinics, or healthcare organizations for patients to access and manage information related to their health. through the patient portal, they can perform activities such as viewing diagnostic imaging and laboratory reports, viewing personal medical records, viewing information about medications, instructions for use, and other types of material. Additionally, the patient portal facilitates secure messaging interactions with doctors or medical staff, integrates a clinical NLP (Natural language processing) model based on the comprehensive SNOMED CT (Systematized Nomenclature of Medicine-Clinical Terms) into the treatment process, and arranges patient treatment plans based on existing records. through the process of research, development, and implementation at the Victoria Healthcare Clinic system, practical results have shown the effectiveness of the Patient web Portal tool for storing and returning medical record results. In addition to exploiting encryption techniques, DICOM digital signatures are al

关键词： Computers Hospitals Digital images information security Picture archiving and communication systems Natural language processing DICOM

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Predicting the Stock Market Prices Using Ensemble and Fbprophet Model 7th

Predicting the Stock Market Prices Using Ensemble and Fbprop...

引用

7th international conference on information and Communication technology for Competitive Strategies, ICTCS 2022

作者： Shareef, Shaik Ahmad Kumar, Chinchili tharun Harika, Kotha Yellisetti, Sandeep Department of Information Technology Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada Kanuru India

ISBN: (纸本)9789811993039

Stock price prediction through machine learning is an emerging area of research. In the emerging economy, stock investment is useful for individuals and institutions for stabilising their income on investments. Many fund houses hire professionals to analyse the stocks. the machine learning models are more useful and effective than any other traditional techniques. However, many researchers have done price prediction based on various ML algorithms and techniques such as classification and regression. In this proposed work, we were comparing two main types of stock market analysis methods, technical analysis and fundamental analysis. For technical analysis, ensemble classification was used. More care has been taken on choosing the classifier to get more accuracy of prediction. ML algorithm decision tree, KNN and random forest have been used for creating ensemble models. three ensemble classifiers are chosen such as AdaBoost, bagging and voting classifiers. For the fundamental analysis, we have chosen the Fbprophet price forecast with sentiment on stock from New York Times news for stock ‘Apple’. the proposed ensemble models and Fbprophet model are compared to find the best on accurate predictions. Natural language processing (NLP), sentiment analysis technique is used for finding the stock sentiment as positive, negative or neutral. this sentiment value is compounded for each date and added as the additional feature for stock historical prices downloaded from Yahoo. From the experimental results, it is observed that voting-based ensemble classifiers are more efficient and have achieved the highest accuracy of 79.98%. this tells us for short-term market prediction technical analysis gives us better results than fundamental analysis. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Decision trees

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A Container-Based Edge Computing System for Smart Healthcare Applications 7th

A Container-Based Edge Computing System for Smart Healthcare...

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7th EAI international conference on Industrial Networks and Intelligent Systems, INISCOM 2021

作者： Le-Anh, Tuan Ngo-Van, Quan Vo-Huy, Phuong Huynh-Van, Dang Le-Trung, Quan UiTiOt Research Group Department of Computer Networks University of Information Technology Vietnam National University – Ho Chi Minh City Ho Chi Minh City Viet Nam

ISBN: (纸本)9783030774233

Edge computing is evolving how data are processed and analyzed from a large figure of various Internet of things (IoT) devices globally. the rapid development of IoT, 5G, artificial intelligence (AI), and applications that require real-time computing capability steadily propel edge computing systems. In this paper, we propose a container-based edge computing system for smart healthcare applications. the smart care mobile and web-based applications aim to assist doctors or nurses with intelligent monitoring and caring for patients in the recovery phase in real-time. the proposed system’s design takes advantage of edge computing’s capabilities to timely deal with the patient’s facial emotion detection and heart disease diagnosis AI applications and a robust cloud computing infrastructure to centralize the patient’s data in the secure, scalable, and fault-tolerance database. Moving these AI applications to the edge outperforms cloud computing in processing time, energy efficiency, and bandwidth saving. Finally, implementing the AI applications on a lightweight container orchestration platform for management efficiency with high availability, scalability, and deployment automation. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Containers

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Use of Video-enabled web based CMC to Facilitate Oral Conversation Drill

Use of Video-enabled Web based CMC to Facilitate Oral Conver...

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international conference on information technology Based Higher Education and Training, IthET

作者： Chiung-Fang Chiu Greg C. Lee Ju-Hsush Yang Department of Information and Computer Education National Taiwan Normal University Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan Normal University Taipei Taiwan Department Of Chinese Language And Literature National Taiwan Normal University Taipei Taiwan

this study investigates how video-enabled web-based Computer Mediated Communication (CMC) system can be effectively used in a local dialect learning course to enhance students' learning. Eighteen students enrolled in the course used the system to complete course related activities. Students' in class oral conversation drills were videotaped and made available for viewing on a CMC system. After each class, students and course instructor can give both textual and audio feedback to each student's in class oral conversation drill on the CMC system to foster interactions, which were fewer in the classroom due to limited class time. Furthermore, students can access the video to self-evaluate their oral conversations as often as necessary and monitor their personal growth. It was found that this video-enabled CMC system is valuable in improving quality of feedback and in increasing students' reflection. the audio feedback given by instructor was especially useful for correcting their pronunciation and utterance. It also gave students more opportunities to interact with instructor and peers after class.

关键词： Negative feedback Delay Computer mediated communication Natural languages Monitoring Speech Error correction Computer science education Systems engineering education Computer science

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Natural language processing: Concepts and Applications using Chatbot

Natural Language Processing: Concepts and Applications using...

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international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： R. Srinivasan M. Kavitha Uma S Department of Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Chennai Department of Computer Science and Engineering Rajalakshmi Institute of Technology Chennai

A chatbot is a paradigm of human-computer interaction (HCI) and artificial intelligence software. A chatbot is described as "computer software designed to simulate human-to-human interaction, particularly over the Internet." Chatbot is a popular computer programme that is used to promote human user interaction and communication, particularly via the internet. As a computer programme application, it is becoming more popular. Previously, a user would ask a query, and a computer programme would respond. By entering in the question, the user can answer it. If a user asks a question that isn't answered in the database, the chat bot conducts a Google search and responds with pertinent information. When a user enters a query, the bot compares and correlates the query terms with words in the database using pattern matching. User's input will be used to analyses the terms in the phrase for similarity. As a result, the highest score is printed. NLP (Natural language processing) is a technique for helping computers understand human language. this document also offers a summary of the metrics used to evaluate bot performance. this contributes in the development of more effective bots.

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Enhancing the Ability to Communicate by Synthesizing American Sign language using Image Recognition in A Chatbot for Differently Abled

Enhancing the Ability to Communicate by Synthesizing America...

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international conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： Arjun Pardasani Ajay Kumar Sharma Sashwata Banerjee Vaibhav Garg Debdutta Singha Roy School of Electronics Engineering (Vellore Institute of Technology) School of Electrical Engineering (Vellore Institute of technology) Vellore India School of Information Technology (Vellore Institute of Technology)

ISBN: (纸本)9781538646939

Sign language is a mode of communication for differently abled persons -Mute (Dumb). Sign language is the hand gestures used by people to communicate. American Sign language is the most widely used Sign language which has its own syntax and rules and by following these rules and syntax, mute people can communicate. We have used image recognition to recognize the hand gestures. Detection of hand motions and processing of finger movement to identify what the mute person is communicating. Computer vision in python recognizes the hand gestures of a mute person and gives its output to a chatbot. Chatbot is a computer program which conducts a conversation via voice recognition. Such programs are often designed to convincingly simulate to help human beings with different tasks. this paper presents image recognition of Sign language through hand gestures and integrate it with chatbot and gives us an audio as well as text output.

关键词： Gesture recognition Assistive technology conferences Image recognition Computer vision Speech recognition Task analysis

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i-AEGIS-128: An Improved Authenticated Encryption Based on AEGIS-128

i-AEGIS-128: An Improved Authenticated Encryption Based on A...

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international conference on Optimization and Applications (ICOA)

作者： Muhammad Ghulam Ghouse Sapiee Jamel Muhammad Aamir Muhammad Zulqarnain Mustafa Mat Deris Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia College of Science and Engineering University of Derby United Kingdom Faculty of Applied Sciences and Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia

ISBN: (纸本)9781665431156

Authenticated Encryption (AE) is the latest cryptographic algorithm standard introduced through CAESAR (Com-petition for Authenticated Encryption: Security, Applicability, and Robustness). AE schemes provide a process for simultaneously achieving the security goals of confidentiality and integrity assurance. the constructions of authentication encryption is secure and efficient to protect the modern electronic information systems. In this research paper, we proposed an Improved AEGIS-128 Algorithm (i-AEGIS-128) for improving the standard AEGIS-128 algorithm to enhance the performance in which quarter round-based AES (advanced Encryption Standard) is used for the encryption and decryption process. the proposed i-AEGIS-128 is based on an AEGIS-128 AES-round permutation modification for hardware implementation. the Results of i-AEGIS-128 on Intel(R)Core(TM) i7-3700 Processor running at 3.40 GHz speed with 16GB of RAM using C/C++ and HDL (Hardware Description language) languages and platforms to determine the encryption and decryption time, throughput processing unit memory during encryption and decryption. Finally we compared the efficiency and power analysis of the hardware. the i-AEGIS-128 algorithm relies on the use of ¼ AES-round in authentication encryption to reduce the area consumed during processing, perform fast encryption and decryption, use less power and provide the best efficiency.

关键词： Performance evaluation Power demand Authentication Random access memory throughput Hardware Robustness

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the Algorithms for Word Segmentation and Named Entity Recognition of Chinese Medical Records 7th

The Algorithms for Word Segmentation and Named Entity Recogn...

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7th international conference on Artificial Intelligence and Security, ICAIS 2021

作者： Ye, Yuan-Nong Zheng, Liu-Feng Huang, Meng-Ya Liu, Tao Zeng, Zhu Bioinformatics and Biomedical Big Data Mining Laboratory Department of Medical Informatics School of Big Health Guizhou Medical University Guiyang550025 China Key Laboratory of Environmental Pollution Monitoring and Disease Control Ministry of Education Guizhou Medical University Guiyang550025 China Cells and Antibody Engineering Research Center of Guizhou Province Key Laboratory of Biology and Medical Engineering School of Biology and Engineering Guizhou Medical University Guiyang550025 China

ISBN: (纸本)9783030786144

A complete inpatient electronic medical record contains a lot of information. In recent years, numerous researchers have carried out research on word segmentation of medical texts. Since the medical record text is written by free text, structuring the medical record text is an important part of the medical record intelligent analysis when these medical named entities are recognized. At present, named entity recognition methods are mainly divided into lexicographical and rule-based methods and machine learning-based methods. the machine learn-based approach takes the named entity recognition task as the annotation problem of sequence data, mainly considering the context information. the features commonly used in feature construction are contextual feature and dictionary features. BERT+LSTM+CRF were used to train the named entity recognition model. Open source CRF++ was adopted as the tool we relied on. We trained the LSTM+F model using the results of the original word segmentation and the information in the context as features. We carried out a 5-fold cross validation. the results showed that the overall F-1 score (MICRO-F) of named entity recognition reached 0.92, which confirmed that the model could accurately complete the task of medical named entity recognition. © 2021, Springer Nature Switzerland AG.

关键词： Natural language processing systems

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Extensions to the Pig data processing platform for scalable RDF data processing using Hadoop

Extensions to the Pig data processing platform for scalable ...

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international conference on Data Engineering Workshops

作者： Yusuke Tanimura Akiyoshi Matono Steven Lynden Isao Kojima Information Technology Research Institute National Institute for Advanced Industrial Science and Technology Tsukuba Ibaraki Japan

In order to effectively handle the growing amount of available RDF data, a scalable and flexible RDF data processing framework is needed. We previously proposed a Hadoop-based framework, which takes advantages of scalable and fault-tolerant distributed processing technologies, originally proposed as Google's distributed file system and MapReduce parallel model. In this paper, we present a method extending the Pig data processing platform on top of the Hadoop infrastructure. Pig compiles programs written in a high level language, called Pig Latin, into MapReduce programs that can be executed by Hadoop. In order to support RDF, Pig was extended with the ability to load and store RDF data efficiently. Furthermore, as reasoning is an important requirement for most systems storing RDF data, support for inferring new triples using entailment rules was also added. In this paper, we describe these extensions and present an evaluation of their performance.

关键词： Data processing Resource description framework Relational databases File systems Scalability Semantic web Open source software OWL information technology Distributed processing

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Applying ontological modeling on quranic "nature" domain

Applying ontological modeling on quranic "nature" domain

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international conference on information and Communication Systems (ICICS)

作者： A. B. M. Shamsuzzaman Sadi Towfique Anam Mohamed Abdirazak Abdillahi Hasan Adnan Sazid Zaman Khan Mohamed Mahmudur Rahman Ghassan Samara Department of Computer Science and Engineering International Islamic University Chittagong Bangladesh Department of Science and Technology Universiti Sains Islam Malaysia Nilai Malaysia Department of Internet Technology Zarqa University Jordan

ISBN: (纸本)9781467386159

the holy Quran is the holy book of the Muslims. It contains information about many domains. Often people search for particular concepts of holy Quran based on the relations among concepts. An ontological modeling of holy Quran can be useful in such a scenario. In this paper, we have modeled nature related concepts of holy Quran using OWL (web Ontology language) / RDF (Resource Description Framework). Our methodology involves identifying nature related concepts mentioned in holy Quran and identifying relations among those concepts. these concepts and relations are represented as classes/instances and properties of an OWL ontology. Later, in the result section it is shown that, using the Ontological model, SPARQL queries can retrieve verses and concepts of interest. thus, this modeling helps semantic search and query on the holy Quran. In this work, we have used English translation of the holy Quran by Sahih international, Protege OWL Editor and for querying we have used SPARQL.

关键词： Ontologies Semantics OWL Search engines Resource description framework Data mining

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