James H. Lubowitz

Jan 14, 2025 | arthroscopyjournal.org | James H. Lubowitz |Elizabeth Matzkin |Michael J. Rossi

As editors, we prefer to focus attention on exciting developments in our journals.1-5 From print to Podcasts, such developments are not unique to our publications and reflect publishing industry trends. When it comes to biomedical research publication, there is much for which to feel positive. However, when concerning exceptions to positive progress are recognized, one would be remiss to ignore such concerns, particularly if opportunities for improvement can be identified.

Jun 21, 2024 | arthroscopyjournal.org | Michael J. Rossi |James H. Lubowitz |Mark P. Cote |Elizabeth Matzkin

AbstractDisaggregation, in the medical literature, means separation into demographic groups. This results in an opportunity to discover differences in outcomes by group, which could improve future treatments and provide outcome data, by group, that could be included in future systematic reviews. In research, the term disaggregation is most often used in reference to addressing inequities.

Jun 21, 2024 | arthroscopyjournal.org | Michael J. Rossi |James H. Lubowitz |Mark P. Cote |Elizabeth Matzkin

AbstractDisaggregation, in the medical literature, means separation into demographic groups. This results in an opportunity to discover differences in outcomes by group, which could improve future treatments and provide outcome data, by group, that could be included in future systematic reviews. In research, the term disaggregation is most often used in reference to addressing inequities.

Jan 11, 2024 | arthroscopyjournal.org | Mark P. Cote |James H. Lubowitz

Abstract Essential elements required for proper use of artificial intelligence machine learning tools in biomedical research and scientific publications include (1) explanation justifying why a machine learning approach contributes to the purpose of the study; (2) description of the adequacy of the data (input) to produce the desired results (output); (3) details of the algorithmic (i.e., computational) approach including methods for organizing the data (preprocessing); the machine learning...

Jan 11, 2024 | arthroscopyjournal.org | Mark Siegel |Michael J. Rossi |James H. Lubowitz

AbstractBiomedical information doubles almost every 2 months, and this very rate is expected to double by 2025. The result is information overload for clinicians and researchers. Today, artificial intelligence (AI) and machine learning (ML) research contribute to the deluge of information. In addition, AI large language models, although capable of automating scientific writing, are flawed.