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72 articles for “Large Language Models”
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RoseRAG-Based Clinical Decision Support System for Precision Medication Safety
Abstract: Medication-related errors remain a major challenge in healthcare, contributing to adverse drug events, increased hospitalization rates, and substantial healthcare costs. Conventional Clinical Decision Support Systems (CDSS) primarily rely on rule-based mechanisms for identifying drug-related problems (DRPs), including drug–drug interactions, contraindications, dosing errors, therapeutic duplication, and medication omissions. Although effective in structured environments, these systems frequently generate excessive context-insensitive alerts, leading to alert fatigue and reduced clinical acceptance. Recent developments in …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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VeriSci—AI-Based Multi-Modal Research Assistant
Abstract: The exponential growth of scientific literature is a major bottleneck for academic researchers who want to efficiently discover, assess, and synthesize relevant scholarly knowledge. Traditional methods of literature review are heavily reliant on manual keyword searching, human screening, and subjective data extraction, making them time-consuming, susceptible to cognitive bias, and less effective as the tidal wave of information continues to grow. To overcome these limitations, this study introduces VeriSci, an …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 2, 2026 · pp. 20–27 Read article
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An Automation Detection for Sign Language Using AI
Abstract: Sign language recognition has attracted considerable interest because of its ability to facilitate communication between the deaf community and the public, thereby bridging communication divides. Traditional approaches to sign language recognition often face challenges in accurately interpreting the complex and nuanced gestures inherent in sign languages. However, recent advancements in deep learning techniques have shown promising results in improving the accuracy and robustness of sign language recognition systems. This study …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 1–14 Read article
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Statistical and AI Approaches to Measure Sustainability Performance of Enterprises
Abstract: Measuring sustainability performance has become a critical priority for enterprises facing increasing regulatory pressure, stakeholder expectations, and global sustainability challenges. Traditional assessment methods, largely based on static indicators and manual reporting, often struggle to capture the multidimensional, dynamic, and data-intensive nature of sustainability. This study explores the integration of statistical and artificial intelligence (AI) approaches to evaluate and enhance the sustainability performance of enterprises in a more robust, accurate, and …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 30–36 Read article
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DATABASE-DRIVEN ENERGY MANAGEMENT IN ELECTRIC VEHICLES
Abstract: With the growing concern over environmental pollution, there is an increasing demand for sustainable and eco-friendly technologies. Among these, electric vehicles (EVs) have emerged as a promising alternative to conventional fossil-fuel-based transportation. However, as EV adoption accelerates, efficient energy management becomes critical to enhance vehicle performance, extend battery life, and ensure overall system reliability. This research presents a Database-Driven Energy Management System (DBEMS) that leverages real-time data from EV components …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 19–24 Read article
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Exploring Technologies for Extractive Text Summarization: A Review of Transformer and Reinforcement Learning Models
Abstract: In recent years, the size of information on the Internet has increased exponentially. Therefore, a solution is needed to transform large amounts of raw data into useful information the human brain can understand. Automatic Text Summarization (ATS) is a part of Natural Language Processing (NLP) that aims to take long texts and shorten them, keeping the most important information in a clear and easy-to-understand way. This research report explores methods …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 1–6 Read article
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AI-based Drug Discovery-Revolutionizing Pharmaceutical Research
Abstract: The traditional drug discovery process is often costly, time-consuming, and prone to high failure rates. The advent of Artificial Intelligence (AI) has revolutionized this field by significantly enhancing efficiency, reducing costs, and improving success rates. AI-driven approaches, including machine learning (ML), deep learning (DL), and natural language processing (NLP), have transformed key areas such as drug target identification, molecular screening, lead optimization, and clinical trial design. AI models can analyze …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 30–44 Read article
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Random Image Steganography and Statistical Generation
Abstract: Steganography is the art of concealing the fact that communication is taking place by enclosing data in other data. There are a variety of carrier file types available, but digital photos are the most popular due to their prevalence on the Internet. There are numerous steganographic ways for hiding secret information in pictures. Some are more complex than others, and each has its own set of advantages and disadvantages. The …
Published in Recent Trends in Parallel Computing · Vol. 8, Issue 3, 2021 · pp. 22–29 Read article
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Segmentation and Classification of Hand Gestures for Indian Sign Language with YCbCr and HSV Color Models with Dissimilar Signers Under Different Lighting Conditions using AlexNet
Abstract: Indian Sign Language (ISL) Recognition System can be implemented by considering the signs as hand gestures and developing a hand gesture recognition system. The impact of illumination changes on the performance of segmentation and classification where different lighting conditions such as normal, bright, dim, and artificial light under different color spaces like RGB, HSV and YCbCr are studied, and performance parameters are analyzed. It is observed that YCbCr color space …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 10, Issue 1, 2023 · pp. 37–50 Read article
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Native Language Identification from Spoken Indian English
Abstract: Automatic speech recognition (ASR) systems that facilitate voice based search and information retrieval have gained importance recently. While the performance of ASR systems for Indian languages have improved in the recent past. They have yet to gain wide acceptability as much as the ASR systems for English spoken by Indians. Almost all Indians learn English as a second or third language. So, the phoneme set and the prosody of native …
Published in Trends in Electrical Engineering · Vol. 9, Issue 2, 2019 · pp. 1–6 Read article
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Integrated Qualitative Response Assessment System
Abstract: Examinations for universities and yearboards are traditionally administered offline, with a significant number of students opting for subjective exams. This preference stems from the labor-intensive nature of evaluating subjective responses, which requires considerable time and effort from educators. Additionally, subjective grading can be influenced by the evaluator’s mood, leading to inconsistencies. In contrast, multiple-choice and objective questions are prevalent in entrance and competitive exams due to their ease of automated …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 18–24 Read article
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Artificial Intelligence in Pharmacovigilance: Improving Drug Safety
Abstract: Artificial intelligence (AI) is revolutionizing pharmacovigilance (PV) by enhancing the detection, assessment, and prevention of adverse drug reactions (ADRs). This review examines how AI technologies – such as machine learning (ML), natural language processing (NLP), and big data analytics – tackle existing challenges in pharmacovigilance (PV), including issues like underreporting, large data volumes, and inefficiencies in data processing. AI improves drug safety by automating data collection, enabling real-time adverse event …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 1–16 Read article
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Website Summarization Using Deep Learning
Abstract: They are a lot of websites, articles and blogs on the internet with a lot of textual information it is sometimes impossible to read all of them, without knowing the underlying summary of the whole text. The whole concept is to reduce or minimize the entire Textual information into a small summary of important information present in the documents so that we get an idea of what the blog or …
Published in Recent Trends in Electronics Communication Systems · Vol. 9, Issue 2, 2022 · pp. 7–12 Read article
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Machine Learning Using Python
Abstract: Machine learning (ML) is a subset of artificial intelligence (AI) that enables software applications to become more accurate at predicting outcomes without explicitly programming them to do so. Machine learning algorithms predict new output values by using historical data as input. In this project, we have used data from the 1994 U.S. Census to model people's income using numerous supervised algorithms of your choice. The best candidate algorithm will then …
Published in Recent Trends in Programming languages · Vol. 8, Issue 3, 2021 · pp. 25–37 Read article
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Comprehensive Review of Moebius Syndrome: Clinical Landscape, Etiology, and Therapeutic Challenges
Abstract: Moebius syndrome, a rare congenital neuromuscular disorder, presents with non-progressive facial weakness, limited eye abduction, and diverse manifestations affecting cranial nerves. This comprehensive review explores its clinical landscape, emphasizing the need for extensive investigations into its elusive etiology and genetic underpinnings. The estimated prevalence is 1 in 250,000 live births, with sporadic cases prevailing. Initial symptoms, evident from birth, encompass difficulties in sucking, and feeding, and absent facial expressiveness. Beyond …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 27–38 Read article
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AI-Powered Pharmacovigilance: Revolutionizing Adverse Drug Reaction Detection, Reporting, and Future Perspectives-A Review
Abstract: Pharmacovigilance is very important in drug safety as it monitors, identifies and prevents adverse drug reactions (ADR). Conventional pharmacovigilance systems are usually limited by underreporting and delay in signal detection as well as the inability to scale up. The pharmacovigilance sphere is undergoing a seismic shift with the arrival of AI. The use of AI-driven tools, such as machine learning and natural language processing, is transforming how ADR detection is …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 01–07 Read article
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Cyberattack Detection and Prevention Using Empowering AI Tools
Abstract: With more organizations entering the digital transformation sphere, the opportunities and risks in cyberspace have increased and gone up in levels of sophistication and occurrence. Many of these developments are attributed to the limits of existing cyber security solutions where addressing new threats requires advanced detection technologies and techniques. Cyber threats gained a new meaning and dimension with artificial intelligence (AI) coming into play in ways that supplement security systems …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data
Abstract: With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 55–65 Read article
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Efficient Design of Pseudo-Random Pattern Generator with High Fault Coverage
Abstract: In this paper a comparative analysis of various test pattern generators is done in terms of power consumed .Testing is a crucial process in VLSI (Very-large-scale integration), not only it ensures proper functioning of the chip ,it also helps identify the common faults that occur as a part of VLSI fabrication. However, the power consumed during the testing process is nearly 40% higher than normal circuit operation. Various test pattern …
Published in Journal of Microelectronics and Solid State Devices · Vol. 1, Issue 1, 2015 · pp. 21–25 Read article
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The Role of Artificial Intelligence in Automating Incident Response in Cloud-Based Cybersecurity
Abstract: As cloud computing continues to gain traction across industries, the complexity and scale of cloud environments present significant challenges to traditional cybersecurity practices. The dynamic and distributed nature of cloud infrastructures necessitates agile and effective incident response mechanisms to detect, analyze, and mitigate threats in real-time. However, conventional incident response methods often fall short due to the growing sophistication of cyber threats and the vast amounts of data generated in …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 15–24 Read article