A* Path-Finding Algorithm to Determine Cell Connections حسب Max Weng (22327159)

Correlation heatmap of the principal components. حسب Muhammad Hilal Alkhudaydi (21560690)

"…These are then compared with other algorithms, such as vector autoregression, in portfolio optimisation tests. …"

Scatter diagram of different principal elements. حسب Jizhong Wang (7441697)

Algorithm testing. حسب Ziad M. Ali (12516532)

الموضوعات:

TB screening and diagnostic algorithm. حسب Arangba S (21656068)

Convergence curves of the investigated algorithms. حسب Ziad M. Ali (12516532)

الموضوعات:

Phenotype frequencies for each mutant and for complementation testing. حسب McKenna Feltes (11242085)

Accuracy and average dots covered for difficulty level 11 using gradient descent to find the optimal solution. حسب Tarun Khajuria (12117309)

Phenotype frequency and complementation for additional novel DY alleles. حسب McKenna Feltes (11242085)

Dispersion signal in principal and residual space in PCA and KPCA algorithm. حسب Emmanuel Ndongue Esseme (22615091)

M3C2 algorithm diagram. حسب Xiaowei Li (620087)

الموضوعات:

Spatial spectrum of the 100th frame under array distortion conditions (20 elements). حسب Gaoxiang Xing (21755689)

Dispersion signal in principal and residual space in PCA-FFT and KPCA-FFT algorithm. حسب Emmanuel Ndongue Esseme (22615091)

Overview of different metaheuristic algorithms used in PV parameter estimation and their corresponding full names and acronyms. حسب Ziad M. Ali (12516532)

الموضوعات:

Signal strength of adverse events that are unexpected findings of Relugolix (Orgovyx^®)-related adverse events at the preferred term (PT) level. حسب Ruibo Li (2063167)

Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. حسب Borjan Milinkovic (21349908)

Clinical use algorithm. حسب Chibuike K. Uwakwe (22655742)

Filtered Labels after applying the data preparation algorithms. حسب Tanjim Taharat Aurpa (11250554)

Data Sheet 1_Clinical validation of an artificial intelligence algorithm for classifying tuberculosis and pulmonary findings in chest radiographs.pdf حسب Thiago Fellipe Ortiz de Camargo (19460818)

"…</p>Results<p>In the internal validation, the Lung Abnormality and Tuberculosis models achieved an AUC of 0.94, while the Radiological Findings model yielded a mean AUC of 0.84. During the external validation, utilizing the ground truth generated by board-certified thoracic radiologists, the algorithm achieved better sensitivity in 6 out of 11 classes than physicians with varying experience levels. …"

Dataset state after applying our data preparation algorithm. حسب Tanjim Taharat Aurpa (11250554)