Large Language Models (LLMs) have significantly advanced artificial intelligence, particularly in natural language understanding and generation. However, these models encounter difficulties with complex reasoning tasks, especially those requiring multi-step, non-linear processes. While traditional Chain-of-Thought (CoT) approaches, which promote step-by-step reasoning, improve performance on simpler tasks, they often fall short in addressing more intricate problems. This… →
Artificial intelligence research has steadily advanced toward creating systems capable of complex reasoning. Multimodal large language models (MLLMs) represent a significant development in this journey, combining the ability to process text and visual data. These systems can address intricate challenges like mathematical problems or reasoning through diagrams. By enabling AI to bridge the gap between… →
The generation of synthetic tabular data has become increasingly crucial in fields like healthcare and financial services, where privacy concerns often restrict the use of real-world data. While autoregressive transformers, masked transformers, and diffusion models with transformers, have shown significant success in generating high-quality synthetic data with strong fidelity, utility, and privacy guarantees, they face… →
The aim of this study was to assess if ischaemic preconditioning (IPC) can reduce pain perception and enhance corticospinal excitability during voluntary contractions. In a randomised, within-subject design, healthy participants took part in three experimental visits after a familiarisation session. Measures of pressure pain threshold (PPT), maximum voluntary isometric force, voluntary activation, resting twitch force,… →
INTRODUCTION: The follow-up adherence after treatment for a positive screening test is critical for preventing the development of screen-detected abnormalities in cervical cancer. Yet, this poses a major challenge in developing countries like Ethiopia, emphasising the urgency for intervention strategies. Our trial aims to assess which strategies would be effective in improving adherence to follow-up… →
CONCLUSIONS: Both Tele-cEEG and Tele-rEEG are feasible, although Tele-EEG requires additional EEG specialists, budget, and computational resources. While Tele-cEEG may help detect NCS/NCSE, this study had limited power to detect its efficacy in reducing mortality or improving functional outcomes. In limited-resource settings, Tele-rEEG approximating 30 min or longer offers a feasible and potentially valuable initial… →
CONCLUSION: These qualitative research results identified several important barriers to engaging in HIV care and provide insights into the mechanisms through which the Daraja intervention operated to affect the perceived stigma, social support, self-efficacy, and increased capacity of participants to navigate the HIV clinic during HIV clinic linkage. →
CONCLUSION: This study suggests that WB-EMS is safe and feasible for cancer patients. Furthermore, it showed that even after 2 weeks, improvements concerning the physical performance and patient-reported outcomes can be achieved. This study indicates benefits of WB-EMS as short-term exercise methode in cancer patients, that could be utelised in fields such as cancer prehabilitation. →
PURPOSE: To evaluate the efficacy and subjects’ perception of the Modified Schirmer Test (MST) to the traditional Unstimulated Salivary Flow Test (USFT) when measuring salivary flow rate for screening and monitoring patients’ dry mouth. →
Microsoft has open-sourced Phi-4, a compact and efficient small language model, on Hugging Face under the MIT license. This decision highlights a shift towards transparency and collaboration in the AI community, offering developers and researchers new opportunities. What Is Microsoft Phi-4? Phi-4 is a 14-billion-parameter language model developed with a focus on data quality and… →