A STUDY ON THE COMPLETENESS OF PATIENT MEDICAL DOCUMENTATION BY PHYSICIANS IN MULTISPECIALTY HOSPITALS
In multi-specialty hospitals, maintaining comprehensive and accurate medical records is a mechanical necessity for high-quality care, regulatory compliance, and medicolegal protection. While physicians are the primary authors of these clinical records, a focus on care execution over documentation often leads to critical gaps in recording patient pr...
By A. Jasmin, K. Ravichandran, K. Anandhi
METAHEURISTIC-BASED OPTIMIZATION OF COMPOSER DEEP LEARNING MODELS FOR SEPSIS PREDICTION AND CLASSIFICATION
Heterogeneous, high-dimensional, and complex clinical data have remained a key challenge for early sepsis detection in intensive care units. This paper introduces a Hybrid GAP-HMSOA-GNN-COMPOSER architecture that incorporates a graph-based relational model and metaheuristic optimization to learn and generate accurate, reliable sepsis predictions. T...
By K. Sameera, P. Amudhavalli
INFLUENCING FACTORS ON MIGRATION: EVIDENCE AND POLICY IMPLICATIONS FOR AN EMERGING COUNTRY
International migration from developing economies is increasingly driven by the interplay between economic incentives, social networks, and the institutional environment. The understanding of these drivers is central to policy design aimed at maximizing the benefits of labor mobility, minimizing human capital loss, and capturing positive impacts of...
By Dao Tuan Minh
ARTIFICIAL INTELLIGENCE IN AUDITING: EVALUATING THE IMPACT OF GENERATIVE AND PREDICTIVE MODELS ON AUDIT QUALITY AND EFFICIENCY
Artificial intelligence (AI) is significantly contributing to beneficial transformations in auditing by enhancing analytical capabilities, automating monotonous tasks, and refining decision-making processes. This piece of research looks into the effects of predictive and generative AI on the quality of auditing as well as its efficiency. Moreover, ...
By S. Edmund Christopher, Jaishu Antony, Zaheda Daruwala, Mahmoud Abouagwa
EFFICIENTNET-B0-BASED FRAMEWORK FOR AUTOMATED MULBERRY ROOT KNOT DISEASE CLASSIFICATION Based ON LEAF SYMPTOMS USING GRAD-CAM VISUALIZATION
The study is based on the idea of an innovative method of automated classification of mulberry root Knot diseases on the basis of the leaf symptoms through the EfficientMulberryNet-B0-GC model, which is a combination of EfficientNet-B0 and Grad-Cam visualization. The model aims to complement the lack of efficient and transparent disease detection i...
By N. Priyanka, K.G. Mohan
INTELLIGENT FINANCIAL DOCUMENT DIGITISATION AND CLASSIFICATION VIA A HYBRID ATTENTION-GUIDED DUAL PATH CNN WITH ATOMIC ORBITAL SEARCH OPTIMISATION
The financial institution uses different types of documents, including bank statements, cheques, income tax forms, salary slips, and electricity bills. Current approaches deal with either the preprocessing stage, text and feature extraction, or even classification separately and fail to perform efficiently on low-quality, handwritten, and visually ...
By Archana Lopes, Kolla Bhanu Prakash, Yu-Chen Hu
ASSESSING IFRS 15 IMPLEMENTATION EFFECTS ON REVENUE PRACTICES AND ACCOUNTING INFORMATION SYSTEMS IN UAE TELECOM COMPANIES E& AND DU
By comparing e& with du, the study examines how introducing the International Accounting Standard 15 (IFRS 15) affected revenue recognition, revenue measurement, and information systems across UAE telecommunications businesses. The comparison provides evidence from both companies. Because data lacked a normal distribution, the analysis employed...
By Ranya Riyadh Radhi, Hussein Talib Alhamada, Majid Ahmed AL Anssari
LOW-COST REMOTELY-OPERATED VEHICLE NAVIGATION WITH GPS AND RF LORA INTEGRATION
In recent decades, remote-controlled vehicles (ROVs) have attracted significant attention because of their potential applications in healthcare, medicine, agriculture, and civilian information. In this article, we investigate the development of low-cost mobile robots equipped with a global positioning system (GPS). GPS-assisted robot is used to pro...
By Huu Khoa Tran, Viet Thang Le, Thanh Trang Tran, Van Dung Nguyen
ADVANCING DIABETES PREDICTION THROUGH MACHINE LEARNING AND DEEP LEARNING MODELS USING PIMA INDIAN AND CLINICAL-BIOLOGICAL DATA
Diabetes Mellitus is a significant world health and early detection is of paramount significance since it decreases the complications and enables medical intervention in time. The paper is a comparison between the predictive accuracy of the eight Machine Learning classifiers: Logistic Regression, Support Vector Machine (SVM), Decision Tree, Random ...
By Zeeshan Hussain, Suraiya Parveen, Ashif Khan, Ihtiram Raza, Umnah
ANALYZING THE INFLUENCE OF BEHAVIORAL ECONOMICS ON CONSUMER DECISION-MAKING IN SUSTAINABLE PRODUCT MARKETS
The paper discusses the application of behavioral economics in consumer decision-making in the sustainable product market. Behavioral economics is contrasted to the traditional economic theory, which assumes rationality of choices based on the maximization of utility, where behavioral factors, including psychological biases, social norms, and emoti...
By Arasuraja Ganesan, R. Velanganni, Vijayakanthan Selvaraj, M. Rajapriya