Data Sheet 1_Emotional prompting amplifies disinformation generation in AI large language models.docx by Rasita Vinay (21006911)

“…Introduction<p>The emergence of artificial intelligence (AI) large language models (LLMs), which can produce text that closely resembles human-written content, presents both opportunities and risks. …”

Feasibility of AI-powered assessment scoring: Can large language models replace human raters? by Michael Jaworski III (22156096)

A novel RNN architecture to improve the precision of ship trajectory predictions by Martha Dais Ferreira (18704596)

“…To solve these challenges, Recurrent Neural Network (RNN) models have been applied to STP to allow scalability for large data sets and to capture larger regions or anomalous vessels behavior. …”

AI KRegression by CHIN-CHENG CHU (20718575)

Presentation 1_Tracking priming-induced language recovery in aphasia with pre-trained language models.zip by Yan Cong (1491478)

Data Sheet 1_Tracking priming-induced language recovery in aphasia with pre-trained language models.zip by Yan Cong (1491478)

Ethnic identity as a moderator among APIDA students. by Ronna Bañada (19233063)

Interaction plot with 95% confidence intervals generated from the GAM regression model 1 in Table 2 examining initial ED SBP and management group interactions. by Randeep S. Jawa (20489181)

GPT-4 results in decreased error rate for all tasks with increasing complexity when compared to GPT-3.5-turbo. by Jacqueline A. Jansen (14894276)

The correlogram. by Bingtao Su (4740009)

“…Results demonstrated that groups with a lower prevalence of diabetes showed lower dietary EFP, while the dietary EFP and GHG emissions peaked among the prediabetes group with a prevalence of 32.7%−34.9%, and then decreased significantly with the increasing prevalence of prediabetes. …”

The food consumption quantity. by Bingtao Su (4740009)

“…Results demonstrated that groups with a lower prevalence of diabetes showed lower dietary EFP, while the dietary EFP and GHG emissions peaked among the prediabetes group with a prevalence of 32.7%−34.9%, and then decreased significantly with the increasing prevalence of prediabetes. …”

Dataset. by Bingtao Su (4740009)

“…Results demonstrated that groups with a lower prevalence of diabetes showed lower dietary EFP, while the dietary EFP and GHG emissions peaked among the prediabetes group with a prevalence of 32.7%−34.9%, and then decreased significantly with the increasing prevalence of prediabetes. …”

Analysis of errors of the AI model on accuracy and decision times for different tasks during the retrospective reader study. (a) by Kerol Djoumessi (21349992)

Feature engineering. by Youli Jiang (15249070)

Inherently interpretable deep learning framework highlights clinically relevant image regions. by Kerol Djoumessi (21349992)

The raw data used in this study. by Yu Fu (16582)

“…<div><p>Objectives</p><p>Hematological malignancies (HMs) pose a severe threat to human health and contribute substantially to the disease burden in mainland China and Taiwan. …”

Disease burden trends of leukemia and lymphoma analyzed by joinpoint regression analysis in mainland China. by Yu Fu (16582)

Disease burden trends of multiple myeloma and other hematological neoplasms analyzed by joinpoint regression analysis in mainland China. by Yu Fu (16582)

Projections of incidence for hematological malignancies in mainland China. by Yu Fu (16582)

Age- and sex-specific distribution of prevalence, incidence, mortality, and DALY rates for leukemia in mainland China. by Yu Fu (16582)