The "publish or perish" culture in academia has intensified trends in medical research, particularly around artificial intelligence (AI) and machine learning. This letter highlights how the pressure to publish positive findings during research trends, such as artificial intelligence in medicine, exacerbates the replication crisis. Issues like data leakage and lack of cross-institutional validation in AI models, particularly in clinical radiology, raise concerns about their reliability. The letter urges authors, reviewers, and editors to enforce rigorous standards to ensure reproducibility and safeguard the integrity of medical research.
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http://dx.doi.org/10.1007/s10439-024-03625-7 | DOI Listing |
Neurol Sci
January 2025
Epilepsy Center, Department of Neurology, West China Hospital of Sichuan University, Chengdu, China.
This study intents to detect graphical network features associated with seizure relapse following antiseizure medication (ASM) withdrawal. Twenty-four patients remaining seizure-free (SF-group) and 22 experiencing seizure relapse (SR-group) following ASM withdrawal as well as 46 matched healthy participants (Control) were included. Individualized morphological similarity network was constructed using T1-weighted images, and graphic metrics were compared between groups.
View Article and Find Full Text PDFInflamm Res
January 2025
Department of Nephrology, First Affiliated Hospital of Naval Medical University, Shanghai Changhai Hospital, Shanghai, China.
Background: Chronic inflammation is well recognized as a key factor related to renal function deterioration in patients with diabetic kidney disease (DKD). Neutrophil extracellular traps (NETs) play an important role in amplifying inflammation. With respect to NET-related genes, the aim of this study was to explore the mechanism of DKD progression and therefore identify potential intervention targets.
View Article and Find Full Text PDFJ Invest Dermatol
January 2025
Department of Dermatology, Stanford University, Stanford, California, USA; Department of Biomedical Data Science, Stanford University, Stanford, California, USA. Electronic address:
JACC Cardiovasc Imaging
January 2025
National Amyloidosis Centre, University College London, Royal Free Campus, Rowland Hill Street, London, United Kingdom.
Cardiac amyloidosis represents a unique disease process characterized by amyloid fibril deposition within the myocardial extracellular space. Advances in multimodality cardiac imaging enable accurate diagnosis and facilitate prompt initiation of disease-modifying therapies. Furthermore, rapid advances in multimodality imaging have enriched understanding of the underlying pathogenesis, enhanced prognostication, and resulted in the development of imaging-based markers that reflect the amyloid burden, which is of increasing importance when assessing the response to treatment.
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