Category Archives: Uncategorized

AI in Continuous Blood Glucose Monitoring Systems
Authors:-Nagesh M S

Abstract-Continuous Blood Glucose Monitoring (CGM) systems have revolutionized diabetes management by providing real-time insights into glucose fluctuations, enabling patients and healthcare providers to take proactive measures. The integration of Artificial Intelligence (AI) into CGM systems has significantly enhanced their efficiency, accuracy, and predictive capabilities. AI algorithms analyze complex and voluminous glucose data to identify patterns, predict future trends, and offer personalized recommendations. This paper explores the applications of AI in CGM, examining how machine learning and deep learning models are being used for improved glycemic control, early detection of glucose anomalies, behavior prediction, and adaptive insulin therapy. It also discusses the impact of AI-driven CGMs on patient engagement, remote monitoring, and clinical decision-making. Ethical concerns, data privacy, and technological limitations are also addressed. This comprehensive analysis underscores AI’s transformative role in reshaping diabetes care, making it more precise, predictive, and patient-centric.

DOI: 10.61137/ijsret.vol.11.issue2.379

Published by: vikaspatanker

AI-Powered Patient Flow Optimization in Emergency Rooms
Authors:-Kumar S

Abstract-Emergency Rooms (ERs) are high-pressure environments characterized by unpredictability, time-sensitive decisions, and often overcrowding. These conditions, when not optimally managed, can lead to prolonged wait times, increased medical errors, clinician burnout, and compromised patient outcomes. As healthcare systems strive to deliver efficient, equitable, and timely emergency care, Artificial Intelligence (AI) has emerged as a transformative force. AI-powered patient flow optimization employs machine learning, predictive analytics, and intelligent decision support systems to streamline triage, resource allocation, and care coordination. This paper explores how AI is revolutionizing emergency room operations by enhancing real-time decision-making, reducing bottlenecks, forecasting demand, and personalizing patient care pathways. It also examines the integration of AI tools into clinical workflows, the ethical and infrastructural challenges of implementation, and the future of AI-driven operational excellence in emergency healthcare settings.

DOI: 10.61137/ijsret.vol.11.issue2.378

Published by: vikaspatanker

Integrating AI into Pediatric Health Management

Authors:-Varsha

Abstract-The application of Artificial Intelligence (AI) in healthcare has shown tremendous potential in various domains, yet one of its most impactful and delicate arenas is pediatric health management. Children are not merely miniature adults; their physiological, psychological, and developmental needs are distinct and require tailored approaches in clinical care. Pediatric health management is particularly complex, involving routine checkups, vaccinations, developmental monitoring, chronic disease management, and acute care—all while ensuring minimal invasiveness and maximum safety. Integrating AI into this domain promises transformative improvements in diagnosis, treatment planning, patient monitoring, early detection of developmental disorders, and personalized health interventions. This paper explores the significant role of AI in pediatric healthcare, examining current applications, challenges, ethical considerations, and future possibilities. By analyzing the technological advancements and real-world implementations of AI in pediatrics, this research underscores the importance of intelligent systems in ensuring the long-term health and well-being of children.

DOI: 10.61137/ijsret.vol.11.issue2.377

Published by: vikaspatanker

AI-Enhanced Decision Support for Radiology Technicians
Authors:-Pavan T.K

Abstract-The exponential rise in diagnostic imaging demands has outpaced the capacity of radiologists and radiology technicians worldwide, creating a bottleneck in timely and accurate diagnosis. Artificial Intelligence (AI) has emerged as a revolutionary tool in the field of radiology, particularly as a decision support system for radiology technicians. While much of the AI research in medical imaging focuses on automating radiologist tasks, the integration of AI tools into radiology technician workflows presents a valuable, underexplored frontier. This paper investigates the role of AI in assisting radiology technicians by enhancing image acquisition quality, automating repetitive tasks, supporting error detection, and optimizing workflow management. It also discusses AI’s contribution to patient safety, data annotation, training, and real-time support during imaging procedures. As AI technology evolves, radiology technicians are increasingly becoming empowered with tools that boost accuracy, improve efficiency, and reduce burnout. The paper also examines ethical, technical, and operational considerations in deploying AI systems in radiological environments, concluding with insights into the future of collaborative human-AI integration in medical imaging.

DOI: 10.61137/ijsret.vol.11.issue2.376

Published by: vikaspatanker

Deep Learning for Liver Segmentation
Authors:-Amarnath Chigurupati. Madhuri Sirasanagandla. Ankit Kommalapati. Siddique Ibrahim Peer Mohammed, Madhuri Sirasanagandla

Abstract-Liver cancer is becoming a huge threat to global health health, where early detection and accurate diagnosis are crucial for effective treatment [1]. Our research on deep learning- A based learning system for automatic segmentation of the liver and The tumor from computed tomography (CT) images is highlighted, using a U-Net model integrated with ResNet-34, which acts as a backbone [2]. This model is trained on the Liver Tumor Segmentation Challenge (LiTS) dataset, which is a standard for This type of problem [2]. Training a high-performance model, The project itself differentiates with the development of a user- friendly GUI with the help of the Python package PyQt5, making It is possible to achieve real- time visualization and user-friendly interaction for the end users like radiologists, students, and researchers [10] . This interface helps in taking input as an image in the form of a JPG, predicts segmentation tasks, and compares the results With the grayscale liver anatomy structures. Our model delivers high accuracy in segmentation, obtaining a high accuracy Dice coefficient of 98.20% with an extraordinary precision, recall, and f-score up to 99.89%, making it usable for real-time scenarios like clinical and research purposes Index Terms—Liver Segmentation, Deep Learning, U-Net, ResNet-34, FastAI, PyQt5.

DOI: 10.61137/ijsret.vol.11.issue2.375/a>

Published by: Kajal Tripathi

Young scholars and students often look for academic and research platforms that provide free publication charge journals. As a newbie in the field they lack motivation and guidance how to complete the publication process without financial support. These platforms provide assistance in getting hands on crucial websites that support young academicians throughout the paper publication process for best free journal publication. Although free publication charge journals exist, they are partially chargeable. This blog will help scholars how a research paper should be written to get accepted by the free of charge journals.

Submit Your Paper  / Check Publication Charges

There are many things that one should pay attention to when publishing research papers.

• Proofread – one should proofread their manuscript prior to submission. Academic or research papers cross various levels to get published. It has to be grammatical error free otherwise get rejected just after the submission.

• Literature review – scholars need to read 10-15 research papers published in related field. This in depth reading of research articles help one to understand the need of the hour, develop critical thinking, highlight prominent areas for research, etc.

• Title – one should keenly pay attention to the research paper title, it plays a crucial role in getting the reader’s attention. An ideal title represents the research paper through the title and helps in discovering different search engines.

• Methodology/survey – scholars should write down the methodologies and source of data collection and inspirations clearly. It will help reviewer in analysing the content easily.

• Result – result section should be well written and presentable enough to attract readers attention, one should include tables, charts, figures, diagrams, graphs to elaborate the outcomes. It is suggested to not interpret each and everything as they all can be discussed in the discussion part of the paper.

• Conclusion – write a well structured conclusion that summarized all the research and present a lasting impression on the readers with some future questions related to the research.

Apart from that, scholars looking for better career opportunities in India and abroad often need to present good academic and research orientation in their research field. Research publication in their respective field can be useful for the further advancement of their career. One can submit their research work in an international journal for scientific research and engineering technology. This journal provide easy and fast publications in the field of science, engineering, social sciences, mathematics and humanities. Authors related to the field can share their manuscripts for review and publications in it.

Published by: Neeraj Mishra

Work –Life Balance of Women Employees: Challenges and Strategies
Authors:-Greeshma Muraly

Abstract-Women across the world encounter difficulties in managing what their professional work and personal life. These research paper exams the difficulties of workload and life balancing in women particularly among working women and entrepreneurs. It analysis the key factors affecting work life balance, the impact of overload on mental and Physical health and Strategies for achieving stability. This paper also highlights policies and support systems that can help woman in managing the responsibilities effectively.

DOI: 10.61137/ijsret.vol.11.issue2.374/a>

Published by: Kajal Tripathi

Speech Emotion Recognition Using CNN
Authors:-Pratiksha Sathe, Dr. Jasbir Kaur, Assistant Professor Suraj Kanal

Abstract-Speech Emotion Recognition (SER) is an evolving and critical field in human-computer interaction, aimed at identifying and interpreting human emotions through speech signals. The ability to recognize emotions accurately from speech has applications in various domains, including mental health diagnostics, customer service, and adaptive learning systems. This paper focuses on leveraging Convolutional Neural Networks (CNN) for SER, emphasizing their capability to perform robust feature extraction and accurate classification. CNNs excel in capturing both spatial and temporal characteristics of audio signals, making them particularly well-suited for processing speech data. By converting speech signals into Log-Mel spectrograms, which effectively represent the spectral and temporal properties of audio, the proposed model achieves high accuracy in recognizing a diverse range of emotions. The study demonstrates the practical application of CNNs for SER, highlights their advantages over traditional machine learning models, and evaluates their performance on benchmark datasets such as RAVDESS and IEMOCAP. The results underscore the potential of CNN-based approaches to advance the field of speech emotion recognition, paving the way for more sophisticated and empathetic human-computer interaction systems.

DOI: 10.61137/ijsret.vol.11.issue2.373/a>

Published by: Kajal Tripathi

Silent Voice -The Sign Language Recognition Android Application Using Machine Learning Algorithm
Authors:-Ms Mitali Pawar, Dr. Jasbir Kaur, Assistant Professor Ms.Sandhya Thakkar

Abstract-Sign language is an essential communication tool for people with speech and hearing impairments.”[4] The creation of an Android application for sign language recognition using machine learning methods is presented in this study. The program facilitates communication between sign language users and non-sign language users by using OpenCV and a machine learning model to process images and transform hand gestures into text. Real-time alphabetic sign recognition from live video input is possible with the suggested approach. The application guarantees effective gesture detection with low resource consumption by using TensorFlow Lite for model inference on mobile devices, which makes it appropriate for Android devices with low processing power. The system’s user-friendly interface facilitates quick and precise translations between sign language and other languages, encouraging inclusion and assisting in the removal of barriers to communication.

DOI: 10.61137/ijsret.vol.11.issue2.372/a>

Published by: Kajal Tripathi

Developing an AI Based Interactive Chatbot for the Department of Justice’s Website
Authors:-Sulake Bhavya Sri Bai, Kamboja Akshith Swamy

Abstract-addition to the Department of Justice website to enhance the virtual experience. The new website upgrade is centered around an artificial intelligence-enabled chatbot that uses Natural Language Processing (NLP) to become more conversational and easier for visitors to interact with when they just speak to it. The DOJ website enhancement also offers a multilingual capability for all citizens, irrespective of their ability. It is powered by a scalable cloud-based infrastructure that ensures high availability and round-the-clock access. Long legal procedures that, regrettably, impede the ability of many regular people to obtain simple information or services are the main goals of this efficiency improvement. Key words: Natural Language Process (NLP), AI chatbot, voice assistant, legal technology, accessibility, public service automation, department of justice, and legal query resolution.

DOI: 10.61137/ijsret.vol.11.issue2.371/a>

Published by: Kajal Tripathi