BUILDING A BEST-IN-CLASS AUTOMATED DE-IDENTIFICATION TOOL FOR ELECTRONIC HEALTH RECORDS THROUGH ENSEMBLE LEARNING

Building a best-in-class automated de-identification tool for electronic health records through ensemble learning

Summary: The presence of personally identifiable information (PII) in natural language portions of electronic health records (EHRs) constrains their broad reuse.Despite continuous improvements in automated detection of PII, residual identifiers require manual validation and correction.Here, we describe an automated de-identification system that emp

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Mucosa-like differentiation of head and neck cancer cells is inducible and drives the epigenetic loss of cell malignancy

Abstract Head and neck squamous cell carcinoma (HNSCC) is a highly malignant disease with high death rates that have remained substantially unaltered for decades.Therefore, new treatment approaches are urgently needed.Human papillomavirus-negative tumors harbor areas of terminally differentiated tissue that are characterized by cornification.Dissec

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Design Optimization of a Novel Networked Electromagnetic Soft Actuators System Based on Branch and Bound Algorithm

This paper presents a design optimization framework based on Branch and Bound Algorithm for novel networked electromagnetic soft actuators.The soft actuators work based on the operating principle of solenoids but are made of intrinsically soft materials.We confirmed that by scaling down the size of the soft actuators, their force to volume ratio in

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