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Bo Lu

Researcher at Ohio State University

Publications -  390
Citations -  24905

Bo Lu is an academic researcher from Ohio State University. The author has contributed to research in topics: Cancer & Lung cancer. The author has an hindex of 58, co-authored 353 publications receiving 21823 citations. Previous affiliations of Bo Lu include Wuhan University of Technology & Wuhan University.

Papers
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Journal ArticleDOI

Incidence of adverse events in an integrated US healthcare system: a retrospective observational study of 82,784 surgical hospitalizations

TL;DR: Detecting variations in AEs among surgical categories can be useful for surgeons and for hospital quality assurance personnel, and determining AE severity and age distributions within surgical categories will enable officials to better identify specific patient safety needs and develop appropriately targeted interventions for improvement.
Journal ArticleDOI

Effectiveness of varenicline for smoking cessation: a 1-year follow-up study.

TL;DR: It is found that the combination of counseling and VAR is effective at promoting abstinence at 1 year even when compliance with the medication is not 100%.
Journal ArticleDOI

Comparison between proton boron fusion therapy (PBFT) and boron neutron capture therapy (BNCT): a monte carlo study

TL;DR: The utility of PBFT was verified using the simulation and it has a potential for application in radiotherapy, and the dramatic effectiveness of the alpha particle was validated, especially in PBFT.
Journal ArticleDOI

Nonoccupational and Occupational Injuries to US Workers With Disabilities

TL;DR: Disability status was strongly associated with risk of nonoccupational and occupational injuries among US workers and federal agencies with an interest in the employment of workers with disability and their safety in the workplace should take a lead in further assessing injury risk.
Book ChapterDOI

Autophagy in lung cancer.

TL;DR: This text reviews the most up to date protocols and techniques for the study of autophagic cell death in lung cancer models and suggests that these techniques should be used as a framework for study within their experimental models.