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Articoli di riviste sul tema "IBM Watson Content Analytics"

Autore: Grafiati

Pubblicato: 25 luglio 2024

Ultima modifica: 31 luglio 2025

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1

Rajeshwari, M., and Prasad K. Krishna. "IBM Watson Industry Cognitive Education Methods." International Journal of Case Studies in Business, IT, and Education (IJCSBE) 4, no. 1 (2020): 38–50. https://doi.org/10.5281/zenodo.3766900.

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Data analytics converts bulk of data into insights for business, healthcare, insurance and education. An upcoming development in IBM’s data analytic approach towards education is cognitive learning systems. Human being and machine can communicate each other by the technologies that use Natural Language processing and Machine Language together in action. Presently, many students struggle for their education without any goals. In this sense, cognitive systems should improve student education and results with a customized perception of their learning. IBM has recently pointed his service on

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Zahraa Raji Mohi Al-zobaidy. "Artificial Intelligence in Natural Language Processing." International Journal of Science and Research Archive 13, no. 1 (2024): 370–77. http://dx.doi.org/10.30574/ijsra.2024.13.1.1638.

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Natural language processing is one of basic topics used by artificial intelligence techniques. realized it is role in content analysis. In this study we introduce artificial intelligence role in content analysis and data revealing process by using natural language processing in libraries specifically that is powerful in content analysis domain. applied to one of natural language processing systems used in content analysis as a resource of information for aim investment depends on analytic description theory. The most important result from this study : the ability of using natural language proc

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Sundas Jabeen Mirza, Etizaz Ali Shah, Farhad Ali Tamour, Hira Hussain, and Muhammad Bilal Khan. "The Role of Social Media Analytic in Crafting International Political Narrative." Critical Review of Social Sciences Studies 3, no. 2 (2025): 2456–68. https://doi.org/10.59075/gft9jn19.

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In the digital era, social media has become a powerful platform for shaping political discourse and influencing international narratives. This study explores the pivotal role of social media analytics in crafting international political narratives by examining how governments, political actors and non-state entities utilize data-driven insights to influence public opinion, engage global audiences, and shape geopolitical messaging. Adopting a qualitative research approach, the study conducts a thematic content analysis of relevant scholarly articles, case studies and policy reports to identify

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Vaccaro-Witt, G. F., Hilaria Bernal, Sergio Guerra Heredia, F. E. Cabrera, and J. I. Peláez. "Effect of Informational Divergence on the Mental Health of the Population in Crisis Situations: A Study in COVID-19." Societies 15, no. 5 (2025): 118. https://doi.org/10.3390/soc15050118.

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Informational divergence emerged as a significant phenomenon during the COVID-19 health crisis. This period was characterized by information overload and changes in the communication of public health recommendations and policies by authorities and media outlets. This study examines the impact of such divergence on the population’s mental health, focusing on primary emotions expressed in comments across digital ecosystems. A media EMIC approach was used to analyze digital ecosystems during March and April 2020. Data were collected from Twitter, YouTube, Instagram, official press websites, and i

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Taha, Sawsan, and Rania Abdel-Qader Abdallah. "Leveraging Artificial Intelligence in Social Media Analysis: Enhancing Public Communication Through Data Science." Journalism and Media 6, no. 3 (2025): 102. https://doi.org/10.3390/journalmedia6030102.

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This study examines the role of AI tools in improving public communication via social media analysis. It reviews five of the top platforms—Google Cloud Natural Language, IBM Watson NLU, Hootsuite Insights, Talkwalker Analytics, and Sprout Social—to determine their accuracy in detecting sentiment, predicting trends, optimally timing content, and enhancing messaging engagement. Adopting a structured model approach and Partial Least Squares Structural Equation Modeling (PLS-SEM) via SMART PLS, this research uses 500 influencer posts from five Arab countries. The results demonstrate the impactful

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Pyatnychuk, I. D., A. V. Tomashevska, N. I. Horogotska, and Yu V. Paska. "Digital-marketing: current challenges and development prospects." Marketing and Digital Technologies 8, no. 1 (2024): 150–61. https://doi.org/10.15276/mdt.8.1.2024.10.

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The aim of the article. The purpose of the article is to define modern challenges and prospects for the development of digital marketing using digital tools in conditions of uncertainty and dynamism of the business environment. The tasks of the article are: identify challenges in digital marketing; to form prospects for the development of digital marketing in modern conditions; identify the key areas of digital marketing development; to identify digital tools that are useful for the implementation of key areas of digital-marketing development. Analyses results. The article examines modern chal

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Leonenko, E. A., and S. V. Kunev. "RESEARCH OF THE COMPANY’S MARKETING ENVIRONMENT BASED ON DIGITAL TECHNOLOGY TOOLS AND A PROCESS FRAMEWORK." Scientific Review Theory and Practice 11, no. 7 (2021): 2122–37. http://dx.doi.org/10.35679/2226-0226-2021-11-7-2122-2137.

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The study of the marketing environment of an enterprise is one of the most difficult types of marketing activities, since it always contains an element of foreseeing a difficult and contradictory socio-economic object – the market, therefore, the content and forms of research of the marketing environment depend on the eco- nomic structure, external and internal conditions in which it is develops, and can vary significantly. In the 21st century, the processes of growth in the use of various digital tools in various areas of business are seriously accelerating. At the same time, the catalyst for

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Tsoi, Kelvin K. F., Felix C. H. Chan, Hoyee W. Hirai, et al. "Data Visualization with IBM Watson Analytics for Global Cancer Trends Comparison from World Health Organization." International Journal of Healthcare Information Systems and Informatics 13, no. 1 (2018): 45–54. http://dx.doi.org/10.4018/ijhisi.2018010104.

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Visual analytics is widely used to explore data patterns and trends. This work leverages cancer data collected by World Health Organization (WHO) across a hundred of cancer registries worldwide. In this study, the authors present a visual analytics platform, IBM Watson Analytics, to explore the patterns of global cancer incidence. They included 26 forms of cancers from eight different geographic regions which are United States, the United Kingdom, Costa Rica, Sweden, Croatia, Japan, Hong Kong and China (Shanghai). An interactive interface was applied to plot a choropleth map to show global can

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Hoyt, Robert Eugene, Dallas Snider, Carla Thompson, and Sarita Mantravadi. "IBM Watson Analytics: Automating Visualization, Descriptive, and Predictive Statistics." JMIR Public Health and Surveillance 2, no. 2 (2016): e157. http://dx.doi.org/10.2196/publichealth.5810.

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Sribharathi, B., B. Vimal Mathew, MLA Sai Sethu, R. Dharanidharan, and A. Hareesh Kumar. "AI-POWERED TOOL FOR SUMMARIZING LARGE VOLUME OF CONTENT." International Scientific Journal of Engineering and Management 04, no. 04 (2025): 1–8. https://doi.org/10.55041/isjem02865.

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Abstract—This project focuses on developing an AI-powered tool for efficiently summarizing large volumes of content using the IBM Watson platform. With the rapid growth of digital information, it has become increasingly challenging for individuals and businesses to process and extract key insights from lengthy documents, articles, and reports. The tool leverages advanced natural language processing (NLP) and machine learning algorithms available through IBM Watson’s suite of AI services, including Watson Natural Language Understanding and Watson Discovery. By analyzing textual content and iden

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Researcher. "ADVANCING CLINICAL DECISION SUPPORT: A TECHNICAL ANALYSIS OF IBM WATSON HEALTH'S AI-DRIVEN HEALTHCARE ANALYTICS PLATFORM." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 7, no. 2 (2024): 1265–75. https://doi.org/10.5281/zenodo.14170059.

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This technical article comprehensively examines IBM Watson Health's AI-driven healthcare analytics platform, focusing on its implementation framework and clinical applications. The article explores the platform's advanced analytics capabilities, diagnostic support systems, and specialized oncology applications while providing detailed insights into its technical architecture and deployment methodologies. The article demonstrates how machine learning algorithms, real-time analytics processing, and sophisticated data integration mechanisms work together to create an effective healthcare decision

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Bensberg, Frank, Gunnar Auth, and Christian Czarnecki. "Einsatz von Text Analytics zur Unterstützung literaturintensiver Forschungsprozesse." Anwendungen und Konzepte der Wirtschaftsinformatik, no. 8 (December 20, 2018): 6. http://dx.doi.org/10.26034/lu.akwi.2018.3221.

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Das anhaltende Wachstum wissenschaftlicher Veröffentlichungen wirft die Fragestellung auf, wie Literaturana-lysen im Rahmen von Forschungsprozessen digitalisiert und somit produktiver realisiert werden können. Insbesondere in informationstechnischen Fachgebieten ist die Forschungspraxis durch ein rasant wachsendes Publikationsaufkommen gekennzeichnet. Infolgedessen bietet sich der Einsatz von Methoden der Textanalyse (Text Analytics) an, die Textdaten automatisch vorbereiten und verarbeiten können. Erkenntnisse entstehen dabei aus Analysen von Wortarten und Subgruppen, Korrelations- sowie Zeit

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Guidi, Gabriele, Roberto Miniati, Matteo Mazzola, and Ernesto Iadanza. "Case Study: IBM Watson Analytics Cloud Platform as Analytics-as-a-Service System for Heart Failure Early Detection." Future Internet 8, no. 3 (2016): 32. http://dx.doi.org/10.3390/fi8030032.

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Marshall, Thomas Edward, and Sherwood Lane Lambert. "Cloud-Based Intelligent Accounting Applications: Accounting Task Automation Using IBM Watson Cognitive Computing." Journal of Emerging Technologies in Accounting 15, no. 1 (2018): 199–215. http://dx.doi.org/10.2308/jeta-52095.

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ABSTRACT This paper presents a cognitive computing model, based on artificial intelligence (AI) technologies, supporting task automation in the accounting industry. Drivers and consequences of task automation, globally and in accounting, are reviewed. A framework supporting cognitive task automation is discussed. The paper recognizes essential differences between cognitive computing and data analytics. Cognitive computing technologies that support task automation are incorporated into a model delivering federated knowledge. The impact of task automation on accounting job roles and the resultin

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Nagwanshi, Kapil Kumar, and Sipi Dubey. "Statistical Feature Analysis of Human Footprint for Personal Identification Using BigML and IBM Watson Analytics." Arabian Journal for Science and Engineering 43, no. 6 (2017): 2703–12. http://dx.doi.org/10.1007/s13369-017-2711-z.

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Choi, Youngkeun, and Jae W. Choi. "Assessing the Predictive Performance of Machine Learning in Direct Marketing Response." International Journal of E-Business Research 19, no. 1 (2023): 1–12. http://dx.doi.org/10.4018/ijebr.321458.

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This paper intends to better understand the pre-exercise of modeling for direct marketing response prediction and assess the predictive performance of machine learning. For this, the authors are using a machine learning technique in a dataset of direct marketing, which is available at IBM Watson Analytics in the IBM community. In the results, first, among all variables, customer lifetime value, coverage, employment status, income, marital status, monthly premium auto, months since last claim, months since policy inception, renew offer type, and the total claim amount is shown to influence dire

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Bhanu Pratap Singh. "ML and Legal Analytics: A Computational Approach to Case Outcome Prediction in Legal Management." Communications on Applied Nonlinear Analysis 32, no. 5s (2024): 43–50. https://doi.org/10.52783/cana.v32.2945.

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The legal industry has undergone a transformation through the combination of machine learning and artificial intelligence techniques. This work focuses the application of such approaches in legal management and also explores how these techniques are useful in various aspects of legal service. With this work, there is an analysis done using case studies from leading organisations such as Lex Machina, JP Morgan, Deloitte, IBM Watson, All State insurance and others. We show that the potential of machine learning is useful in improving the efficiency and decision making in these processes applied

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Anuja, More, and Unnikrishnan Roshin. "AI-Powered Analytics in Product Marketing Optimizing Customer Experience and Market Segmentation." Sarcouncil Journal of Multidisciplinary 4, no. 11 (2024): 12–19. https://doi.org/10.5281/zenodo.14057597.

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This study explores the role of AI-powered analytics in transforming product marketing, focusing on how AI-driven tools enhance customer experience, optimize market segmentation, and drive personalized engagement. Through a mixed-methods approach, we assess the effectiveness of AI tools, including Salesforce Einstein, IBM Watson, Google Analytics 360, and Microsoft Azure ML, in refining segmentation strategies, improving customer satisfaction, and enabling real-time adjustments. Our findings indicate that AI enables precise behavioral, predictive, and sentiment-based segmentation, which signif

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Kashyap, Gaurav. "AI in Blockchain-Enabled Healthcare Systems." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 12 (2024): 1–7. https://doi.org/10.55041/ijsrem17947.

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The integration of Artificial Intelligence (AI) and Blockchain technology offers transformative potential for the healthcare industry. Blockchain provides a secure, immutable, and transparent infrastructure for managing healthcare data, while AI enhances decision-making, predictive analytics, and personalized treatment. This research paper explores the synergies between AI and Blockchain in healthcare systems, focusing on how these technologies can improve patient care, streamline operations, enhance data security, and address key challenges like interoperability and trust. Through case studie

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Ahmed, Mohammed Imtyaz, and G. Kannan. "Secure End to End Communications and Data Analytics in IoT Integrated Application Using IBM Watson IoT Platform." Wireless Personal Communications 120, no. 1 (2021): 153–68. http://dx.doi.org/10.1007/s11277-021-08439-7.

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Researcher. "NATURAL LANGUAGE PROCESSING IN CUSTOMER INTELLIGENCE: A FRAMEWORK FOR UNSTRUCTURED DATA ANALYSIS." International Journal of Computer Engineering and Technology (IJCET) 15, no. 6 (2024): 864–77. https://doi.org/10.5281/zenodo.14264818.

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This article presents a comprehensive framework for leveraging Natural Language Processing (NLP) technologies in the analysis of unstructured customer data, addressing the growing need for sophisticated data analytics in business intelligence. Through a systematic implementation of sentiment analysis and topic modeling techniques, including VADER and Latent Dirichlet Allocation (LDA), the article demonstrates how organizations can extract actionable insights from diverse data sources including social media, customer feedback, and service interactions.The article employs a multi-modal approach,

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Varenko, Volodymyr. "Operational (Online) Analytics: New Technologies and Opportunities." Ukrainian Journal on Library and Information Science, no. 9 (June 17, 2022): 10–21. http://dx.doi.org/10.31866/2616-7654.9.2022.259140.

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The aim of the article is to systematise and generalise new knowledge on operational analytics and consider specific automated information systems in terms of the present and prospects for its development. The research methodology was based on the general scientific principles of unity of theory and practice, systematics, complexity, and comprehensiveness of knowledge. The use of general scientific (description, analysis, synthesis, comparison, generalisation) and special (bibliographic, sample observation, grouping, content analysis) methods at the empirical and theoretical levels of resea

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Wrzeszczynski, Kazimierz O., Mayu O. Frank, Takahiko Koyama, et al. "Comparing sequencing assays and human-machine analyses in actionable genomics for glioblastoma." Neurology Genetics 3, no. 4 (2017): e164. http://dx.doi.org/10.1212/nxg.0000000000000164.

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Objective:To analyze a glioblastoma tumor specimen with 3 different platforms and compare potentially actionable calls from each.Methods:Tumor DNA was analyzed by a commercial targeted panel. In addition, tumor-normal DNA was analyzed by whole-genome sequencing (WGS) and tumor RNA was analyzed by RNA sequencing (RNA-seq). The WGS and RNA-seq data were analyzed by a team of bioinformaticians and cancer oncologists, and separately by IBM Watson Genomic Analytics (WGA), an automated system for prioritizing somatic variants and identifying drugs.Results:More variants were identified by WGS/RNA ana

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Balan, Shilpa, and Janhavi Rege. "Mining for Social Media: Usage Patterns of Small Businesses." Business Systems Research Journal 8, no. 1 (2017): 43–50. http://dx.doi.org/10.1515/bsrj-2017-0004.

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AbstractBackground: Information can now be rapidly exchanged due to social media. Due to its openness, Twitter has generated massive amounts of data. In this paper, we apply data mining and analytics to extract the usage patterns of social media by small businesses. Objectives: The aim of this paper is to describe with an example how data mining can be applied to social media. This paper further examines the impact of social media on small businesses. The Twitter posts related to small businesses are analyzed in detail. Methods/Approach: The patterns of social media usage by small businesses a

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Varenko, Volodymyr. "Operational (Online) Analytics: New Technologies and Opportunities." Ukrainian Journal on Library and Information Science, no. 9 (June 17, 2022): 10–21. https://doi.org/10.31866/2616-7654.9.2022.259140.

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The aim of the article is to systematise and generalise new knowledge on operational analytics and consider specific automated information systems in terms of the present and prospects for its development. The research methodology was based on the general scientific principles of unity of theory and practice, systematics, complexity, and comprehensiveness of knowledge. The use of general scientific (description, analysis, synthesis, comparison, generalisation) and special (bibliographic, sample observation, grouping, content analysis) methods at the empirical and theoretica

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Pérez-Gutiérrez, Boris Rainiero. "Comparación de técnicas de minería de datos para identificar indicios de deserción estudiantil, a partir del desempeño académico." Revista UIS Ingenierías 19, no. 1 (2020): 193–204. http://dx.doi.org/10.18273/revuin.v19n1-2020018.

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Uno de los grandes retos en las instituciones educativas consiste en poder establecer la posibilidad de retiro o deserción de sus estudiantes. En este artículo se presentan los resultados de un estudio de comparación de técnicas para apoyar la identificación de deserción estudiantil a partir del registro académico de los estudiantesde una Universidad en Colombia para el programa de Ingeniería de Sistemas. El registro académico se estableció para un periodo de 7 años. Árboles de decisión, regresión logística y Naive Bayes, fueron comparados para lograr establecer la mejor técnica de detección d

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Perţa, Emanuelle I. "Evaluating Data Science Tools: A Comparative Analysis of Platforms." General Mathematics 32, no. 1 (2024): 73–86. https://doi.org/10.2478/gm-2024-0006.

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Abstract This study targets organizations in the data science domain seeking optimal platforms for their operations. It employs experimental research using the comparison method and mathematical modeling integrated into the Global Utility Method and TOPSIS Method. The aim is to create hierarchies of three prominent data science platforms: IBM Watson Studio, SAS – Advanced Analytics Software and Google Cloud AI Platform. The analysis was conducted using Microsoft Excel. Various comparison criteria are meticulously applied to ensure mathematical correctness and comprehensiveness. The Data Scienc

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Freeman, Daniel, Shaurya Gupta, D. Hudson Smith, et al. "Watson on the Farm: Using Cloud-Based Artificial Intelligence to Identify Early Indicators of Water Stress." Remote Sensing 11, no. 22 (2019): 2645. http://dx.doi.org/10.3390/rs11222645.

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As demand for freshwater increases while supply remains stagnant, the critical need for sustainable water use in agriculture has led the EPA Strategic Plan to call for new technologies that can optimize water allocation in real-time. This work assesses the use of cloud-based artificial intelligence to detect early indicators of water stress across six container-grown ornamental shrub species. Near-infrared images were previously collected with modified Canon and MAPIR Survey II cameras deployed via a small unmanned aircraft system (sUAS) at an altitude of 30 meters. Cropped images of plants in

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Nicholas, Musau, and Ochieng Kuja Josiah. "A review of predictive analysis techniques of diabetes prevalence." International Journal of Biomolecules and Biomedicine (IJBB) 8, no. 1 (2018): 1–9. https://doi.org/10.5281/zenodo.8312753.

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Diabetes is a significant cause of mortality and morbidity in different continents of the world. Many diabetes victims are found in developing countries like Sub-Saharan Africa. However, some developed nations like United States and Europe record significant records on diabetes prevalence. Studies project a dramatic increase of the infection spread in the world. Also, it provides visible results on the effects of the infection among the victims and the society at large. Studies of type 2 diabetes prevalence indicate minimal rates in rural population and moderate results in the developed region

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Vishwadeep Saxena. "AI-Driven Wildfire Management: An Integrated Approach to Detection, Prevention, and Response." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 2125–33. https://doi.org/10.32628/cseit251112178.

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This comprehensive article explores the integration of artificial intelligence in wildfire management systems, presenting an innovative approach to detection, prevention, and response strategies. The article examines how AI technologies transform traditional firefighting methods through advanced sensing, predictive analytics, and resource optimization. The article encompasses various aspects of modern wildfire management, including drone-based surveillance, IoT sensor networks, and machine learning algorithms for fire behavior prediction. The article analyzes the implementation of automated ri

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Omankwu, Obinnaya Chinecherem Osodeke Efe Charlse Ubah Valetine Ifeanyi. "Artificial Intelligence a Paradigm Shift in Healthcare Sector Past, Present and Future Prospects." Journal of Science and Technology Research 5, no. 3 (2023): 201–11. https://doi.org/10.5281/zenodo.8348838.

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<em>Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing

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Feliciano, Joseph, Machaon Bonafede, Donna McMorrow, Julie Park, Julie Lisano, and Thomas Manley. "Real World Prevalence of Diagnostic Revision Among Patients with Peripheral T-Cell Lymphomas (PTCL) in the US: Results of an Administrative Claims and Electronic Medical Record Analyses." Blood 132, Supplement 1 (2018): 1633. http://dx.doi.org/10.1182/blood-2018-99-117104.

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Abstract Introduction: Peripheral T-cell lymphomas (PTCL) are a rare heterogeneous group of lymphoid malignancies, which originate from post-thymic (or mature) T-cells. Although there are approximately 7,000 new cases of PTCL in the US annually, PTCL is extremely heterogenous and difficult to diagnose even in academic settings (Teras et al. 2016. CA Cancer J Clin 2016; 66:443-459). Prior research suggests a high rate of diagnostic revision among PTCL patients. The objective of this analysis was to describe the rate of diagnostic revision among patients with a PTCL diagnosis using 2 large, real

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Bhamidipati, Maheeza. "Dual Convergence: AI Technologies Transforming Trust Paradigms in Healthcare and Financial Services." European Journal of Computer Science and Information Technology 13, no. 39 (2025): 38–53. https://doi.org/10.37745/ejcsit.2013/vol13n393853.

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This article analyzes the transformative impact of artificial intelligence on healthcare and financial services, highlighting how AI technologies are fundamentally reshaping trust paradigms in these critical sectors. The article examines four key capabilities driving AI adoption: efficiency enhancements, automation capabilities, enhanced security frameworks, and predictive analytics. Through detailed case studies of pioneering systems like IBM Watson Health, Google DeepMind, PathAI, and Viz.ai in healthcare, alongside Darktrace, Zest AI, Kensho, and DataRobot in financial services, the paper d

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Swapnil Chawande. "The role of Artificial Intelligence in cybersecurity." World Journal of Advanced Engineering Technology and Sciences 11, no. 2 (2024): 683–96. https://doi.org/10.30574/wjaets.2024.11.2.0014.

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AI implementation in cybersecurity frameworks became necessary due to rising cyber threat complexity and frequency that made standard security measures insufficient. This research analyzes how Artificial Intelligence helps security practitioners identify cyber threats at higher velocities and with greater accuracy than standard procedures. The paper studies how machine learning with natural language processing and behavioral analytics transforms cybersecurity systems by detecting irregularities while performing automatic threat defense operations. Through their qualitative research design and

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Chow, James C. L., Valerie Wong, Leslie Sanders, and Kay Li. "Developing an AI-Assisted Educational Chatbot for Radiotherapy Using the IBM Watson Assistant Platform." Healthcare 11, no. 17 (2023): 2417. http://dx.doi.org/10.3390/healthcare11172417.

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Objectives: This study aims to make radiotherapy knowledge regarding healthcare accessible to the general public by developing an AI-powered chatbot. The interactive nature of the chatbot is expected to facilitate better understanding of information on radiotherapy through communication with users. Methods: Using the IBM Watson Assistant platform on IBM Cloud, the chatbot was constructed following a pre-designed flowchart that outlines the conversation flow. This approach ensured the development of the chatbot with a clear mindset and allowed for effective tracking of the conversation. The cha

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C S, Anu. "Extract and Organize Information in Images with AI using IBM Services." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (2022): 2031–35. http://dx.doi.org/10.22214/ijraset.2022.45670.

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Abstract: OCR is a short form of Optical character recognition or optical character reader. By the full form, we can understand it is something that can read content present in the image. Every image in the world contains any kind of object in it and some of them have characters that can be read by humans easily, programming a machine to read them can be called OCR. In machine learning, data mining is one of the major sections that cover the extraction of the data from the different platforms. OCR (Optical Character Recognition) is part of the data mining process that mainly deals with typed,

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Yadav, Dr Neha. "AI in Cybersecurity: A Literature review." International Scientific Journal of Engineering and Management 04, no. 05 (2025): 1–7. https://doi.org/10.55041/isjem03378.

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Abstract - In cybersecurity, artificial intelligence is revolutionizing incident response, risk management, and threat identification in a progressively hostile cyber threat landscape. This research presents a thorough literature review on AI in cybersecurity, focusing on both aspects of the balance sheet. This paper discusses how AI-driven technologies like machine learning, deep learning, natural language processing, and expert systems improve security frameworks through predictive analytics, real-time threat intelligence, and anomaly detection. The research explores various uses of AI such

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Jung, Soon-Gyo, Joni Salminen, and Bernard J. Jansen. "Engineers, Aware! Commercial Tools Disagree on Social Media Sentiment: Analyzing the Sentiment Bias of Four Major Tools." Proceedings of the ACM on Human-Computer Interaction 6, EICS (2022): 1–20. http://dx.doi.org/10.1145/3532203.

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Large commercial sentiment analysis tools are often deployed in software engineering due to their ease of use. However, it is not known how accurate these tools are, and whether the sentiment ratings given by one tool agree with those given by another tool. We use two datasets - (1) NEWS consisting of 5,880 news stories and 60K comments from four social media platforms: Twitter, Instagram, YouTube, and Facebook; and (2) IMDB consisting of 7,500 positive and 7,500 negative movie reviews - to investigate the agreement and bias of four widely used sentiment analysis (SA) tools: Microsoft Azure (M

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TP, Krishna Kumar, M. Ramachandran, Vidhya Prasanth, and Chandrasekar Raja. "Developing Business Services Using IBM SPSS Statistics." REST Journal on Banking, Accounting and Business 2, no. 1 (2023): 40–50. http://dx.doi.org/10.46632/jbab/2/1/9.

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Developing Business Services. This study examines business development services for entrepreneurs, which should be offered in various phases. Non-financial services and products are defined as business services. “Business services” is a common term used to describe supportive but firm objects and non-productive work. Information technology (IT) is an important supporting service in many businesses, such as shipping and finance. A good business service aligns with the company’s IT assets, employees, and customers’ requirements, supports business goals, and facilitates company profitability. The

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Walter, Angela Wangari, Randall P. Ellis, and Yiyang Yuan. "Health care utilization and spending among privately insured children with medical complexity." Journal of Child Health Care 23, no. 2 (2018): 213–31. http://dx.doi.org/10.1177/1367493518785778.

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Children with medical complexity have high health service utilization and health expenditures that can impose significant financial burdens. This study examined these issues for families with children enrolled in US private health plans. Using IBM Watson/Truven Analytics℠ MarketScan® commercial claims and encounters data (2012–2014), we analyzed through regression models, the differences in health care utilization and spending of disaggregated health care services by health plan types and children’s medical complexity levels. Children in consumer-driven and high-deductible plans had much highe

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Wilhelm, Anja, and Wolfgang Ziegler. "Extending semantic context analysis using machine learning services to process unstructured data." SHS Web of Conferences 102 (2021): 02001. http://dx.doi.org/10.1051/shsconf/202110202001.

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The primary focus of technical communication (TC) in the past decade has been the system-assisted generation and utilization of standardized, structured, and classified content for dynamic output solutions. Nowadays, machine learning (ML) approaches offer a new opportunity to integrate unstructured data into existing knowledge bases without the need to manually organize information into topic-based content enriched with semantic metadata. To make the field of artificial intelligence (AI) more accessible for technical writers and content managers, cloud-based machine learning as a service (MLaa

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Sari, Herva Emilda, Benelekser Tumanggor, and David Efron. "Improving Educational Outcomes Through Adaptive Learning Systems using AI." International Transactions on Artificial Intelligence (ITALIC) 3, no. 1 (2024): 21–31. http://dx.doi.org/10.33050/italic.v3i1.647.

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Adaptive learning systems powered by AI have transformed education by offering personalized learning experiences tailored to individual student needs, enhancing engagement and outcomes. This study examines the impact of AI-driven adaptive learning systems on educational outcomes across diverse settings using a mixed-methods approach. Quantitative data were collected through pre- and post-assessments, surveys, and system analytics, while qualitative insights were obtained via interviews. Participants included 300 students and 50 educators spanning primary to higher education. Findings revealed

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Rios-Campos, Carlos, Sandra Marcela Zapata Vega, Mariuxi Ileana Tejada-Castro, et al. "Artificial Intelligence and Business." South Florida Journal of Development 4, no. 9 (2023): 3547–64. http://dx.doi.org/10.46932/sfjdv4n9-015.

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Abstract (sommario):

The general objective of the research was to determine the advances related to the artificial intelligence and business. The specific objectives of the research are to identify the software of AI used in business and the countries that invest more in AI. Methodology, in this research, 62 documents have been selected, carried out in the period 2018 - 2023; including: scientific articles, review articles and information from websites of recognized organizations. Results, every day new AI tools appear that support activities in today's businesses. Conclusions, about the general objective of the r

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Lee, Linda W., Amir Dabirian, Ian P. McCarthy, and Jan Kietzmann. "Making sense of text: artificial intelligence-enabled content analysis." European Journal of Marketing 54, no. 3 (2020): 615–44. http://dx.doi.org/10.1108/ejm-02-2019-0219.

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Purpose The purpose of this paper is to introduce, apply and compare how artificial intelligence (AI), and specifically the IBM Watson system, can be used for content analysis in marketing research relative to manual and computer-aided (non-AI) approaches to content analysis. Design/methodology/approach To illustrate the use of AI-enabled content analysis, this paper examines the text of leadership speeches, content related to organizational brand. The process and results of using AI are compared to manual and computer-aided approaches by using three performance factors for content analysis: r

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De, Hemangee, and Koushik Deb. "Does Social Media Follow News Media?" International Journal of Information Communication Technologies and Human Development 13, no. 4 (2021): 72–82. http://dx.doi.org/10.4018/ijicthd.2021100102.

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Today, sentiment analysis is in high use to understand user reactions. In this paper, the authors have discussed this topic using news and Twitter texts as sources of data. They use TextBlob, VADER, and IBM Watson NLU as sentiment analysis tools. The news sentiment analysis data is from January to July 2020, classified under each tool. The authors get almost the same result from all of them. February shows having the maximum negative polarity news, followed by June. While Twitter data of each month when classified under each sentiment analysis tool shows the same kind of result for all the mon

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Pragati, Sontake*. "A Review on Artificial Intelligence (AI) Tools in Research Writing." International Journal of Scientific Research and Technology 2, no. 5 (2025): 85–102. https://doi.org/10.5281/zenodo.15331079.

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Abstract (sommario):

The rapid advancements in artificial intelligence (AI) have transformed research writing, improving efficiency and accuracy across various stages. This review explores essential AI tools used from literature surveys to final submission. Tools like Semantic Scholar, Iris.ai, and Connected Papers help in retrieving relevant research, summarizing content, and visualizing relationships between studies. For research design and idea generation, platforms like ChatGPT and Jasper aid in formulating research questions and structuring drafts. In the manuscript drafting phase, tools like WriteSonic 

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Schwartz, Steven M., Brigid Byrd, Helen Dempster, and Tim Payne. "The Promise of Small Data for Telemedicine in Chronic Condition Management: A Real-World Case Series." Clinical Trials and Practice – Open Journal 4, no. 1 (2021): 1–9. http://dx.doi.org/10.17140/ctpoj-4-117.

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Connected care is defined as the “real-time, electronic communication between a patient and a provider, including telehealth, remote patient monitoring, and secure email communication between clinicians and their patients” (Alliance of Connected Care). Connected care can create a high-value interaction strategy with patients when it makes thoughtful use of commercially available digital health technologies with demonstrated both clinical and economic effectiveness. Karantis360™, is a home sensor technology that enables real-time tracking, data analytics and predictive care for personal (at hom

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Gunjawale, Prachi. "Adaptive Job Search and Recruitment Using AI." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42663.

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“The rapid advancement of Artificial Intelligence (AI) has transformed the recruitment landscape, enabling more efficient, data-driven, and adaptive job search mechanisms. Traditional hiring methods often suffer from inefficiencies such as lengthy hiring cycles, unconscious bias, and poor candidate-job matching. AI-driven recruitment systems address these challenges by automating resume screening, analyzing candidate behavior, and providing personalized job recommendations. This paper explores the role of AI in recruitment, focusing on machine learning (ML), natural language processing (NLP),

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Soelistyowati, Rr Dinar, and Sri Ekowati. "The Algorithm of Digital Technology for Communication." Jurnal Penelitian Pendidikan IPA 11, no. 5 (2025): 255–60. https://doi.org/10.29303/jppipa.v11i5.10930.

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This paper explores effectively utilize digital technology for a campaign or communication. A solid algorithm-driven approach can be implemented to ensure data-driven decisions, targeted messaging, and high engagement. Citizens can easily actively disseminate political issues through existing social media platforms. This research uses descriptive research with a qualitative approach with a literature study approach. The data collection technique in this research is to conduct a literature search that is current and compatible with the research theme. The results of the study show that social m

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Mustikaningsih, Marlina, and Atef Fahrudin. "Tantangan dan Peluang Dunia PR di Era Kecerdasan Buatan : Sebuah Tinjauan Literatur." JIKA (Jurnal Ilmu Komunikasi Andalan) 7, no. 1 (2024): 99–110. http://dx.doi.org/10.31949/jika.v7i1.10145.

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This study focuses on the challenges and opportunities of implementing artificial intelligence (AI) in the field of Public Relations (PR). The main issues addressed are the lack of technical understanding among PR practitioners and the ethical and privacy concerns arising from AI usage. The purpose of this study is to analyze how AI can enhance operational efficiency and the effectiveness of communication strategies, as well as to identify new metrics introduced by AI. The method used is a literature review from various academic and industry sources, including scientific journals, books, indus

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