Artificial Intelligence Medical Compendium

Evidence for the ongoing biodiversity crisis rests on assessment of a small fraction of described species, with major knowledge gaps for most organisms, including plants. Here, we highlight how digitised herbarium specimens can be used to accelerate ... read more 

BACKGROUND: The use of large language models (LLMs) such as ChatGPT and Gemini in clinical settings has surged, presenting potential benefits in reducing administrative workload and enhancing patient communication. However, concerns about the clinica... read more 

AIMS AND OBJECTIVES: To assess the knowledge and opinions of operating room nurses about artificial intelligence. BACKGROUND: Artificial intelligence technologies play a significant role in improving the quality of care and ensuring patient safety. O... read more 

PURPOSE: To investigate the association between best-corrected visual acuity (BCVA) and quantitative macular fluid volumes, compared to central subfield thickness (CST) in treatment-naïve and previously treated patients with active neovascular age-re... read more 

BACKGROUND AND OBJECTIVES: Parkinson disease (PD) patients with motor complications are often considered for deep brain stimulation (DBS) surgery. Predicting symptom improvement to separate DBS responders and nonresponders remains an unmet need. Curr... read more 

AIMS: To (1) analyse managers' experiences with handling patient safety incident reports in an incident reporting software, identifying key challenges; (2) analyse the incident report processes from the managers' perspective; (3) examine managers' pe... read more 

Recent cost reductions and technological advances have enabled the use of Immersive Virtual Reality (IVR) to assess performance tasks in high-fidelity 3D environments. This review outlines the current state of its application in neurocognitive assess... read more 

The planet hosts half a million plant species exhibiting a spectacular diversity of plant forms with genomes driving phenotypic variations. The genome information exists for less than 1% of species, limiting quantitative genomic studies in natural po... read more 

OBJECTIVE: Clinical adoption of T2 mapping is limited by poor reproducibility, lengthy examination times, and cumbersome image analysis. This study aimed to develop an accelerated deep learning (DL)-enhanced cartilage T2 mapping sequence (DL CartiGra... read more 

Coronary artery disease (CAD) remains a leading cause of morbidity and mortality worldwide, with incidence rates continuing to rise. Automated coronary artery medical image segmentation can ultimately improve CAD management by enabling more advanced ... read more