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Personalized Breast Cancer Screening: Moving Beyond Age-Based Algorithms
Breast cancer screening has traditionally been organized around two principal variables: when mammography should begin and how frequently it should be performed.
Intracranial Hemorrhages, Central Nervous System Infections, Machine Learning
Dr. Jane Smith, MD, Neurocritical Care Physician, MD
Assistant Professor of Neurology
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University Hospital of Critical Care Medicine
“While high internal AUCs like 0.923 are promising, without external validation their applicability remains limited; models often over-perform in the derivation cohort.”
Dr. Li Wei, PhD, Data Scientist & Neuroscience Researcher, PhD
Senior Research Fellow
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Institute for Brain Health Research
“In many studies, predictive factors are selected via univariate analyses, but modern techniques like LASSO or embedded ML enhance feature selection and reduce bias.”
Dr. Maria Gonzalez, MPH, Infectious Disease Epidemiologist, MPH
Public Health Policy Advisor
•
National Stroke & Infection Control Coalition
“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.”