AIMC Topic: Knowledge

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Performance of ChatGPT, Bard, Claude, and Bing on the Peruvian National Licensing Medical Examination: a cross-sectional study.

Journal of educational evaluation for health professions
PURPOSE: We aimed to describe the performance and evaluate the educational value of justifications provided by artificial intelligence chatbots, including GPT-3.5, GPT-4, Bard, Claude, and Bing, on the Peruvian National Medical Licensing Examination ...

CLOOME: contrastive learning unlocks bioimaging databases for queries with chemical structures.

Nature communications
The field of bioimage analysis is currently impacted by a profound transformation, driven by the advancements in imaging technologies and artificial intelligence. The emergence of multi-modal AI systems could allow extracting and utilizing knowledge ...

Improving the classification of veterinary thoracic radiographs through inter-species and inter-pathology self-supervised pre-training of deep learning models.

Scientific reports
The analysis of veterinary radiographic imaging data is an essential step in the diagnosis of many thoracic lesions. Given the limited time that physicians can devote to a single patient, it would be valuable to implement an automated system to help ...

A benchmarking protocol for SAR colorization: From regression to deep learning approaches.

Neural networks : the official journal of the International Neural Network Society
Synthetic aperture radar (SAR) images are widely used in remote sensing. Interpreting SAR images can be challenging due to their intrinsic speckle noise and grayscale nature. To address this issue, SAR colorization has emerged as a research direction...

Examining ChatGPT Performance on USMLE Sample Items and Implications for Assessment.

Academic medicine : journal of the Association of American Medical Colleges
PURPOSE: In late 2022 and early 2023, reports that ChatGPT could pass the United States Medical Licensing Examination (USMLE) generated considerable excitement, and media response suggested ChatGPT has credible medical knowledge. This report analyzes...

Knowledge graph and CBR-based approach for automated analysis of bridge operational accidents: Case representation and retrieval.

PloS one
Bridge operational accident analysis is a critical process in bridge operational risk management. It provides valuable knowledge support for responding to newly occurring accidents. However, there are three issues: (1) research specifically focused o...

Mapping the flow of knowledge as guidance for ethics implementation in medical AI: A qualitative study.

PloS one
In response to the COVID-19 crisis, Artificial Intelligence (AI) has been applied to a range of applications in healthcare and public health such as case identification or monitoring of the population. The urgency of the situation should not be to th...

Boosting fine-tuning via Conditional Online Knowledge Transfer.

Neural networks : the official journal of the International Neural Network Society
Fine-tuning is an effective technique to enhance network performance in scenarios with limited labeled data. To achieve this, recent methods exploit the knowledge mined in the source model (e.g., feature maps) to construct an extra regularization sig...

Entity Summarization via Exploiting Description Complementarity and Salience.

IEEE transactions on neural networks and learning systems
Entity summarization is a novel and efficient way to understand real-world facts and solve the increasing information overload problem in large-scale knowledge graphs (KG). Existing studies mainly rely on ranking independent entity descriptions as a ...

Exploring the role of an artificial intelligence chatbot on appendicitis management: an experimental study on ChatGPT.

ANZ journal of surgery
BACKGROUND: Appendicitis is a common surgical condition that requires urgent medical attention. Recent advancements in artificial intelligence and large language processing, such as ChatGPT, have demonstrated potential in supporting healthcare manage...