The recent publication, in prestigious scientific journals, of two major studies that were subsequently shown to contain fabricated data may compel reviewers and editors to adopt a more rigorous policy in accepting articles for publication. The current manner of peer reviewing research articles provides no assurance that the proffered work is not the result of fraud. The present guidelines for contributors in large team investigations may need to be updated to avoid giving credit to co-authors who may have made little, if any, contribution to the work.
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| http://dx.doi.org/10.5694/j.1326-5377.2006.tb00420.x | DOI Listing |
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TransRAUNet: A Deep Neural Network with Reverse Attention Module Using HU Windowing Augmentation for Robust Liver Vessel Segmentation in Full Resolution of CT Images.
Diagnostics (Basel)
January 2025
Department of Medical Device and Healthcare, Dongguk University, Seoul 04620, Republic of Korea.
Liver cancer has a high mortality rate worldwide, and clinicians segment liver vessels in CT images before surgical procedures. However, liver vessels have a complex structure, and the segmentation process is conducted manually, so it is time-consuming and labor-intensive. Consequently, it would be extremely useful to develop a deep learning-based automatic liver vessel segmentation method.
View Article and Find Full Text PDFImportance and fitness of family medicine milestone project from America to Taiwan.
BMC Med Educ
January 2025
Department of Family Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan City, Taiwan.
Background: The six core competencies of ACGME - patient care (PC), medical knowledge (MK), systems-based practice (SBP), practice-based learning and improvement (PBLI), professionalism (PROF), and interpersonal and communication skills (ICS) - represent domains in which physicians must ultimately demonstrate competence. Although the ACGME's six core competencies have been applied in Taiwan with the milestone project, the application of the six core competences in the Family Medicine milestones for residency training have not yet been established.
Methods: We recruited 61 family medicine physicians from 25 hospitals from four major geographic areas for a Delphi round one survey and 72 physicians from 27 hospitals for a Delphi round two survey.
Deficits in facial emotion recognition and cognitive function among baby boomers.
Acta Psychol (Amst)
January 2025
Department of Biomedical Laboratory Science, Honam University, Gwangju 62399, Republic of Korea. Electronic address:
Facial emotion recognition (FER), a key component of social cognition, plays a critical role in social interactions. In the aging process, FER among older adults holds significant potential as a tool for diagnosing cognitive function or enhancing interpersonal relationships. However, research in this area remains limited.
View Article and Find Full Text PDFArtificial intelligence-enhanced comprehensive assessment of the aortic valve stenosis continuum in echocardiography.
EBioMedicine
January 2025
CONNECT-AI Research Center, Yonsei University College of Medicine, Seoul, Republic of Korea; Ontact Health Inc., Seoul, Republic of Korea; Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Yonsei University Health System, Seoul, Republic of Korea.
Background: Transthoracic echocardiography (TTE) is the primary modality for diagnosing aortic stenosis (AS), yet it requires skilled operators and can be resource-intensive. We developed and validated an artificial intelligence (AI)-based system for evaluating AS that is effective in both resource-limited and advanced settings.
Methods: We created a dual-pathway AI system for AS evaluation using a nationwide echocardiographic dataset (developmental dataset, n = 8427): 1) a deep learning (DL)-based AS continuum assessment algorithm using limited 2D TTE videos, and 2) automating conventional AS evaluation.
Automated extracellular volume fraction measurement for diagnosis and prognostication in patients with light-chain cardiac amyloidosis.
PLoS One
January 2025
Phantomics, Inc., Seoul, South Korea.
Aims: T1 mapping on cardiac magnetic resonance (CMR) imaging is useful for diagnosis and prognostication in patients with light-chain cardiac amyloidosis (AL-CA). We conducted this study to evaluate the performance of T1 mapping parameters, derived from artificial intelligence (AI)-automated segmentation, for detection of cardiac amyloidosis (CA) in patients with left ventricular hypertrophy (LVH) and their prognostic values in patients with AL-CA.
Methods And Results: A total of 300 consecutive patients who underwent CMR for differential diagnosis of LVH were analyzed.
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