Accurate building energy forecasting is essential for efficient energy management and operational optimization in intelligent building systems. This study presents an explainable machine learning framework for high-resolution healthcare building energy demand forecasting. Random Forest, XGBoost, Long Short-Term Memory...
Nurudeen Gbadegesin· British journal of computer,...· 0 citations
Aims: To synthesise and critically appraise evidence on artificial intelligence (AI) and multimodal data approaches for diagnosis, prognosis, and treatment decision support in diffuse large B-cell lymphoma (DLBCL) and acute myeloid leukaemia (AML), and to compare how disease biology shapes model design and clinical rea...
Emmanuel Niiboye Odai, M. S. Ibrahim, Mable Nalugya et al.· Journal of Advances in Medic...· 0 citations
This critical narrative review evaluates the evidence linking real-world evidence and machine learning to predictive oncology and clinical decision support and found the evidence is strongest for scalable extraction of treatment response, progression, performance status and mortality-related phenotypes.
Emmanuel Niiboye Odai, E. Twene, Nurudeen Gbadegesin et al.· Archives of Current Research...· 0 citations
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