A comprehensive evaluation benchmarks Large Language Models with traditional machine learning algorithms for automatic news classification is done on three standard news classification datasets: BBC News, 20 Newsgroups, and AG News. We implement traditional mo…
This doctoral dissertation, entitled "Application of Explainable Artificial Intelligence to Precision Oncology," explores the development and evaluation of interpretable machine learning models for drug response prediction in personalized cancer therapy. It hi…
ML models have shown remarkable performance in predictions in genomic cancer applications but experience the black-box problem. Where complicated processes of decision making remain non transparent to healthcare professionals and researchers. This absence of i…
Η παρούσα μελέτη διερευνά την απόδοση τόσο κλασικών όσο και ασαφών αλγορίθμων ταξινόμησης στην πρόβλεψη της αυθεντικότητας σημάτων pulsar, χρησιμοποιώντας ένα ευρέως αποδεκτό σύνολο χαρακτηριστικών που έχει προταθεί ως πρότυπη αναφορά για τις μελλοντικές έρευν…
This dissertation explores machine learning approaches for the automatic classification of neurological gait disorders and the detection of falls in older adults. Using EMG and wearable sensor data, the study evaluates multiple machine learning algorithms and…
The proliferation of user-generated content on online platforms like Reddit has created vast datasets that can be used to extract significant knowledge, such as author attribution through various analytical techniques. Author attribution is the task of identif…
Breast cancer is one of the most prevalent cancers globally and remains a leading cause of death among women. While mammography helps detect existing abnormalities, it offers limited insight into the future risk of developing cancer. This highlights the need f…
Inventory management and operation planning in retail sector involve accurate demand forecasting as a key element of the process. Linear models and tree-based models are typical examples of traditional forecasting models that may not work well in capturing com…
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…
Machine learning is no longer limited to low-risk tasks, but it is also being used in critical decision-making systems. Consequently, machine learning has a direct effect on individuals' lives in domains such as recidivism prediction (COMPAS) and loan approval…
The adoption of network virtualization and cloud computing has introduced new complexities and attack vectors, which demands more intelligent and scalable security solutions. In such cases, traditional Intrusion Detection Systems (IDS) often have struggle to p…
With the increasing growth of Internet of Things (IoT) devices, network infrastructures have become more vulnerable to cyber-attacks. Traditional network security measures often fall short in detecting sophisticated intrusion patterns in real-time, highlightin…
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.
