ALL diagnosis: can efficiency and transparency coexist? An explainble deep learning approach

Abstract Acute Lymphoblastic Leukemia (ALL) is a life-threatening malignancy characterized by its aggressive progression and detrimental effects on the hematopoietic system. Early and accurate diagnosis is paramount to optimizing therapeutic interventions and improving clinical outcomes. This study...

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Hlavní autoři:	Dost Muhammad, Muhammad Salman, Ayse Keles, Malika Bendechache
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Nature Portfolio 2025-04-01
Edice:	Scientific Reports
Témata:	Explainable artificial intelligence XAI for medical diagnosis EXplainble medical imaging ALL detection Decision support system Responsible AI
On-line přístup:	https://doi.org/10.1038/s41598-025-97297-5
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!