One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

Diagnostic performance for determining malignancy; binary classification. by Seung Seog Han (4782486)

A new fast filtering algorithm for a 3D point cloud based on RGB-D information by Chaochuan Jia (7256237)

Results of the model on test sets 1 and 2. by Rémy Peyret (14691736)

“…We describe a patch-based algorithm that incorporates a convolutional neural network to detect and locate invasive carcinoma on breast whole-slide images. …”

Data set constituents. by Rémy Peyret (14691736)

“…We describe a patch-based algorithm that incorporates a convolutional neural network to detect and locate invasive carcinoma on breast whole-slide images. …”

Scanners and staining methods. by Rémy Peyret (14691736)

“…We describe a patch-based algorithm that incorporates a convolutional neural network to detect and locate invasive carcinoma on breast whole-slide images. …”

Table_1_Development and validation of a diagnostic model for the identification of chronic ocular graft-versus-host disease (oGVHD).DOCX by Zhan Shen (4059739)

PET/CT data for PDL auto-segmentation project by Kareem Wahid (9944579)

Image_2_A Diagnostic Model for Kawasaki Disease Based on Immune Cell Characterization From Blood Samples.TIF by Shangming Du (9950501)

Image_4_A Diagnostic Model for Kawasaki Disease Based on Immune Cell Characterization From Blood Samples.TIF by Shangming Du (9950501)

Image_1_A Diagnostic Model for Kawasaki Disease Based on Immune Cell Characterization From Blood Samples.TIF by Shangming Du (9950501)

Image_3_A Diagnostic Model for Kawasaki Disease Based on Immune Cell Characterization From Blood Samples.TIF by Shangming Du (9950501)

Image_3_Deep Learning on High-Throughput Transcriptomics to Predict Drug-Induced Liver Injury.pdf by Ting Li (117885)

Image_2_Deep Learning on High-Throughput Transcriptomics to Predict Drug-Induced Liver Injury.tif by Ting Li (117885)

Image_1_Deep Learning on High-Throughput Transcriptomics to Predict Drug-Induced Liver Injury.tif by Ting Li (117885)

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

“…Our research used open-source multi-centered image datasets that included records of 100.000 non-overlapping images from 86 patients for training and 7180 non-overlapping images from 50 patients for testing. …”

Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease by Zhuoyan Chen (12193358)

“…<i>Z</i> score standardization and independent sample <i>t</i> test were applied to identify optimal predictive features, which were then utilized in seven ML algorithms for training and validation. …”

Image3_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

“…The preliminary performance of the platform was tested on wound images acquired using a cell phone.…”

Image4_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

“…The preliminary performance of the platform was tested on wound images acquired using a cell phone.…”

Image1_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

“…The preliminary performance of the platform was tested on wound images acquired using a cell phone.…”