Showing 21 - 40 results of 53,163 for search '(((( ai large increases ) OR ( a large increases ))) OR ( via ((step decrease) OR (a decrease)) ))', query time: 1.23s Refine Results
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    Human-AI Collaborative Journaling with POCKET-MIND: A Dual-Prompt Framework for Emotional Exploration and Goal Attainment by HaeJi Yang (22829125)

    Published 2025
    “…<p>Human-AI collaborative systems are increasingly explored as tools for promoting mental well-being and supporting personal development. …”
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    Data Sheet 1_Conversational AI agent for precision oncology: AI-HOPE-WNT integrates clinical and genomic data to investigate WNT pathway dysregulation in colorectal cancer.docx by Ei-Wen Yang (149486)

    Published 2025
    “…</p>Methods<p>AI-HOPE-WNT employs a modular architecture combining large language models (LLMs), a natural language-to-code engine, and a backend statistical workflow interfaced with harmonized data from cBioPortal. …”
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    Opening the Black Box(es) by Charles Pence (99065)

    Published 2025
    “…<p dir="ltr">A talk which explores challenges for contemporary work in digital humanities stemming from the increasing use of generative large language models.…”
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    Data_Sheet_1_Application of a nomogram model for the prediction of 90-day poor outcomes following mechanical thrombectomy in patients with acute anterior circulation large-vessel o... by Xia Li (14984)

    Published 2024
    “…Moreover, five variables, namely, age (odds ratio [OR]: 1.049, 95% CI [1.016–1.083]; p = 0.003), glucose level (OR: 1.163, 95% CI [1.038–1.303]; p = 0.009), baseline National Institute of Health Stroke Scale (NIHSS) score (OR: 1.066, 95% CI [0.995–1.142]; p = 0.069), unsuccessful recanalization (defined as a TICI grade of 0 to 2a) (OR: 3.730, 95% CI [1.688–8.245]; p = 0.001), and early neurological deterioration (END, defined as an increase of ≥4 points between the baseline NIHSS score and the NIHSS score at 24 h after MT) (OR: 3.383, 95% CI [1.411–8.106]; p = 0.006), were included in the nomogram to predict the potential risk of poor outcomes at 90 days following MT in LVO patients, with a C-index of 0.763 (0.693–0.832) in the training set and 0.804 (0.719–0.889) in the validation set.…”
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    Data Sheet 1_Exploring LLM-powered multi-session human-robot interactions with university students.pdf by Mauliana Mauliana (21467063)

    Published 2025
    “…<p>This exploratory study investigates how open-domain, multi-session interactions with a large language model (LLM)-powered social humanoid robot (SHR), EMAH, affect user perceptions and willingness for adoption in a university setting. …”
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