Case 5-2018: A 63-Year-Old Man with Confusion after Stem-Cell Transplantation

Neurological Diagnosis: Artificial Intelligence Compared With Diagnostic Generator

OBJECTIVE

Artificial intelligence has recently become available for widespread use in medicine, including the interpretation of digitized information, big data for tracking disease trends and patterns, and clinical diagnosis. Comparative studies and expert opinion support the validity of imaging and data analysis, yet similar validation is lacking in clinical diagnosis. Artificial intelligence programs are here compared with a diagnostic generator program in clinical neurology.

METHODS

Using 4 nonrandomly selected case records from New England Journal of Medicine clinicopathologic conferences from 2017 to 2022, 2 artificial intelligence programs (ChatGPT-4 and GLASS AI) were compared with a neurological diagnostic generator program (NeurologicDx.com) for diagnostic capability and accuracy and source authentication.

RESULTS

Compared with NeurologicDx.com, the 2 AI programs showed results varying with order of key term entry and with repeat querying. The diagnostic generator yielded more differential diagnostic entities, with correct diagnoses in 4 of 4 test cases versus 0 of 4 for ChatGPT-4 and 1 of 4 for GLASS AI, respectively, and with authentication of diagnostic entities compared with the AI programs.

CONCLUSIONS

The diagnostic generator NeurologicDx yielded a more robust and reproducible differential diagnostic list with higher diagnostic accuracy and associated authentication compared with artificial intelligence programs.

Towards a Comprehensive Understanding of UA-ADRCs (Uncultured, Autologous, Fresh, Unmodified, Adipose Derived Regenerative Cells, Isolated at Point of Care) in Regenerative Medicine

It has become practically impossible to survey the literature on cells derived from adipose tissue for regenerative medicine. The aim of this paper is to provide a comprehensive and translational understanding of the potential of UA-ADRCs (uncultured, unmodified, fresh, autologous adipose derived regenerative cells isolated at the point of care) and its application in regenerative medicine. We provide profound basic and clinical evidence demonstrating that tissue regeneration with UA-ADRCs is safe and effective. ADRCs are neither 'fat stem cells' nor could they exclusively be isolated from adipose tissue. ADRCs contain the same adult stem cells ubiquitously present in the walls of blood vessels that are able to differentiate into cells of all three germ layers. Of note, the specific isolation procedure used has a significant impact on the number and viability of cells and hence on safety and efficacy of UA-ADRCs. Furthermore, there is no need to specifically isolate and separate stem cells from the initial mixture of progenitor and stem cells found in ADRCs. Most importantly, UA-ADRCs have the physiological capacity to adequately regenerate tissue without need for more than minimally manipulating, stimulating and/or (genetically) reprogramming the cells for a broad range of clinical applications. Tissue regeneration with UA-ADRCs fulfills the criteria of homologous use as defined by the regulatory authorities.

The Curious Case of "Case Report" of Infections Caused by Human and Animal Fungal Pathogens: An Educational Tool, an Online Archive, or a Format in Need of Retooling

Case reports describe the unusual occurrence and complications of diseases, diagnostic challenges, and notable therapeutic successes. Some journals have discontinued the case reports, while new case report journals have appeared in recent years. During the eightieth anniversary of Mycopathologia, it is fitting to examine the relevance of the case report since the journal continues to traverse the boundaries of basic and clinical sciences. A random sample of recent case reports and other articles were selected from Mycopathologia. Springer Nature individual article download statistics, and Google Scholar and Scopus citations numbers were compared to assess the reader access and bibliometric impact of case reports. Our analysis indicated that the case report format continues to be a vital element of publication in a cross-disciplinary journal such as Mycopathologia. Medical and veterinary case reports covering fungal pathogens are widely read as evident from their download numbers. The download numbers have a positive correlation with the completeness of the report, the topics and geographic origin of reports have a neutral influence, and the recency leads to lower downloads. There is no discernible trend between the download numbers and the citations of case reports as measured by Google Scholar and Scopus. A specially designed checklist for Mycopathologia case reports and new format MycopathologiaIMAGES are being introduced to improve the quality and relevance of case reports further.