AI Medical Compendium Topic

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Medical Informatics

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Split Learning for Distributed Collaborative Training of Deep Learning Models in Health Informatics.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Deep learning continues to rapidly evolve and is now demonstrating remarkable potential for numerous medical prediction tasks. However, realizing deep learning models that generalize across healthcare organizations is challenging. This is due, in par...

A non-linear SVR-based cascade model for improving prediction accuracy of biomedical data analysis.

Mathematical biosciences and engineering : MBE
Biomedical data analysis is essential in current diagnosis, treatment, and patient condition monitoring. The large volumes of data that characterize this area require simple but accurate and fast methods of intellectual analysis to improve the level ...

Machine and Deep Learning Dominate Recent Innovations in Sensors, Signals and Imaging Informatics.

Yearbook of medical informatics
OBJECTIVES: This review presents research papers highlighting notable developments and trends in sensors, signals, and imaging informatics (SSII) in 2022.

Clinical Research Informatics: Contributions from 2022.

Yearbook of medical informatics
OBJECTIVES: To summarize key contributions to current research in the field of Clinical Research Informatics (CRI) and to select best papers published in 2022.

Leveraging Data and Technology to Enhance Interdisciplinary Collaboration and Health Outcomes.

Yearbook of medical informatics
OBJECTIVE: To give an overview of recent research and propose a selection of best papers published in 2022 in Informatics for One Health.

Machine learning for administrative health records: A systematic review of techniques and applications.

Artificial intelligence in medicine
Machine learning provides many powerful and effective techniques for analysing heterogeneous electronic health records (EHR). Administrative Health Records (AHR) are a subset of EHR collected for administrative purposes, and the use of machine learni...

Discriminative fusion of moments-aligned latent representation of multimodality medical data.

Physics in medicine and biology
Fusion of multimodal medical data provides multifaceted, disease-relevant information for diagnosis or prognosis prediction modeling. Traditional fusion strategies such as feature concatenation often fail to learn hidden complementary and discriminat...

Large AI Models in Health Informatics: Applications, Challenges, and the Future.

IEEE journal of biomedical and health informatics
Large AI models, or foundation models, are models recently emerging with massive scales both parameter-wise and data-wise, the magnitudes of which can reach beyond billions. Once pretrained, large AI models demonstrate impressive performance in vario...

A comparative patient-level prediction study in OMOP CDM: applicative potential and insights from synthetic data.

Scientific reports
The emergence of collaborations, which standardize and combine multiple clinical databases across different regions, provide a wealthy source of data, which is fundamental for clinical prediction models, such as patient-level predictions. With the ai...

BactInt: A domain driven transfer learning approach for extracting inter-bacterial associations from biomedical text.

Computational biology and chemistry
BACKGROUND: The healthy as well as dysbiotic state of an ecosystem like human body is known to be influenced not only by the presence of the bacterial groups in it, but also with respect to the associations within themselves. Evidence reported in bio...