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. Novel Adversarial Machine Learning algorithms for structured data will be proposed. The algorithms will be further extended to graph-structured data. Applications of AML will also be investigated to
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. Novel Adversarial Machine Learning algorithms for structured data will be proposed. The algorithms will be further extended to graph-structured data. Applications of AML will also be investigated to
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datasets to train effectively. In practice, acquiring high-quality spectral data from wet-lab experiments is expensive and time-consuming. Furthermore, relying on a single spectral modality often
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datasets to train effectively. In practice, acquiring high-quality spectral data from wet-lab experiments is expensive and time-consuming. Furthermore, relying on a single spectral modality often
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behaviour. Natural language processing algorithms are utilized to examine vast amounts of textual data, identifying keywords, phrases, and sentiment that may indicate extremist views or intentions
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Primary supervisor Jesmin Nahar Research area Data Science and Artificial Intelligence Background Colorectal cancer is a major health challenge, and early detection and accurate risk assessment are
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Primary supervisor Jesmin Nahar Research area Data Science and Artificial Intelligence Background Colorectal cancer is a major health challenge, and early detection and accurate risk assessment are
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Primary supervisor Jesmin Nahar Co-supervisors Anyone from the Faculty who is interested. Research area Data Science and Artificial Intelligence Background Cardiovascular disease is a major global
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Primary supervisor Jesmin Nahar Co-supervisors Anyone from the Faculty who is interested. Research area Data Science and Artificial Intelligence Background Cardiovascular disease is a major global
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areas of computer science. ML’s versatility stems from the wealth of techniques it offers, making ML seem an excellent tool for any task that involves building a model from data. Nevertheless, ML