International Journal of Data Science and Advanced Analytics

Digital Transformation as a Catalyst for Activity-Based Funding Implementation

Ahmed Emad Alhamalawy — 2025-09-01

Activity-Based Funding (ABF) has gained traction globally to enhance hospital reimbursement by linking payments to volume and complexity of care via Diagnosis-Related Groups (DRGs). Empirical evidence on ABF’s effectiveness remains mixed and context dependent. Notably, the Middle East and North Africa (MENA) region lacks rigorous analyses of ABF implementation due to lack of understanding of advanced digital health technologies. This study investigated the role of digital transformation in ABF implementation within Saudi Arabia’s healthcare system considering institutional, organizational, and technological factors. A comparative qualitative case study was employed, analyzing policy documents, implementation reports, and stakeholder interviews. The study applied the framework of the principal-agent theory to interpret incentive structures and utilized a digital maturity lens to assess the integration of health information systems supporting ABF. Findings revealed that ABF reforms were initiated and aligned with national development agendas. Saudi Arabia’s relatively advanced digital health ecosystem has facilitated more effective cost accounting, data integration, and transparency, enabling smoother ABF rollout. This Saudi context underscores the necessity of aligning stakeholder incentives and building organizational capabilities for data-driven decision-making to realize ABF’s efficiency and quality improvement goals. In conclusion, this study contributed to the research dialogue by demonstrating that successful ABF implementation in emerging economies surpasses financial restructuring per se, to leverage digital transformation to overcome systemic barriers. Policymakers are advised to prioritize investments in digital health infrastructure and governance frameworks to support sustainable, value-based healthcare financing reforms in the MENA region.

AI-Driven News Summarisation for Financial Insights: Revolutionising Large Language Models

Shraddha Bhoir — 2025-09-19

Financial professionals rely on timely news to support decision making. However, manually reviewing large volumes of financial news is inefficient particularly when articles are complex and lengthy. Automated text summarisation using large language models (LLMs) offers a promising solution for summarising extensive textual information. This study aims to customise and optimise a text summarisation model for financial news. To achieve this, the study examines the effectiveness of transformer based LLMs by fine-tuning the FLAN-T5-XL model for this domain. Experiments were conducted using a dataset of 2,000 general news articles. Performance was assessed using ROUGE metrics and expert human evaluation. The results show that the fine-tuned FLAN-T5-XL with truncation achieved the best performance obtaining a ROUGE -1 score of 55 and 86% agreement with expert evaluation. These findings demonstrate that domain adapted LLMs can provide a practical tool for rapid information synthesis and financial decision making.

Impact of Weather on Solar Panel Efficiency

Mustafa Hamid AL-Jumaili — 2025-10-18

Abstract— Photovoltaic systems are a popular form of renewable energy technology used to harness power in a sustainable manner. The effects of environmental factors such as rainfall on photovoltaic systems have been found to be quite pronounced through competing effects on irradiance attenuation and natural cleaning. This study aims to evaluate the effects of rainfall intensity on photovoltaic power output through a dynamic model of rainfall-soiling-power and experimental measurements. The study used a photovoltaic power system installed in Ramadi, Iraq. The experiment measured and monitored rainfall intensity, reference panel power, and natural panel power. The study used a mathematical model to simulate the effects of rainfall attenuation, soiling, and natural cleaning. The model simulated a dynamic model of dirt accumulation and predicted photovoltaic power output. The experiment found that light rain has a detrimental effect on photovoltaic power output through irradiance attenuation, but high rain intensity enhances power output through natural cleaning. The study found that high rain intensity, i.e., rain intensity above or equal to 15 mm, enhances power output by 9%. The model simulated power output with high accuracy and provided valuable insights on understanding photovoltaic power output behavior. The study found that rain plays a vital role in natural cleaning, thereby improving photovoltaic power output efficiency.

Hybrid Crime Scene Policing in the Digital Evidence Era: A Conceptual Framework for Artificial Intelligence and Immersive Training

Saleh MANSOUR — 2025-08-01

Hybrid crime scene policing in the digital evidence era increasingly involves the integration of physical and digital evidence, creating new operational, legal, and training challenges for law enforcement. This paper presents a conceptually framed, practice-informed analytical synthesis of selected literature and documented international use cases examining the role of artificial intelligence (AI) and immersive technologies in crime scene training and investigation. It proposes a tiered conceptual framework for AI and immersive training that integrates immersive simulation, AI-facilitated performance analysis, and hybrid physical–digital training, and discusses the associated legal, ethical, and operational considerations necessary for responsible implementation.

Phase Locking Values and Analytics for Finding Patterns from Rhythms of Hormones

Hillol Biswas — 2025-08-02

The body's hormones have exact timing patterns that function as codes for regular physiology. Sleep, metabolism, temperament, immunity, and reproduction are all influenced by the manner in which a hormone is produced, not just its quantity. The same hormone level can have quite different consequences when these time patterns are disturbed, which can result in issues like poor glucose control, infertility, or sleep disturbances. Internal conflict results from improper signal timing, whereas organs and cells function in unison when signals are timed correctly. Light, food, and activity are examples of external stimuli that have a significant impact on these patterns. Natural timing-restoring clinical treatments frequently perform better than dose-only alternatives. Essentially, the timing of hormone action is just as important to health as their intensity. However, data are not available for all these hormones at one place for a broader study based on analytical techniques for finding any overall relation. This paper describes the different hormones from available resources/data and using this based on a synthetic data generation of 50 number of hormones with temporal characteristics make analytics for finding a broader overview.