Objective: To explore the efficacy and safety of domestic bortezomib in combination with lenalidomide and dexamethasone in the treatment of newly diagnosed multiple myeloma (NDMM) . Methods: This multicenter, prospective, single-arm clinical study included 126 patients with NDMM admitted to seven hospitals between December 2019 and January 2022. All patients received domestic bortezomib in combination… →
INTRODUCTION: Previous studies have shown that substantial percentages of emergency department (ED) patients in the USA recommended for HIV or hepatitis C (HCV) decline testing. Evidence-based and cost-effective interventions to improve HIV/HCV testing uptake are needed, particularly for people who inject drugs (PWIDs) (currently or formerly), who comprise a group at higher risk for these… →
Optical Character Recognition (OCR) converts text from images into editable data, but it often produces errors due to issues like poor image quality or complex layouts. While OCR technology is valuable for digitizing text, achieving high accuracy can be challenging and typically requires ongoing refinement. Large Language Models (LLMs), such as the ByT5 model, offer… →
Deploying large language models (LLMs) has become a significant challenge for developers and researchers. As LLMs grow in complexity and size, ensuring they run efficiently across different platforms, such as personal computers, mobile devices, and servers, is daunting. The problem intensifies when trying to maintain high performance while optimizing the models to fit within the… →
Maximum A Posteriori (MAP) decoding is a technique used to estimate the most probable value of an unknown quantity based on observed data and prior knowledge, especially in digital communications and image processing. The effectiveness of MAP decoding depends on the accuracy of the assumed probability model. Researchers from the Nara Institute of Science and… →
The research field of log parsing is a critical component of software performance analysis and reliability. It transforms vast amounts of unstructured log data, often spanning hundreds of gigabytes to terabytes daily, into structured formats. This transformation is essential for understanding system execution, detecting anomalies, and conducting root-cause analyses. Traditional log parsers, which rely on… →
Handling partial code with potential bugs presents a significant challenge in developing real-time code suggestion systems. Incomplete code snippets often exhibit errors, necessitating accurate completion that also addresses embedded bugs to enhance the reliability and efficiency of AI-driven programming tools. The primary challenge involves developing models capable of generating code completions while simultaneously correcting potential… →
Introduction Mainframe operating systems, originating in the 1940s, remain essential to critical sectors such as finance and government. However, the vast legacy of COBOL code—estimated by IBM to be around 200 to 220 billion lines—needs to be migrated to modern platforms and rewritten in contemporary programming languages. This task is monumental, with the cost of… →
Financial data analysis plays a critical role in the decision-making processes of analysts and investors. The ability to extract relevant insights from unstructured text, such as earnings call transcripts and financial reports, is essential for making informed decisions that can impact market predictions and investment strategies. However, this task is complicated by the specialized language… →
Building and managing such AI systems requires specialized knowledge due to the intricate interactions between various components. The AI landscape is fragmented, with disparate tools and libraries that lead to integration challenges and inconsistencies. This fragmentation hinders the ability to create standardized, interoperable, and reusable AI components, making the development process arduous and less accessible… →