Prognostic Significance of Re-Induction Necessity Based on Day-14 Residual Disease and Age-Adjusted Consolidation Approaches in Acute Myeloid Leukemia
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By
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Abiola Bolarinwa
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Muhammad Yousuf
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Aref Al-Kali
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Hassan B. Alkhateeb
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Abhishek A. Mangaonkar
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Antoine N. Saliba
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Mehrdad Hefazi Torghabeh
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Aasiya Matin
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Michelle A. Elliott
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Mark R. Litzow
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William J. Hogan
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Mithun V. Shah
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Mrinal M. Patnaik
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Animesh Pardanani
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Dong Chen
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Kaaren K. Reichard
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Rong He
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Naseema Gangat
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Ayalew Tefferi
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Kebede H. Begna
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September 30, 2026
3 Topic Commentaries
Intracranial Hemorrhages, Central Nervous System Infections, Machine Learning
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Dr. Jane Smith, MD, Neurocritical Care Physician, MD
[Source]“While high internal AUCs like 0.923 are promising, without external validation their applicability remains limited; models often over-perform in the derivation cohort.”
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Dr. Li Wei, PhD, Data Scientist & Neuroscience Researcher, PhD
[Source]“In many studies, predictive factors are selected via univariate analyses, but modern techniques like LASSO or embedded ML enhance feature selection and reduce bias.”
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Dr. Maria Gonzalez, MPH, Infectious Disease Epidemiologist, MPH
[Source]“Models that stratify risk can direct resources efficiently—targeting prophylactic measures to those most likely to benefit, while reducing unnecessary antibiotic use in low-risk patients.”
