One-Versus-Others Attention: Scalable Multimodal Integration for Biomedical Data.

Multimodal models have become increasingly important as they surpass single-modality approaches on diverse tasks ranging from question-answering to disease diagnosis. Despite the importance of multimodal learning, existing efforts focus on vision-language applications, where the number of modalities rarely exceeds four (images, text, audio, video). However, data in healthcare domain, may include many more modalities like X-rays, PET scans, MRIs, genetic screening, genomic data, and clinical notes, creating a need for both efficient and accurate data integration.

How Do We Get the Public Into Public Health Research? Learnings and Key Recommendations From Initiating a Community Involvement Project Scheme.

Introduction: There are many recognised benefits of public involvement, including more relevant research. The COVID-19 pandemic highlighted the existing health inequalities and disparities in access to care and treatment for under-served groups, necessitating meaningful and sustainable approaches to engaging them in health research. However, there is limited guidance to suggest what groundwork and processes are necessary for initiating such projects.

[Development of competencies in the Medical Informatics Initiative (MII)-educational offers for a competent and secure handling of medical data].

In order to achieve the goals of the Medical Informatics Initiative (MII), staff with skills in the field of medical informatics and data science are required. Each consortium has established training activities. Further, cross-consortium activities have emerged.