Performance evaluation of models based on various indicators in 2008 and 2023. by Abdolhossein Boali (19996390)

Subjects:

Performance evaluation of ensemble model based on various indicators in 2008 and 2023. by Abdolhossein Boali (19996390)

Subjects:

DLS mGluR1/5 signaling activation in instrumental conditioning and differential behavioral sensitivity to A–O changes with training duration. by Vincent Paget-Blanc (21807763)

Literature comparison. by Saravanan Manoharan (21273304)

“…The method also includes automatic segmentation of punch videos, which improves classification accuracy by utilizing both data sources. To reduce labeling effort, we apply a Query by Committee-based active learning technique, significantly decreasing the required labeling effort by one-sixth. …”

Flow chart of proposed system. by Saravanan Manoharan (21273304)

“…The method also includes automatic segmentation of punch videos, which improves classification accuracy by utilizing both data sources. To reduce labeling effort, we apply a Query by Committee-based active learning technique, significantly decreasing the required labeling effort by one-sixth. …”

Literature review. by Saravanan Manoharan (21273304)

“…The method also includes automatic segmentation of punch videos, which improves classification accuracy by utilizing both data sources. To reduce labeling effort, we apply a Query by Committee-based active learning technique, significantly decreasing the required labeling effort by one-sixth. …”

Confusion matrix-punch classification. by Saravanan Manoharan (21273304)

“…The method also includes automatic segmentation of punch videos, which improves classification accuracy by utilizing both data sources. To reduce labeling effort, we apply a Query by Committee-based active learning technique, significantly decreasing the required labeling effort by one-sixth. …”

Data Sheet 1_Identification of ALDH2 as a novel target for the treatment of acute kidney injury in kidney transplantation based on WGCNA and machine learning algorithms and explora... by Jinpu Peng (748597)

“…Next, we found in a rat renal IRI model that increasing the expression of ALDH2 alleviated the impairment of renal function and decreased the expression of NGAL, a marker of tubular injury, and BAX, an apoptotic protein, as well as reducing the expression of the inflammatory factors IL1β and IL6. …”

DataSheet1_Predicting the solubility of CO2 and N2 in ionic liquids based on COSMO-RS and machine learning.docx by Hongling Qin (5557505)

“…To further improve the performance of COSMO-RS, two options were used, i.e., the polynomial expression to correct the COSMO-RS results and the combination of COSMO-RS and machine learning algorithms (eXtreme Gradient Boosting, XGBoost) to develop a hybrid model. …”

Data Sheet 1_Fast perceptual learning induces location-specific facilitation and suppression at early stages of visual cortical processing.docx by Yajie Wang (184298)

“…Here we developed a novel experimental design to investigate the cognitive neural mechanism of location specificity of fast PL. …”

Linear regression analysis. by Young Kyu Lee (14076058)

“…</p><p> Methods </p><p>CT images were acquired from consecutive 40 patients who received HTRT or RT alone for metastatic abdominal lymph nodes. …”

Patient characteristics. by Young Kyu Lee (14076058)

“…</p><p> Methods </p><p>CT images were acquired from consecutive 40 patients who received HTRT or RT alone for metastatic abdominal lymph nodes. …”

Data Sheet 1_Unveiling spatiotemporal evolution and driving factors of ecosystem service value: interpretable HGB-SHAP machine learning model.docx by Xiangming Xu (420946)

“…The ESV exhibited a slight increase in two counties, while it demonstrated a decrease in the remaining 16 counties at the county scale. …”

Supplementary Material for: Feedback from human instructors is superior to guidance by a virtual reality simulator when learning flexible bronchoscopy – a randomized controlled tri... by figshare admin karger (2628495)

Data Sheet 2_Machine learning-driven prediction model for cuproptosis-related genes in spinal cord injury: construction and experimental validation.zip by Yimin Zhou (3857113)

“…Four candidate genes (SLC31A1, DBT, DLST, LIAS) were obtained from the machine learning models, with SLC31A1 performing best (AUC = 0.958). …”

Data Sheet 1_Machine learning-driven prediction model for cuproptosis-related genes in spinal cord injury: construction and experimental validation.zip by Yimin Zhou (3857113)

“…Four candidate genes (SLC31A1, DBT, DLST, LIAS) were obtained from the machine learning models, with SLC31A1 performing best (AUC = 0.958). …”

Image 2_Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm.tif by Jiaming Wang (2637667)

“…Background<p>Osteoporosis is a metabolic bone disease characterized by a decrease in the amount of bone per unit volume. …”

Table 1_Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm.docx by Jiaming Wang (2637667)

“…Background<p>Osteoporosis is a metabolic bone disease characterized by a decrease in the amount of bone per unit volume. …”

Image 1_Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm.tif by Jiaming Wang (2637667)

“…Background<p>Osteoporosis is a metabolic bone disease characterized by a decrease in the amount of bone per unit volume. …”

The significant decrease in GLT-1 levels observed in the nucleus accumbens of rats that had consumed morphine for fifty-six days was completely reversed by the co-administration of... by María Elena Quintanilla (8068691)