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)

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)

Subjects:

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)

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)

Impact of A.I feedback on student and qualified diagnostic radiographers’ diagnostic accuracy. by Clare Rainey (11677747)

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

“…This type of monitoring often relies on the use of navigation systems such as the Automatic Identification System (AIS). …”

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

“…Such use of PLMs for modeling, tracking, and automatically classifying language recovery in aphasia represents a promising deployment of GenAI in a clinical rehabilitation setting. …”

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

“…Such use of PLMs for modeling, tracking, and automatically classifying language recovery in aphasia represents a promising deployment of GenAI in a clinical rehabilitation setting. …”

Feature engineering. by Youli Jiang (15249070)

A graphical representation incorporating ISS range with splenic injury severity, management strategy, and number of patients. by Randeep S. Jawa (20489181)

Subjects:

Interaction plots for probability of in-hospital death by management group and spleen severity in patients (n = 7210) with AIS≤ = 2 in head/neck, face, chest, extremity, and extern... by Randeep S. Jawa (20489181)

Subjects:

Decision switching before any AI feedback and after all AI feedback, reported as % difference in diagnostic accuracy of participants (i.e., difference in diagnostic accuracy before... by Clare Rainey (11677747)

Raw data demonstrating a bimodal association of initial ED SBP range with weighted mortality for all patients (n = = 41187) by management group, whereby higher mortality is noted a... by Randeep S. Jawa (20489181)

Subjects:

Trust perception of student radiographers and radiographers at the beginning of the study, before accessing any of the AI feedback, following exposure to the AI and at the end of t... by Clare Rainey (11677747)

Raw data demonstrating a bimodal association of initial ED SBP range with mortality for patients (n = 8703) without severe injuries (AIS<3) in non-abdominal body regions by managem... by Randeep S. Jawa (20489181)

Subjects:

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

Impact of AI feedback on <i>all</i> participants’ diagnostic accuracy, when the AI feedback is <i>correct</i> and <i>INcorrect.</i> by Clare Rainey (11677747)

Impact of AI feedback on <i>student</i> participants’ diagnostic accuracy, when the AI feedback is <i>correct</i> and <i>INcorrect.</i> by Clare Rainey (11677747)

Impact of AI feedback on <i>radiographer</i> participants’ diagnostic accuracy, when the AI feedback is <i>correct</i> and <i>INcorrect.</i> by Clare Rainey (11677747)