Overview of MitoTracer algorithm. by Xuexin Yu (733842)

Predictions from a Universal Value Function Approximator (UVFA) algorithm. by Sam Hall-McMaster (10343795)

Data Sheet 1_Hybrid machine learning algorithms accurately predict marine ecological communities.pdf by Luciana Erika Yaginuma (10477013)

“…This study aims to predict the spatial distribution of nematode associations from 25 m to 2500 m water depth over an area of 350,000 km² and understand the major oceanographic processes influencing them. The study considered data from 245 nematode genera and 44 environmental parameters from 100 stations. …”

Flow chart of the search process. by Lei Gao (6566)

“…Compared to traditional algorithms, machine learning algorithms are more effective at capturing nonlinear relationships and developing more accurate diagnostic and predictive models.…”

Technological Fitness and Coherence explanation. Schematic representation of the workings of the Fitness and Complexity algorithm and Coherence diversification. by Matteo Straccamore (15083799)

Sample cancer patient treatment timeline with data generated and captured within the EHR. by Shreya Chappidi (18204121)

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Accuracy and average dots covered for difficulty level 11 using gradient descent to find the optimal solution. by Tarun Khajuria (12117309)

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Screening criteria applied for the study selection process. by Yong Lin Lai (20854961)

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Multi-sensor fusion process and algorithm workflow. by Hongliang Zou (20707270)

Data underlying the findings. by Carol Kotliar (22351525)

a) Boxplot and b) scatterplot distributions of manual and data-derived progression free survival dates. by Shreya Chappidi (18204121)

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The overview of process of link by machine learning with local- and global- similarity-based scores. by Pei Zhao (487688)

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The loss and accuracy curves of both training and testing processes for the proposed approach on the Messidor dataset. by Zenglei Liu (20629838)

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The loss and accuracy curves of both training and testing processes for the proposed approach on the APTOS2019 dataset. by Zenglei Liu (20629838)

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BIC-SAC findings. by Nayeem Ahmad Khan (11727377)

The pre-processing of CTG raw signals [26]. by Amin Ullah (12015113)

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Data. by Yin Luo (160903)

“…To address this, we propose a novel hybrid deep learning model that integrates optimized data decomposition with advanced sequence modeling to enhance feature extraction and temporal pattern learning. …”

Work flow process of the proposed EE-AZR-LEACH protocol. by Fazia Akhtar (21453122)

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The taxonomy of data augmentation. by Rodrigo Gutiérrez Benítez (19746443)

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Data types and their sources. by Firdissa Sadeta Tiye (21222102)

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