Towards Intelligent Automation (IA): literature review on the evolution of Robotic Process Automation (RPA), its challenges, and future trends

J Siderska, L Aunimo, T Süße, J von Stamm… - … in Production and …, 2023 - sciendo.com
ABSTRACT Robotic Process Automation (RPA) and Artificial Intelligence (AI) integration
offer great potential for the future of corporate automation and increased productivity. RPA …

Prediction of mortality from heart failure using machine learning

S Kedia, M Bhushan - … on Emerging Frontiers in Electrical and …, 2022 - ieeexplore.ieee.org
Cardiovascular diseases (CVDs) or heart failure (HF) is a vital cause of death worldwide.
Approximately 17.9 million people die each year, and it accounts for 31% of global deaths in …

Adoption of Low-Code and No-Code Development: A Systematic Literature Review and Future Research Agenda

MO Ajimati, N Carroll, M Maher - Journal of Systems and Software, 2024 - Elsevier
Context Low-code/no-code (LCNC) is an emerging technology trend which expose software
development beyond just the software engineers making it available to everyone in …

Deep learning techniques for prediction and diagnosis of diabetes mellitus

S Pal, N Mishra, M Bhushan, PS Kholiya… - 2022 International …, 2022 - ieeexplore.ieee.org
Diabetes Mellitus (DM) is a serious chronic disease that affects billions of people worldwide.
8.5% of the population suffers from diabetes between the age range of18 to 70 years. In …

Prediction of students' academic performance using Machine Learning Techniques

U Verma, C Garg, M Bhushan, P Samant… - 2022 International …, 2022 - ieeexplore.ieee.org
The prediction of students' academic performance is a subset of Educational Data Mining
(EDM) which deals with the large-scale data gathered from an education system. EDM aims …

Advancements in healthcare services using deep learning techniques

M Rana, M Bhushan - 2022 International mobile and embedded …, 2022 - ieeexplore.ieee.org
Deep learning (DL) is the technique encouraging clinical staff and physicians to work on a
variety of data using DL algorithms. DL techniques have given a rise in the medical facilities …

Methodological approach to assessing the current state of organizations for AI-Based digital transformation

A Aldoseri, KN Al-Khalifa, AM Hamouda - Applied System Innovation, 2024 - mdpi.com
In an era defined by technological disruption, the integration of artificial intelligence (AI) into
business processes is both strategic and challenging. As AI continues to disrupt and …

Implications for sustainability accounting and reporting in the context of the automation-driven evolution of ERP Systems

VF Dumitru, BȘ Ionescu, SM Rîndașu, LEL Barna… - Electronics, 2023 - mdpi.com
This paper delves into the impact of the automation-driven evolution of enterprise resource
planning systems (ERPSs) on sustainability accounting and reporting and the associated …

Prediction of indoor air quality using artificial intelligence

NR Kapoor, A Kumar, A Kumar… - … Intelligence, Big Data …, 2023 - Wiley Online Library
For well‐being and good health, indoor air quality (IAQ) is an important concern as most of
the people spend almost total of their time in different types of buildings. Research in IAQ is …

Text Categorization using Supervised Machine Learning Techniques

I Dawar, N Kumar, S Negi, S Pathan… - 2023 Sixth International …, 2023 - ieeexplore.ieee.org
Text categorization is a task for text mining that involves pattern classification and is
essential for the effective management of textual information systems (TIS). Each document …