Illustration of the texton detection process. by Vivian Akoto-Adjepong (18165075)

Illustration of the cell detection process. by Adam L. Tyson (10892822)

Simplified schematic diagram of the serial two-photon microscope and data acquisition process. by Adam L. Tyson (10892822)

Algorithm assessment of temporal drought class using TPM. by Muhammad Asif Khan (7367468)

Data_Sheet_1_Practice toward standardized performance testing of computer-aided detection algorithms for pulmonary nodule.pdf by Hao Wang (39217)

Excel file with primary data used to assemble figures. by Ankit Srivastava (742990)

Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

Post-processing stage. by Yubraj Gupta (7465394)

Pre-processing steps. by Yubraj Gupta (7465394)

Development and testing of an ARSD algorithm: Read, Understand, Learn, & Excel (Kucheria et al., 2019) by Priya Kucheria (5647163)

“…Postsecondary readers apply a wide range of behavioral strategies to process text for learning purposes. Currently, no tools exist to detect a reader’s use of strategies. …”

Malware detection workflow in compressed archives by Paul A. Gagniuc (1818325)

Data supporting figures and tables in Reimagining Electrical Diagrams in Construction: Automated Symbol Detection and Wiring Design and Generation with Deep Learning by IKENNA EKEKE (20996041)

Hybrid feature selection algorithm of CSCO-ROA. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

MLP vs classification algorithms. by Mohd Mustaqeem (19106494)

“…Software defects are the primary concern, and software defect prediction (SDP) plays a crucial role in detecting faulty modules early and planning effective testing to reduce maintenance costs. …”

Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png by Minjin Guo (22751300)

“…</p>Methods<p>To address these challenges, we propose a novel AI-driven framework that incorporates two key methodological innovations: CardioSpectra, a structured sparse inference model, and Risk-Stratified Exertional Embedding (RSEE), a domain-specific representation learning strategy. …”

Data_Sheet_1_Automatic speech analysis for detecting cognitive decline of older adults.pdf by Lihe Huang (19350508)

Supplementary Material for: The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis by He C. (2839727)

“…<b><i>Background:</i></b> Screening for major depression with the Patient Health Questionnaire-9 (PHQ-9) can be done using a cutoff or the PHQ-9 diagnostic algorithm. Many primary studies publish results for only one approach, and previous meta-analyses of the algorithm approach included only a subset of primary studies that collected data and could have published results. …”

Comparative analysis of DDcGAN-GSOM’s True Positive Rate, False Alarm Rate, and Specificity. by Nanavath Kiran Singh Nayak (22184565)

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Architecture of proposed system model. by Nanavath Kiran Singh Nayak (22184565)

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F1-score analysis of DDcGAN-GSOM with existing methods. by Nanavath Kiran Singh Nayak (22184565)

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