This thesis examines the cybersecurity and privacy implications of Explainable Artificial Intelligence (XAI) methods in selected Machine Learning (ML) models. The study focuses on whether post-hoc explainability methods can expose sensitive information from he…
This dissertation investigates how modern machine learning (ML) methods, with a particular focus on multi-task learning (MTL) frameworks, can enhance forecasts in financial and macroeconomic contexts. Chapter 1 outlines the limitations of traditional econometr…
Predictive maintenance was recently introduced as a paradigm shift in the field of smart manufacturing, and it allows organizations to predict equipment failures and streamline maintenance planning based on the data-driven insights. The present work addresses…
The increasing adoption of machine learning (ML) and artificial intelligence (AI) in critical decision-making has intensified demands for explainability and transparency, particularly in high-risk domains such as finance. This dissertation investigates how exp…
This thesis explores the challenges presented by label noise in machine learning (ML) for health. Label noise is unavoidable in real-world data; it can arise from variability in measurement, human annotation errors, and aleatoric uncertainty in the ground trut…
Recent ML advances have shown significant promise in assisting clinical decision-making in healthcare. In particular, the integration of ML predictive models into clinical settings has the potential to transform patient care through more personalized, timely,…
Since cardiovascular diseases (CVDs) continue to be the primary cause of morbidity and death worldwide, better patient outcomes depend on early and precise diagnosis. Although they are essential for clinical decision-making, traditional cardiovascular imaging…
Medical imaging technologies, such as magnetic resonance imaging (MRI) and computed tomography (CT), are invaluable tools in modern medicine - allowing for safe, non-invasive diagnosis and treatment planning. However, leveraging these imaging techniques for sc…
With climate change increasingly impacting communities and around the globe, understanding the Earth system has never been more vital. The many petabytes of data that are generated from remote sensing efforts such as satellite observations and ground-based mea…
This study aims to apply Natural Language Processing (NLP) and develop Machine Learning algorithms for detecting hate speech in social media. The “Hate Speech and Offensive Language dataset” is used, which comprises 24,783 manually annotated English tweets lab…
The integration of Artificial Intelligence (AI) into the domain of medical diagnostics has ushered in a new era of precision, speed, and reliability, particularly in the analysis of medical imaging. Among the most promising applications is the use of Machine L…
This thesis evaluates an artificial intelligence (AI) model's ability to support U.S. Marine Corps promotion boards, investigating how data drift and feedback loops impact its performance and reliability over time. Using the DataRobot automated machine learnin…
أنا مساعد المستودع. اسألني عن الرسائل والأطاريح حسب الموضوع أو الجامعة أو الدولة أو السنة أو الدرجة، أو اطلب أعداداً وإحصاءات.
يجيب من قاعدة بيانات المستودع فقط، ولا يخترع سجلات أو أرقاماً. لا يُحفظ ما تكتبه على الخادم.
قد يخطئ المساعد أحياناً، فراجع المصادر المرفقة.
