An example of 2-dimensional non-linearly separable and non-separable data for binary classification. by Yuji Oyamada (11714754)

Illustration of the four steps in constructing the point feature binary mask. by Luka Maisuradze (8791229)

Three main modules involved in the identification of ceRNA-miRNA triplets. by Yi-Wen Hsiao (13767916)

Data generation process. by Nicola Dietler (12551766)

Graphical representation of KerTAD algorithm. by Luka Maisuradze (8791229)

Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke by Chulho Kim (622686)

“…<div><p>Background and purpose</p><p>This project assessed performance of natural language processing (NLP) and machine learning (ML) algorithms for classification of brain MRI radiology reports into acute ischemic stroke (AIS) and non-AIS phenotypes.…”

Flow chart of the algorithm. by Mukesh Karunanethy (18422857)

An overview of our ceRNAR package. by Yi-Wen Hsiao (13767916)

Illustration of the steps used to construct the mask for identifying corner regions in Hi-C maps. by Luka Maisuradze (8791229)

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…This process generated a ground-truth binary semantic segmentation mask and determined the bounding box coordinates (XYWH) for each cell. …”

S1 Data - by Lijie Feng (3412118)

“…The TF-IDF (Term Frequency-Inverse Document Frequency) algorithm processes the data to obtain critical technical words. …”

LScD (Leicester Scientific Dictionary) by Neslihan Suzen (6947114)

“…Ramya, "Effective pre-processing activities in text mining using improved porter’s stemming algorithm," International Journal of Advanced Research in Computer and Communication Engineering, vol. 2, no. 12, pp. 4536-4538, 2013.…”

DataSheet_1_Histopathology image classification: highlighting the gap between manual analysis and AI automation.pdf by Refika Sultan Doğan (17799677)

Table_1_Identification of sources of DIF using covariates in patient-reported outcome measures: a simulation study comparing two approaches based on Rasch family models.DOCX by Yseulys Dubuy (16809567)

UMAHand: Hand Activity Dataset (Universidad de Málaga) by Eduardo Casilari (3333906)

“…<p dir="ltr">The objective of the UMAHand dataset is to provide a systematic, Internet-accessible benchmarking database for evaluating algorithms for the automatic identification of manual activities. …”

Schematic overview of SINATRA Pro: A novel framework for discovering biophysical signatures that differentiate classes of proteins. by Wai Shing Tang (9541179)

Raw LC-MS/MS and RNA-Seq Mitochondria data by Stefano Martellucci (16284377)

“…<p dir="ltr"><b>LC-MS/MS raw data</b></p><p dir="ltr">Spectrum matching and protein identification and validation were performed with MSFragger, and quantification of protein intensities with matching between runs was performed with IonQuant as components of the FragPipe analysis pipeline using the default settings of each module. …”

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”