The study of autonomous agents powered by large language models (LLMs) has shown great promise in enhancing human productivity. These agents are designed to assist in various tasks such as coding, data analysis, and web navigation. They allow users to focus on creative and strategic work by automating routine digital tasks. However, despite the advancements,… →
The advent of advanced AI models has led to innovations in how machines process information, interact with humans, and execute tasks in real-world settings. Two emerging pioneering approaches are large concept models (LCMs) and large action models (LAMs). While both extend the foundational capabilities of large language models (LLMs), their objectives and applications diverge. LCMs… →
Aligning large language models (LLMs) with human values is essential as these models become central to various societal functions. A significant challenge arises when model parameters cannot be updated directly because the models are fixed or inaccessible. In these cases, the focus is on adjusting the input prompts to make the model’s outputs match the… →
Individuals with long-COVID exhibit a higher frequency of hypomagnesemia, vitamin D deficiency, and depression. Objective. To evaluate the efficacy and safety of oral supplementation with magnesium chloride plus vitamin D in alleviating depressive symptoms related to long-COVID. A total of 60 subjects, aged 52.8±12.6 years, with a diagnosis of hypomagnesemia, vitamin D deficiency, and mild-to-moderate… →
Evaluating conversational AI systems powered by large language models (LLMs) presents a critical challenge in artificial intelligence. These systems must handle multi-turn dialogues, integrate domain-specific tools, and adhere to complex policy constraints—capabilities that traditional evaluation methods struggle to assess. Existing benchmarks rely on small-scale, manually curated datasets with coarse metrics, failing to capture the dynamic… →
Proteins, essential macromolecules for biological processes like metabolism and immune response, follow the sequence-structure-function paradigm, where amino acid sequences determine 3D structures and functions. Computational protein science AIms to decode this relationship and design proteins with desired properties. Traditional AI models have achieved significant success in specific protein modeling tasks, such as structure prediction and… →
CONCLUSION: Stress management-based self-care counseling to prenatal usual care could be considered as an adjunctive care option for reducing on blood sugar and increasing the self-care activities of pregnant women with gestational diabetes and reducing their stress during pregnancy. →
INTRODUCTION: Surgical trauma induces a metabolic stress response, resulting in reduced insulin sensitivity and hyperglycaemia. Postoperative insulin resistance (IR) is associated with postoperative complications, and extended preoperative fasting may further aggravate the postoperative metabolic stress response. Nutritional strategies, such as carbohydrate loading (CHL), have been successfully used to attenuate postoperative IR. Recent evidence suggests that… →
In Boston, a groundbreaking study at Brigham and Women’s Hospital explored the impact of Speech Recognition (SR) on electronic health record (EHR) documentation-and the results were eye-opening. Experienced physicians participated in simulated outpatient scenarios, documenting patient notes using both speech recognition and traditional typing methods. The findings revealed that Speech Recognition notes were significantly more… →