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

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

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_Preoperatively Estimating the Malignant Potential of Mediastinal Lymph Nodes: A Pilot Study Toward Establishing a Robust Radiomics Model Based on Contrast-Enhanced CT I... by Mengshi Dong (5181833)

WEISS Catheter Segmentation in Fluoroscopy Dataset by Evangelos Mazomenos (6761597)

“…<p dir="ltr">This dataset contains fluoroscopy images extracted from four videos of canulation experiments with an aorta phantom and six videos of in-vivo catheterisation procedures: four Transcatheter Aortic Valve Implantations (TAVI) and two diagnostic catheterisation procedures. …”

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

“…It particularly highlights the potential of artificial intelligence to assess histopathological images.…”

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)

“…</p>Methods<p>We developed DFUCare, a platform that leverages computer vision and deep learning (DL) algorithms to localize, classify, and analyze DFUs non-invasively. …”

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

“…</p>Methods<p>We developed DFUCare, a platform that leverages computer vision and deep learning (DL) algorithms to localize, classify, and analyze DFUs non-invasively. …”

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

“…</p>Methods<p>We developed DFUCare, a platform that leverages computer vision and deep learning (DL) algorithms to localize, classify, and analyze DFUs non-invasively. …”

Image2_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

“…</p>Methods<p>We developed DFUCare, a platform that leverages computer vision and deep learning (DL) algorithms to localize, classify, and analyze DFUs non-invasively. …”

Image5_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

“…</p>Methods<p>We developed DFUCare, a platform that leverages computer vision and deep learning (DL) algorithms to localize, classify, and analyze DFUs non-invasively. …”

Data_Sheet_1_Deep learning-based ultrasonographic classification of canine chronic kidney disease.docx by Heejung Yu (17122910)

“…Therefore, deep-learning-based ultrasound diagnostics are potentially valuable tools for diagnosing CKD in dogs.…”

Image_1_Validation of miRNA signatures for ovarian cancer earlier detection in the pre-diagnosis setting using machine learning approaches.pdf by Konrad Stawiski (4753380)