Artificial intelligence (AI) use in diabetes care is increasingly being explored to personalise
care for people with diabetes and adapt treatments for complex presentations. However, the …

Background It is unknown whether large language models (LLMs) may facilitate time-and
resource-intensive text-related processes in evidence appraisal. Objectives To quantify the …

Despite their competitive performance on knowledge-intensive tasks, large language
models (LLMs) still have limitations in memorizing all world knowledge especially long tail …

Importance General-domain large language models may be able to perform risk stratification
and predict postoperative outcome measures using a description of the procedure and a …

In recent years, generative artificial intelligence (AI), particularly large language models
(LLMs) and their multimodal counterparts, Multi-Modal Large Language Models (MM-LLMs) …

Large language models (LLMs) are proving to be very useful in many fields, especially
chemistry and biology, because of their amazing capabilities. Biomolecular data is often …

The current gold standard for evaluating generated chest x-ray (CXR) reports is through
radiologist annotations. However, this process can be extremely time-consuming and costly …

Radiology report generation (RRG) is a challenging task, as it requires a thorough
understanding of medical images, integration of multiple temporal inputs, and accurate …

Electronic health records, biobanks, and wearable biosensors contain multiple high-
dimensional clinical data (HDCD) modalities (eg, ECG, Photoplethysmography (PPG), and …

In any ailment, the identification of the symptoms, detection, and diagnosis plays a pivotal
role in treatment and therapy. However, certain diseases share similar symptoms, lacking …