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关键词： health sciences   natural sciences   immunity   computer science  

摘要： System-level patient health signals, as captured by treatment-emergent adverse events (TEAEs), might contain correlates of immune checkpoint inhibitor (ICI) therapy response. Using all TEAEs and a novel machine learning modeling approach, we derived a composite signature predictive of, and potentially specific to, the response to the anti-PD-L1 ICI durvalumab in patients with non-small-cell lung cancer (NSCLC). We trained on data from the durvalumab arm and chemotherapy arm in the MYSTIC clinical trial and tested on data from four independent durvalumab-containing NSCLC trials using only the first 60 days' TEAEs. We directly compared our signature performance against that of three different definitions of immune-related adverse events. Only our signature was predictive and identified longer survivors in patients treated with durvalumab but not in patients treated with chemotherapy or placebo. It also identified durvalumab-treated long survivors with stable disease at their first RECIST evaluation and a set of PD-L1-negative long survivors.

关键词： Capital punishment   Jesus   Mark  

摘要： This article examines the reference to capital punishment in Mark 7.10. We ask if it was more likely to have been intended and received in a literal or a hyperbolic sense within the first century.1 We conclude that a literal sense is more probable.

关键词： Natural sciences   Applied sciences   Computer science  

摘要： This article proposes a new digital watermarking mechanism based on the Ethereum blockchain, Smart Contract, and Interplanetary File System (IPFS), with an enhanced Fast Walsh Hadamard Transform (FWHT) algorithm for watermark embedding and extraction. The proposed scheme aims to address the limitations of existing digital watermarking techniques, such as dependence on third-party platforms, by leveraging the decentralization feature of blockchain. The Smart Contract is used to manage the transaction between the parties involved in the watermarking process, while IPFS is used to store the watermark data. The enhanced FWHT algorithm is used to embed the watermark into the host image without affecting its visual quality. The results show that the proposed scheme outperforms the state-of-the-art algorithms in terms of both imperceptibility and robustness. Additionally, it demonstrates that our scheme can effectively resist various attacks. Therefore, our scheme can be a promising solution for image copyright protection, authentication applications, and image trading.

关键词： Computer science   Machine learning   Technology  

摘要： [...]technology firms are making scaled-down versions that can be run on consumer hardware - and that rival the performance of older, larger models. The result of training on this text, Bubeck says, is a model that fits on a mobile phone but has the power of the initial 2022 version of ChatGPT. Based on Whisper - an open-weight speech-recognition model from OpenAI - and on Gemma 2 from Google DeepMind, the system will allow physicians to transcribe conversations and convert them to medical notes, and also summarize data from medical-research participants. CELLama, developed at the South Korean pharmaceutical company Portrai in Seoul, exploits local LLMs such as Llama 3.1 to reduce information about a cell's gene expression and other characteristics to a summary sentence2.

关键词： Contrastive Learning  

摘要： As the demand for computer science (CS) skills grows, mastering foundational concepts is crucial yet challenging for novice learners. To address this challenge, we present KoroT-3E, an AI-based system that creates personalized musical mnemonics to enhance both memory retention and understanding of concepts in CS. KoroT-3E enables users to transform complex concepts into memorable lyrics and compose melodies that suit their musical preferences. We conducted semi-structured interviews (n=12) to investigate why novice learners find it challenging to memorize and understand CS concepts. The findings, combined with constructivist learning theory, established our initial design, which was then refined following consultations with CS education experts. An empirical experiment(n=36) showed that those using KoroT-3E (n=18) significantly outperformed the control group (n=18), with improved memory efficiency, increased motivation, and a positive learning experience. These findings demonstrate the effectiveness of integrating multimodal generative AI into CS education to create personalized and interactive learning experiences. Copyright © 2024, The Authors. All rights reserved.

关键词： Psychology   Computer science  

摘要： Large language models (LLMs) have shown remarkable abilities recently, including passing advanced professional exams and demanding benchmark tests. This performance has led many to suggest that they are close to achieving humanlike or "true" understanding of language, and even artificial general intelligence (AGI). Here, we provide a new open-source benchmark, the Two Word Test (TWT), that can assess semantic abilities of LLMs using two-word phrases in a task that can be performed relatively easily by humans without advanced training. Combining multiple words into a single concept is a fundamental linguistic and conceptual operation routinely performed by people. The test requires meaningfulness judgments of 1768 noun-noun combinations that have been rated as meaningful (e.g., baby boy) or as having low meaningfulness (e.g., goat sky) by human raters. This novel test differs from existing benchmarks that rely on logical reasoning, inference, puzzle-solving, or domain expertise. We provide versions of the task that probe meaningfulness ratings on a 0-4 scale as well as binary judgments. With both versions, we conducted a series of experiments using the TWT on GPT-4, GPT-3.5, Claude-3-Optus, and Gemini-1-Pro-001. Results demonstrated that, compared to humans, all models performed relatively poorly at rating meaningfulness of these phrases. GPT-3.5-turbo, Gemini-1.0-Pro-001 and GPT-4-turbo were also unable to make binary discriminations between sensible and nonsense phrases, with these models consistently judging nonsensical phrases as making sense. Claude-3-Opus made a substantial improvement in binary discrimination of combinatorial phrases but was still significantly worse than human performance. The TWT can be used to understand and assess the limitations of current LLMs, and potentially improve them. The test also reminds us that caution is warranted in attributing "true" or human-level understanding to LLMs based only on tests that are challenging for humans.

关键词： Computer science   computer security \u0026 cryptography  

ISBN: (数字)9781394272303 ISBN: (纸本)9781394272273

摘要： This book containing 33 chapters provides an insightful look at creative approaches toward the accelerated development of computing and multidisciplinary IT solutions for society. Technology is advancing on all fronts and is opening new and innovative adaptations to our modern world every single day causing huge shifts in practices and patterns. These new technologies allow

关键词： prompt engineering   prompt design   prompt learning   prompt tuning   large language models   LLMs   scoping review   clinical natural language processing   natural language processing   NLP   medical texts   medical application   medical applications   clinical practice   privacy   medicine   computer science   medical informatics  

摘要： Background: Prompt engineering, focusing on crafting effective prompts to large language models (LLMs), has garnered attention for its capabilities at harnessing the potential of LLMs. This is even more crucial in the medical domain due to its specialized terminology and language technicity. Clinical natural language processing applications must navigate complex language and ensure privacy compliance. Prompt engineering offers a novel approach by designing tailored prompts to guide models in exploiting clinically relevant information from complex medical texts. Despite its promise, the efficacy of prompt engineering in the medical domain remains to be fully explored. Objective: The aim of the study is to review research efforts and technical approaches in prompt engineering for medical applications as well as provide an overview of opportunities and challenges for clinical practice. Methods: Databases indexing the fields of medicine, computer science, and medical informatics were queried in order to identify relevant published papers. Since prompt engineering is an emerging field, preprint databases were also considered. Multiple data were extracted, such as the prompt paradigm, the involved LLMs, the languages of the study, the domain of the topic, the baselines, and several learning, design, and architecture strategies specific to prompt engineering. We include studies that apply prompt engineering-based methods to the medical domain, published between 2022 and 2024, and covering multiple prompt paradigms such as prompt learning (PL), prompt tuning (PT), and prompt design (PD). Results: We included 114 recent prompt engineering studies. Among the 3 prompt paradigms, we have observed that PD is the most prevalent (78 papers). In 12 papers, PD, PL, and PT terms were used interchangeably. While ChatGPT is the most commonly used LLM, we have identified 7 studies using this LLM on a sensitive clinical data set. Chain-of-thought, present in 17 studies, emerges as the mo

关键词： Technology   Computer science   Climate sciences   Engineering  

摘要： In the hills of eastern Tennessee, a record-breaking machine called Frontier is providing scientists with unprecedented opportunities to study everything from atoms to galaxies.