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

“…Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. …”

Snake niche modeling score (SNMS). by Carlos Bravo-Vega (12328684)

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …”

Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level by Giovanni Nattino (561797)

“…Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …”

Optimizing the JSM Program by Luca Frigau (8150688)

“…Specifically, a measure based on total variation distance that ranges from 0 (random scheduling) to 1 (no overlapping content) finds that the original schedule had a score of 0.058, whereas our proposed schedule achieved a score of 0.371. …”

Results of network meta-analysis. by Kaiyu Zhang (198799)

“…Concerning National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) total score, α-RBs+ moxibustion+ auricular point sticking was most likely to be optimal treatment, the therapy ranking second was α-RBs+ needling, and the therapy ranking third was α-RBs+ moxibustion. …”

Results of network meta-analysis. by Kaiyu Zhang (198799)

“…Concerning National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) total score, α-RBs+ moxibustion+ auricular point sticking was most likely to be optimal treatment, the therapy ranking second was α-RBs+ needling, and the therapy ranking third was α-RBs+ moxibustion. …”

Results of network meta-analysis. by Kaiyu Zhang (198799)

“…Concerning National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) total score, α-RBs+ moxibustion+ auricular point sticking was most likely to be optimal treatment, the therapy ranking second was α-RBs+ needling, and the therapy ranking third was α-RBs+ moxibustion. …”

Results of network meta-analysis. by Kaiyu Zhang (198799)

“…Concerning National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) total score, α-RBs+ moxibustion+ auricular point sticking was most likely to be optimal treatment, the therapy ranking second was α-RBs+ needling, and the therapy ranking third was α-RBs+ moxibustion. …”

Study flowchart. by Kaiyu Zhang (198799)

“…Concerning National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) total score, α-RBs+ moxibustion+ auricular point sticking was most likely to be optimal treatment, the therapy ranking second was α-RBs+ needling, and the therapy ranking third was α-RBs+ moxibustion. …”

Risk of bias graph. by Kaiyu Zhang (198799)

“…Concerning National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) total score, α-RBs+ moxibustion+ auricular point sticking was most likely to be optimal treatment, the therapy ranking second was α-RBs+ needling, and the therapy ranking third was α-RBs+ moxibustion. …”

Results of network meta-analysis. by Kaiyu Zhang (198799)

“…Concerning National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) total score, α-RBs+ moxibustion+ auricular point sticking was most likely to be optimal treatment, the therapy ranking second was α-RBs+ needling, and the therapy ranking third was α-RBs+ moxibustion. …”

Characteristics of included studies. by Kaiyu Zhang (198799)

“…Concerning National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) total score, α-RBs+ moxibustion+ auricular point sticking was most likely to be optimal treatment, the therapy ranking second was α-RBs+ needling, and the therapy ranking third was α-RBs+ moxibustion. …”

General overview of the total model. by Xueliang Guo (4797057)

DataSheet1_The LAC Score Indicates Significant Fibrosis in Patients With Chronic Drug-Induced Liver Injury: A Large Biopsy-Based Study.docx by Zhong-Bin Li (11288061)

“…This study proved that the LAC score can contribute to the accurate assessment of high-risk disease progression and the establishment of optimal treatment strategies for patients with chronic DILI.…”

Table 1_Epilepsy-associated CHD2 missense variants and optimization strategies for genetic diagnosis: a comparative analysis of algorithms.docx by Yu-Jie Gu (20963948)

Image 1_Epilepsy-associated CHD2 missense variants and optimization strategies for genetic diagnosis: a comparative analysis of algorithms.tif by Yu-Jie Gu (20963948)

Table_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.xlsx by Xinping Lin (1591438)

“…Finally, rapid-DAMS (R-DAMS) was constructed for a more urgent situation based on DAMS.</p><p>Results: A total of 1,905 mild stroke patients were enrolled in this study, and patients with PSD accounted for 23.4% (447). …”

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML by Ayush Garg (21090944)

“…The important findings of our studies are as follows: (i) there is no effect of threshold optimization on ranking metrics such as AUC and AUPR, but AUC and AUPR get affected by class-weighting and SMOTTomek; (ii) for ML methods RF and SVM, significant percentage improvement up to 375, 33.33, and 450 over all the data sets can be achieved, respectively, for F1 score, MCC, and balanced accuracy, which are suitable for performance evaluation of imbalanced data sets; (iii) for AutoML libraries AutoGluon-Tabular and H2O AutoML, significant percentage improvement up to 383.33, 37.25, and 533.33 over all the data sets can be achieved, respectively, for F1 score, MCC, and balanced accuracy; (iv) the general pattern of percentage improvement in balanced accuracy is that the percentage improvement increases when the class ratio is systematically decreased from 0.5 to 0.1; in the case of F1 score and MCC, maximum improvement is achieved at the class ratio of 0.3; (v) for both ML and AutoML with balancing, it is observed that any individual class-balancing technique does not outperform all other methods on a significantly higher number of data sets based on F1 score; (vi) the three external balancing techniques combined outperformed the internal balancing methods of the ML and AutoML; (vii) AutoML tools perform as good as the ML models and in some cases perform even better for handling imbalanced classification when applied with imbalance handling techniques. …”

Data_Sheet_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.docx by Xinping Lin (1591438)

“…Finally, rapid-DAMS (R-DAMS) was constructed for a more urgent situation based on DAMS.</p><p>Results: A total of 1,905 mild stroke patients were enrolled in this study, and patients with PSD accounted for 23.4% (447). …”