A typical BCI system depicting the flow and processing of EEG data. by Gursimran Singh (575288)

Subjects:

ISAURO Cognitive Framework v0.1.1 – Public Research Summary (Under 4-Year Embargo) by Megan DeHerrera (21361439)

“…\n\nThis v0.1.1 summary provides a high-level overview of ISAURO’s cognitive scaffolding without disclosing internal module names or proprietary algorithms. Key principles include cultural modulation, emotion-cognition interfacing, and ethical alignment protocols aimed at decolonizing AI development practices. …”

Contrast enhancement of digital images using dragonfly algorithm by Soumyajit Saha (19726163)

“…Comparisons with state-of-art methods ensure the superiority of the proposed algorithm. The Python implementation of the proposed approach is available in this <a href="https://github.com/somnath796/DA_contrast_enhancement" target="_blank">Github repository</a>.…”

Data Sheet 1_Human-AI collaboration is not very collaborative yet: a taxonomy of interaction patterns in AI-assisted decision making from a systematic review.pdf by Catalina Gomez (7057646)

“…<p>Leveraging Artificial Intelligence (AI) in decision support systems has disproportionately focused on technological advancements, often overlooking the alignment between algorithmic outputs and human expectations. …”

Example of a typical workflow to construct a network using NeKo. by Marco Ruscone (11747264)

The results of curve fitting analysis. by Hai-bo Ai (20790405)

Comparative analysis of WordNet replacement impact on data distribution. by Enock Niyonkuru (21246879)

Ethics of algorithmic invasiveness in beauty apps: an online experimental survey of public perspectives by Yves Saint James Aquino (12311423)

“…Results show that functionalities with high degree of algorithmic invasiveness, such as AI-generated attractiveness rankings, are viewed as significantly less socially acceptable than less invasive functionalities. …”

LBQANA python code + Merged Gene Expression Dataset from GSE10810, GSE17907, GSE20711, GSE42568, GSE45827, and GSE61304 for Breast Cancer Biomarker Discovery by M RN (9866504)

Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection by Samin Aref (4683934)

“…Each network is provided in .gml format or .pkl format which can be read into a networkX graph object using standard functions from the networkX library in Python. For accessing other networks used in the study, please refer to the article for references to the primary sources of those network data.…”

Retrieved texts. by Jackson Jr Nforbewing Ndenkeh (13788072)

“…This study aims to evaluate Black MSM’ perspectives on the challenges to the uptake of PrEP and identify Black MSM-preferred chatbot functionalities and platforms for embedding AI chatbots. …”

Participants’ characteristics (N = 21). by Jackson Jr Nforbewing Ndenkeh (13788072)

“…This study aims to evaluate Black MSM’ perspectives on the challenges to the uptake of PrEP and identify Black MSM-preferred chatbot functionalities and platforms for embedding AI chatbots. …”

Survey database. by Jackson Jr Nforbewing Ndenkeh (13788072)

“…This study aims to evaluate Black MSM’ perspectives on the challenges to the uptake of PrEP and identify Black MSM-preferred chatbot functionalities and platforms for embedding AI chatbots. …”

Table 1_Development of a prognostic prediction model and visualization system for autologous costal cartilage rhinoplasty: an automated machine learning approach.docx by Aihemaitijiang Niyazi (22355542)

“…We proposed an improved metaheuristic algorithm (INPDOA) for AutoML optimization, validated against 12 CEC2022 benchmark functions. …”

Image 2_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.jpeg by Seungmi Kim (11071440)

Image 1_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.jpeg by Seungmi Kim (11071440)

Data Sheet 2_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.pdf by Seungmi Kim (11071440)

Image 3_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.jpeg by Seungmi Kim (11071440)

Table 1_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.xlsx by Seungmi Kim (11071440)

Data Sheet 1_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.pdf by Seungmi Kim (11071440)