International Conference on Agents and Artificial Intelligence Authors Andrei Olar Abstract Can we control the writing style of large language models (LLMs) by specifying desired linguistic features? We address this question by investigating the impact of handcrafted linguistic feature (HLF) instructions on LLM-generated text. Our experiment evaluates various state-of-the-art LLMs using prompts incorporating HLF…
Logic Journal of the IGPL Authors M. Suciu, R. Lung Abstract Classification and feature selection are two of the most intertwined problems in machine learning. Decision trees (DTs) are straightforward models that address these problems offering also the advantage of explainability. However, solutions that are based on them are either tailored for the problem…
Comput. Biol. Medicine Authors Cristiana Moroz-Dubenco, Adél Bajcsi, A. Andreica, C. Chira Abstract According to the World Health Organization, breast cancer becomes fatal only if it spreads throughout the body. Therefore, regular screening is essential. Whilst mammography is the most frequently used technique, its interpretation can be challenging and time-consuming. For this reason, computer-aided…
International Conference on Agents and Artificial Intelligence Authors Adél Bajcsi, A. Andreica, C. Chira Abstract Proper treatment of breast cancer is essential to increase survival rates. Mammography is a widely used, non-invasive screening method for breast cancer. A challenging task in mammogram analysis is to distinguish between tumors. In the current study, we address…
International Conference on Web Information Systems and Technologies Authors Thomas Kaisser, C. Coste Abstract Over the last years, the Internet has monopolized most businesses and industries. These outstanding advancements lead to the dangerous development of specialized threats employed to outsmart everyday users, collect personal data and financial benefits. One of the most relevant attacks…
International Conference on Machine Learning, Optimization, and Data Science Authors R. Lung, M. Suciu Abstract The feature selection problem has become a key undertaking within machine learning. For classification problems, it is known to reduce the computational complexity of parameter estimation, but it also adds an important contribution to the explainability aspects of the…
Hybrid Artificial Intelligence Systems Authors Cristiana Moroz-Dubenco, L. Dioşan, A. Andreica Abstract In the past five years, 7.8 million women were diagnosed with breast cancer. Breast cancer is curable if it is discovered in early stages. Therefore, mammography screening is essential. But, since interpretation can prove difficult, various automated interpretation systems have been proposed…
International Conference on Knowledge-Based Intelligent Information & Engineering Systems Authors Cristiana Moroz-Dubenco, A. Andreica Abstract Between 2015 and 2020, 7.8 million women were diagnosed with breast cancer. If the cancer is discovered early, it can be completely cured. Computer-aided detection and diagnosis systems are a helpful tool. We propose such a system: after pre-processing…
International Conference on Evaluation of Novel Approaches to Software Engineering Authors Virginia Niculescu, H. Greblă, Adrian Sterca, Darius Bufnea Abstract On account of the extreme expansion of the scientific research paper databases, the usage of searching and recommender systems in this area increased, as they can help researchers find appropriate papers by searching in…
Studia Universitatis Babeș-Bolyai Informatica Authors Adél Bajcsi, C. Chira, A. Andreica Abstract The efficient analysis of digital mammograms has an important role in the early detection of breast cancer and can lead to a higher percentage of recovery. This paper presents an extended computer-aided diagnosis system for the classification of mammograms into three classes…