AIMC Topic: Reproducibility of Results

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Artificial intelligence-enhanced interpretation of kidney transplant biopsy: focus on rejection.

Current opinion in organ transplantation
PURPOSE OF REVIEW: The objective of this review is to provide an update on the application of artificial intelligence (AI) for the histological interpretation of kidney transplant biopsies.

Chat-GPT in triage: Still far from surpassing human expertise - An observational study.

The American journal of emergency medicine
BACKGROUND: Triage is essential in emergency departments (EDs) to prioritize patient care based on clinical urgency. Recent investigations have explored the role of large language models (LLMs) in triage, but their effectiveness compared to human tri...

Deep learning-enhanced zero echo time MRI for glenohumeral assessment in shoulder instability: a comparative study with CT.

Skeletal radiology
PURPOSE: To evaluate image quality and lesion conspicuity of zero echo time (ZTE) MRI reconstructed with deep learning (DL)-based algorithm versus conventional reconstruction and to assess DL ZTE performance against CT for bone loss measurements in s...

Assessing and improving reliability of neighbor embedding methods: a map-continuity perspective.

Nature communications
Visualizing high-dimensional data is essential for understanding biomedical data and deep learning models. Neighbor embedding methods, such as t-SNE and UMAP, are widely used but can introduce misleading visual artifacts. We find that the manifold le...

Bayesian deep-learning structured illumination microscopy enables reliable super-resolution imaging with uncertainty quantification.

Nature communications
The objective of optical super-resolution imaging is to acquire reliable sub-diffraction information on bioprocesses to facilitate scientific discovery. Structured illumination microscopy (SIM) is acknowledged as the optimal modality for live-cell su...

Chatbots' Role in Generating Single Best Answer Questions for Undergraduate Medical Student Assessment: Comparative Analysis.

JMIR medical education
BACKGROUND: Programmatic assessment supports flexible learning and individual progression but challenges educators to develop frequent assessments reflecting different competencies. The continuous creation of large volumes of assessment items, in a c...

Application of the Bidirectional Encoder Representations from Transformers Model for Predicting the Abbreviated Injury Scale in Patients with Trauma: Algorithm Development and Validation Study.

JMIR formative research
BACKGROUND: Deaths related to physical trauma impose a heavy burden on society, and the Abbreviated Injury Scale (AIS) is an important tool for injury research. AIS covers injuries to various parts of the human body and scores them based on the sever...

Machine learning for predicting retention times of chiral analytes chromatographically separated by CMPA technique.

Journal of chromatography. A
Chiral mobile phase additive (CMPA) technique is an attractive method for chromatographic enantioseparation of chiral analytes. However, establishing chromatographic separation and analysis methods for given chiral analytes often requires extensive t...