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Menampilkan 1–2 dari 2 artikel
Transformer-Augmented Deep Learning Ensemble for Multi-Modal Neuroimaging-Based Diagnosis of Amyotrophic Lateral Sclerosis
Asuai, Clive
; Andrew, Mayor
; Arinomor, Ayigbe Prince
; Ogheneochuko, Daniel Ezekiel
; Joseph-Brown, Aghoghovia Agajere
; Merit, Ighere
; Collins, Atumah
Journal of Computing Theories and Applications
Vol 3
, No 2
(2025)
Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disorder that presents significant diagnostic challenges due to its heterogeneous clinical manifestations and symptom overlap with other neurological conditions. Early and accurate diagnosis is critical for initiating timely interventions and improving patient outcomes. Traditional diagnostic approaches rely heavily on clinical expertise and manual interpretation of neuroimaging data, such as structural MRI, Diffusion Tensor...
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UNMASKING FRAUDSTERS: Ensemble Features Selection to Enhance Random Forest Fraud Detection
Akazue, Maureen Ifeanyi
; Debekeme, Irene Alamarefa
; Edje, Abel Efe
; Asuai, Clive
; Osame, Ufuoma John
Journal of Computing Theories and Applications
Vol 1
, No 2
(2023)
Fraud detection is used in various industries, including banking institutes, finance, insurance, government agencies, etc. Recent increases in the number of fraud attempts make fraud detection crucial for safeguarding financial information that is confidential or personal. Many types of fraud problems exist, including card-not-present fraud, fake Marchant, counterfeit checks, stolen credit cards, and others. An ensemble feature selection technique based on Recursive feature elimination (RFE), In...
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