DeLong Tests for Comparing Area Under the Receiver Operating Characteristics Curves of Different Models with Four Algorithms in Testing Dataset. by Yingke Xu (2216680)

Subjects:

Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms by Saadiallakh Normatov (20682324)

Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms by Saadiallakh Normatov (20682324)

Data Sheet 1_Construction of a prognostic model for endometrial cancer related to programmed cell death using WGCNA and machine learning algorithms.zip by Weicheng Pan (12629762)

Data Sheet 1_Investigating neural markers of Alzheimer's disease in posttraumatic stress disorder using machine learning algorithms and magnetic resonance imaging.pdf by Gabriella Yakemow (20137758)

“…Additionally, we utilized two previously established machine learning-based algorithms, one representing AD-like brain activity (Machine learning-based AD Designation [MAD]) and the other focused on AD-like brain structural changes (AD-like Brain Structure [ABS]). …”

Code and data for the paper "Investigating machine learning algorithms to classify label-free images of pancreatic neuroendocrine neoplasms" by Noelle Madyson Daigle (22120114)

“…<p dir="ltr">Code and data for analysis detailed in the paper "Investigating machine learning algorithms to classify label-free images of pancreatic neuroendocrine neoplasms." …”

Prediction of Fraction Unbound in Human Plasma for Per- and Polyfluoroalkyl Substances: Evaluating Transfer Learning as an Algorithmic Solution to the Problem of Sparse Data by Gabriel Sinclair (10688582)

Subjects:

Prediction of Fraction Unbound in Human Plasma for Per- and Polyfluoroalkyl Substances: Evaluating Transfer Learning as an Algorithmic Solution to the Problem of Sparse Data by Gabriel Sinclair (10688582)

Subjects:

Flow chart of the six hybrid ET models and a pure machine learning model using random forest (RF) algorithms. by Yeonuk Kim (4589488)

Subjects:

Algorithm for the proposed work. by Shuvo Biswas (21728782)

“…All models were then tested in an FL platform to maintain data privacy. In the FL platform, the VGG16 algorithm showed the best results, with 92.08% accuracy on ISBI2016 and 94% on ISBI2017. …”

Accuracy of cross-prediction classification (PR-AUC) results using two classification algorithms for the two T2D datasets by Qin et al. [ by Xinyu Han (2237545)

Computed mean error rate for each algorithm and dataset. by Yubraj Gupta (7465394)

Subjects:

Identification of early prognostic biomarkers in Severe Fever with Thrombocytopenia Syndrome using machine learning algorithms by Jie Zhu (126574)

“…Six different machine learning algorithms were employed to develop prognostic models based on the clinical features during the acute phase, which were reduced using Lasso regression.…”

Comparison of the performance of ML algorithms in predicting maize yield using 5-fold CV. by Oumnia Ennaji (20442244)

Data Sheet 1_Causal contextual bandits with one-shot data integration.pdf by Chandrasekar Subramanian (20393715)

“…We perform several experiments, both using purely synthetic data and using a real-world dataset. …”

Machine learning algorithms using the inflammatory prognostic index for contrast-induced nephropathy in NSTEMI patients by Faysal Şaylık (15296054)

“…We aimed to investigate the predictive role of IPI for contrast-induced nephropathy (CIN) development in non-ST segment elevation myocardial infarction patients using a nomogram and performing machine learning (ML) algorithms.…”

Comparison of clustering algorithms (K-Means, MeanShift, etc.) based on the average Silhouette Score. by Manju M. S. (22793350)

Data Sheet 1_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.pdf by Benedictor Alexander Nguchu (9984371)

“…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …”

Characteristics of training algorithms. by Tuan Anh Nguyen (121944)

“…The issue of overfitting is significantly resolved, unlike in the case of the Backpropagation Neural Network (BPNN), which is used as a benchmark for comparison. Overall, the proposed algorithm significantly improves data training accuracy and generalization performance.…”

The structure of genetic algorithm (GA). by Ali Akbar Moosavi (17769033)

“…In this study some of the most appropriate machine learning approaches, including variants of artificial neural networks (ANNs) were used for predicting K_fs by some easily measurable soil attributes. …”