Geometry representations play a crucial role in solving complex 3D vision problems. The rapid evolution of deep learning has sparked significant interest in developing neural network-compatible geometric data representations. Recent technological advances, particularly those centered on coordinate networks, have demonstrated promising capabilities in modeling 3D geometry across diverse applications. These coordinate networks offer a functional… →
In recent years, the evolution of artificial intelligence has brought forth increasingly sophisticated large language models (LLMs). However, training these models remains a complex challenge due to their immense computational requirements. Traditionally, training such models has been possible only in centralized environments with high-bandwidth interconnects, typically within large data centers controlled by a few tech… →
Deep learning techniques are increasingly applied to neuroimaging analysis, with 3D CNNs offering superior performance for volumetric imaging. However, their reliance on large datasets is challenging due to the high cost and effort required for medical data collection and annotation. As an alternative, 2D CNNs utilize 2D projections of 3D images, which often limits volumetric… →
The rapid development of artificial intelligence (AI) has produced models with powerful capabilities, such as language understanding and vision processing. However, deploying these models on edge devices remains challenging due to limitations in computational power, memory, and energy efficiency. The need for lightweight models that can run effectively on edge devices, while still delivering competitive… →
CONCLUSION: The findings suggest a knowledge gap in the safety and effectiveness of smoking cessation medications, specifically in relation to cancer care. Addressing this knowledge gap may increase medication uptake, adherence, and quit rates. Cancer care providers are seen as instrumental in emphasizing the importance and safety of smoking cessation medications as well as patient… →
Machine learning is advancing rapidly, particularly in areas requiring extensive data processing, such as natural language understanding and generative AI. Researchers are constantly striving to design algorithms that maximize computational efficiency while improving the accuracy and performance of large-scale models. These efforts are critical for building systems capable of managing the complexities of language representation,… →
CONCLUSIONS: Intra-articular injections of corticosteroids are better than NSAIDs in reducing pain and improving mouth opening in patients suffering from TMD due to DDwoR. →
CONCLUSION: The results suggest that AI-simulated medical history conversations can support CDM training, especially when combined with structured feedback. Such training format may serve as a cost-effective supplement to existing training methods, better preparing students for real medical history conversations. →
The International Staging System for multiple myeloma recently underwent a second revision (R2-ISS) to include gain/amplification of 1q21 and account for the additive prognostic significance of multiple high-risk features. The phase 3 ICARIA-MM (isatuximab-pomalidomide-dexamethasone vs. pomalidomide-dexamethasone) and IKEMA (isatuximab-carfilzomib-dexamethasone vs. carfilzomib-dexamethasone) studies provide large datasets for retrospectively validating the prognostic value of the R2-ISS in… →
CONCLUSION: CRP-POCT is a cost-effective intervention for safely reducing antibiotic consumption in patients with AECOPD. →