Founded in 2022, Perplexity AI has quickly emerged as a significant player in artificial intelligence, particularly in AI-driven search technologies. With a strong focus on innovation and user-centric features, the company has introduced groundbreaking advancements while securing notable investments to expand its operations. Recent developments in Perplexity AI’s portfolio highlight its commitment to redefining how… →
CONCLUSIONS: All three residual caries evaluation methods were efficient, independently, in detecting residual caries in prepared cavities. DIAGNOdent was the most specific of the tested modalities and had the highest agreement with the bacteriological confirmatory test. →
CONCLUSIONS: Extragenital screening for CT and NG should be recommended as part of STI services to MSM population. Self-collection of rectal and pharyngeal specimens had good performance for CT and NG tests and acceptability to the target population. →
INTRODUCTION: Sickle cell disease (SCD) is one of the most common genetic diseases in the world, annually affecting approximately 310 000 births and causing >100 000 deaths. Vaso-occlusive crisis (VOC) is the most frequent complication of SCD, leading to bone pain, thoracic pain (acute chest syndrome) and/or abdominal spasms. It is the main cause of… →
INTRODUCTION AND AIM: Diabetes is a global health emergency with increasing prevalence and diabetes-associated morbidity and mortality. One of the challenges in optimising diabetes care is translating research advances in this heterogeneous disease into clinical care. A potential solution is the introduction of precision medicine approaches into diabetes care.We aim to develop a digital platform… →
Trailing the advances made by AI in drug discovery, one can say there is a vast amount of untapped potential. Therapeutic nanobodies, particularly, have had relatively limited breakthroughs as they require complex interdisciplinary knowledge. The COVID-19 pandemic urged the development of therapeutic nanobodies that exhibit high binding affinity and stability for the SARS-CoV-2 in a… →
Parallel computing continues to advance, addressing the demands of high-performance tasks such as deep learning, scientific simulations, and data-intensive computations. A fundamental operation within this domain is matrix multiplication, which underpins many computational workflows. Recent hardware innovations, like Tensor Core Units (TCUs), offer efficient processing by optimizing constant-size matrix multiplications. These units are now being… →
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… →