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

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

Presentation_1_Classification of expert-level therapeutic decisions for degenerative cervical myelopathy using ensemble machine learning algorithms.pdf حسب Dougho Park (9566450)

Data_Sheet_1_Deep Learning-Based Classification of GAD67-Positive Neurons Without the Immunosignal.pdf حسب Kotaro Yamashiro (10502753)

"…We then sought to detect GAD67-positive neurons without GAD67 immunosignals using a custom-made deep learning-based algorithm. Using this deep learning-based model, we succeeded in the binary classification of the neurons using Nissl and NeuN signals without referring to the GAD67 signals. …"

Table1_Nucleotide-level prediction of CircRNA-protein binding based on fully convolutional neural network.XLSX حسب Zhen Shen (393133)

"…</p><p>Methods: In this study, based on the deep learning models that implement pixel-level binary classification prediction in computer vision, we viewed the CircRNA-protein binding sites prediction as a nucleotide-level binary classification task, and use a fully convolutional neural networks to identify CircRNA-protein binding motif sites (CPBFCN).…"

DataSheet1_Nucleotide-level prediction of CircRNA-protein binding based on fully convolutional neural network.PDF حسب Zhen Shen (393133)

"…</p><p>Methods: In this study, based on the deep learning models that implement pixel-level binary classification prediction in computer vision, we viewed the CircRNA-protein binding sites prediction as a nucleotide-level binary classification task, and use a fully convolutional neural networks to identify CircRNA-protein binding motif sites (CPBFCN).…"

Super.Complex identifies likely protein complexes within a PPI network using a distributed supervised AutoML method. حسب Meghana Venkata Palukuri (11890672)

Accessibility of translation initiation sites is the strongest predictor of heterologous protein expression in <i>E. coli</i>. حسب Bikash K. Bhandari (11524776)

Influence of underlying networks on the performance of Graph CNNs trained gene expression data. حسب Halima Alachram (11570633)

Influence of underlying networks on the performance of Graph CNNs trained gene expression data. حسب Halima Alachram (11570633)

Influence of underlying networks on the performance of Graph CNNs trained gene expression data. حسب Halima Alachram (11570633)

Influence of underlying networks on the performance of Graph-CNNs trained gene expression data. حسب Halima Alachram (11570633)

Structure-based antibody paratope prediction with 3D Zernike descriptors and SVM حسب Sebastian Daberdaku (4391767)

"…Roto-translationally invariant descriptors are computed from circular patches of the antibody surface enriched with a chosen subset of physicochemical properties from the AAindex1 amino acid index set, and are used as samples for a binary classification problem. An SVM classifier is used to distinguish interface surface patches from non-interface ones. …"

Image_1_A predictive model based on random forest for shoulder-hand syndrome.JPEG حسب Suli Yu (14947807)

"…</p>Results<p>A binary classification model was trained based on 25 handpicked features. …"

Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease حسب 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. …"

Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield... حسب Uttam Khatri (12689072)

"…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …"

DataSheet1_Comparison of Descriptor- and Fingerprint Sets in Machine Learning Models for ADME-Tox Targets.docx حسب Álmos Orosz (12828104)

Image1_Comparison of Descriptor- and Fingerprint Sets in Machine Learning Models for ADME-Tox Targets.TIF حسب Álmos Orosz (12828104)

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

"…</p><p dir="ltr">These biological metrics were used to define a binary toxicity label: entries were classified as toxic (1) or non-toxic (0) based on thresholds from standardized guidelines (e.g., ISO 10993-5:2009) and literature consensus. …"