Digital journalism has essentially swept the scenery of the contemporary communication as it has transformed the manner in which information gets created, distributed, consumed, and perceived. The ability of the journalism industry to merge with digital technologies including the internet, mobile systems, social media, data analytics, artificial intelligence, and multimedia tools has both increased the speed of news dissemination and the performance of the job and role of a professional journalist. This paper discusses how digital journalism relates to the contemporary communication systems in terms of structural, technological, social, and ethical aspects. The paper discusses the impact of digital journalism concerning news credibility, speed, interactivity, personalization and global reach as well as challenges including misinformation, algorithm bias, downward revenue models and loss of traditional gatekeeping functions. A literature survey is carried out systematically to highlight the prevailing theories and research results in the recent studies. The research approach is a mixed approach of qualitative and quantitative in character, i.e. it uses content analysis, comparative measures, and conceptual modeling to analyze the result(s) of communication in the digital news ecosystem. Findings point to the fact that digital journalism increases the level of participatory communication and immediacy and poses serious threats associated with information overload, lack of trust, and accountability. The conclusion of the paper is that digital journalism enhances democratic communication and inclusiveness to the maximum, but regulatory frameworks, ethical standards, and technological literacy should be sustained to ensure that its beneficial effects on the society are fully realized. The results have a contribution on the communication studies and media research by providing an integrated analytical model that complies with the IEEE scholarly standards.
Anita Verma· International Journal of Mod...· 0 citations
With the rapid development of artificial intelligence (AI), natural language processing (NLP), and mobile health technologies, remote healthcare services have significantly improved. Intelligent healthcare chatbots have emerged as an important tool for providing scalable, affordable, and continuous patient care outside clinical environments. These chatbots use conversational interfaces to deliver medical information, perform symptom checks, schedule appointments, remind patients about medications, provide mental health support, and offer personalized health education. The increasing workload in healthcare systems, shortage of healthcare professionals, and rising chronic diseases have accelerated the adoption of chatbot-based remote care solutions. This paper presents a comprehensive study of intelligent healthcare chatbots for supporting remote patients, including their architecture, features, integration with health information systems, and clinical applications. Modern chatbots employ machine learning models, deep learning-based NLP techniques, and medical knowledge bases to enable context-aware, adaptive, and personalized patient interactions. Healthcare chatbots also improve access to medical services, particularly in underserved and rural areas where healthcare facilities may be limited. The paper further discusses ethical, legal, and privacy concerns such as patient data protection, regulatory compliance, and potential algorithmic bias. Chatbot performance is evaluated using metrics like response accuracy, user satisfaction, task completion rate, and clinical relevance, highlighting their advantages over traditional telehealth methods. The proposed framework integrates multimodal data sources, real-time patient feedback, and active learning techniques to enhance clinical decision-making and patient engagement. Overall, intelligent healthcare chatbots can reduce response time, improve treatment adherence, and enhance patient experience. The study concludes that healthcare chatbots have strong potential to transform remote healthcare delivery while emphasizing the need for further research to improve clinical reliability and regulatory compliance.
Anita Verma· International Journal of Mod...· 0 citations
This work begins with dynamic modeling using the Euler-Lagrange formulation and demonstrates that the proposed hybrid controller outperforms traditional methods in terms of tracking accuracy, settling time, and disturbance rejection.
Anita Verma· International Journal of Int...· 0 citations
It is concluded that MARL is a promising solution for future intelligent collaborative robotics and highlights future research directions including federated reinforcement learning, explainable AI, edge-based robotic intelligence, and adaptive swarm robotics for Industry 4.0 applications.
Suresh Babu Reddy, Anita Verma· International Journal of Int...· 0 citations
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