Time-based splitting strategy and forecast horizons. by Thierry Jean (20691795)

Subjects:

The refracted opposition-based learning mechanism. by Yang Guo (399435)

Subjects:

Decrease in loss during the training process. by Muhammad Idrees (92773)

Largest changes in influenza vaccine rates, Pre- vs. Post-COVID-19. by Tyler B. Nofzinger (21560244)

Subjects:

Deep learning-based locomotive syndrome prediction method. by Junichi Kushioka (12236447)

Subjects:

The top 10 putative metabolites with the largest negative fold change between normal and thin cows. by Bhuripit Saraphol (20855573)

The top 10 putative metabolites with the largest positive fold change between normal and thin cows. by Bhuripit Saraphol (20855573)

Accuracy of multiple classifiers with a deep-learning-based feature set by Afira Aslam (21433666)

Subjects:

Cross-lagged panel model based on physical activity, aggressive behavior and Chinese language learning. by Zixia Bu (21475019)

Salt chemotaxis learning assay. by Masahiro Tomioka (430683)

Table 2_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…</p>Objective<p>To systematically assess ML-based mortality risk prediction models for SA-AKI patients.…”

Table 4_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…</p>Objective<p>To systematically assess ML-based mortality risk prediction models for SA-AKI patients.…”

Table 3_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…</p>Objective<p>To systematically assess ML-based mortality risk prediction models for SA-AKI patients.…”

Table 1_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…</p>Objective<p>To systematically assess ML-based mortality risk prediction models for SA-AKI patients.…”

Youthful systemic milieu in young recipients decreased apoptosis and oxidative stress damage in allografts, and promoted proliferation. by Chengjun Yu (12136227)

Cross-lagged panel model consistency test based on physical activity, aggressive behavior and Chinese language learning. by Zixia Bu (21475019)

Presentation 1_Prehospital tranexamic acid decreases early mortality in trauma patients: a systematic review and meta-analysis.pdf by Yi Li (1144)

“…</p>Systematic review registration<p>https://www.crd.york.ac.uk/PROSPERO/, Identifier: CRD 42019132189.…”

Data Sheet 1_Prehospital tranexamic acid decreases early mortality in trauma patients: a systematic review and meta-analysis.docx by Yi Li (1144)

“…</p>Systematic review registration<p>https://www.crd.york.ac.uk/PROSPERO/, Identifier: CRD 42019132189.…”

Oviduct Glycoprotein 1 (OVGP1) Diagnoses Polycystic Ovary Syndrome (PCOS) Based on Machine Learning Algorithms by Fengjuan Wang (768949)

Organic solvent exposure causes defects in salt chemotaxis learning. by Masahiro Tomioka (430683)