AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Information Dissemination

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The SINFONIA project repository for AI-based algorithms and health data.

Frontiers in public health
The SINFONIA project's main objective is to develop novel methodologies and tools that will provide a comprehensive risk appraisal for detrimental effects of radiation exposure on patients, workers, caretakers, and comforters, the public, and the env...

Facilitating the use of routine data to evaluate artificial intelligence solutions: lessons from the NIHR/RCR data curation workshop.

Clinical radiology
Radiology currently stands at the forefront of artificial intelligence (AI) development and deployment over many other medical subspecialities within the scope of both research and clinical practice. Given this current leadership position, it is impe...

From code sharing to sharing of implementations: Advancing reproducible AI development for medical imaging through federated testing.

Journal of medical imaging and radiation sciences
BACKGROUND: The reproducibility crisis in AI research remains a significant concern. While code sharing has been acknowledged as a step toward addressing this issue, our focus extends beyond this paradigm. In this work, we explore "federated testing"...

Evaluating the accuracy and reliability of AI chatbots in disseminating the content of current resuscitation guidelines: a comparative analysis between the ERC 2021 guidelines and both ChatGPTs 3.5 and 4.

Scandinavian journal of trauma, resuscitation and emergency medicine
AIM OF THE STUDY: Artificial intelligence (AI) chatbots are established as tools for answering medical questions worldwide. Healthcare trainees are increasingly using this cutting-edge technology, although its reliability and accuracy in the context ...

Artificial intelligence and health-related data: The patient's best interest and data ownership dilemma.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
The rapid advancement of artificial intelligence (AI) in healthcare has the potential to revolutionize the global healthcare sector and medicine in general. However, integrating AI technologies in healthcare requires access to large amounts of person...

Advancing healthcare practice and education via data sharing: demonstrating the utility of open data by training an artificial intelligence model to assess cardiopulmonary resuscitation skills.

Advances in health sciences education : theory and practice
Health professional education stands to gain substantially from collective efforts toward building video databases of skill performances in both real and simulated settings. An accessible resource of videos that demonstrate an array of performances -...

An international study presenting a federated learning AI platform for pediatric brain tumors.

Nature communications
While multiple factors impact disease, artificial intelligence (AI) studies in medicine often use small, non-diverse patient cohorts due to data sharing and privacy issues. Federated learning (FL) has emerged as a solution, enabling training across h...

Privacy-preserving federated data access and federated learning: Improved data sharing and AI model development in transfusion medicine.

Transfusion
BACKGROUND: Health data comprise data from different aspects of healthcare including administrative, digital health, and research-oriented data. Together, health data contribute to and inform healthcare operations, patient care, and research. Integra...

Empowering Data Sharing in Neuroscience: A Deep Learning Deidentification Method for Pediatric Brain MRIs.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Privacy concerns, such as identifiable facial features within brain scans, have hindered the availability of pediatric neuroimaging data sets for research. Consequently, pediatric neuroscience research lags adult counterparts,...