Journal: BMC Cancer

Article Title: Response to neoadjuvant chemotherapy based on pathologic complete response in very young patients with ER-positive breast cancer: a large, multicenter, observational study

doi: 10.1186/s12885-021-08355-w

Figure Lengend Snippet: Univariate and multivariate analysis for pathologic complete response

Article Snippet: The association between clinicopathologic parameters and pCR rate within each subgroup was evaluated using the Chi-squared test and univariate Cox regression analysis.

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Overall procedures for sensor evaluation and calibration.

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Default data separation methods for the training dataset and test dataset. 20% of the training dataset is used for the validation dataset to prevent the over-fitting calibration model. A shuffled method is controlled by a fixed random seed to compare the performance between calibration algorithms.

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques: Biomarker Discovery

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Overall procedures for SMART calibration. (e.g., MLR and multilayer perceptron (MLP) model).

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Residual maps and a prevailing model map for SMART calibration. Residual map#1 from the linear model ( top left ) and residual map#2 from the nonlinear model ( bottom left ) are merged into a prevailing model map ( right ). Residuals under high humidity and low-temperature condition are indicated in red dotted circles. In this region, the linear model has higher expectations of residuals than the nonlinear model.

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Prevailing model map and prevailing model map (segmented cell). A cell ( Blue box ) is segmented by the allocated inputs, and it has means and standard deviations of calibration models and BAM. The cell offers the prevailing model and its residual for the allocated input.

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Comparison of calibration performance by input variables (short-term: 80%—training dataset, 20%—test dataset, shuffled method, 5 min. sampling interval condition).

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques: Comparison, Sampling

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Comparison of calibration performance by input variables (long-term: 80%—training dataset, 20%—test dataset, shuffled method, 5 min sampling interval condition)

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques: Comparison, Sampling

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Comparison between low-cost sensors and governmental BAM (before calibration).

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques: Comparison

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Correlation coefficient and metrics of low-cost sensor and governmental BAM (before calibration).

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Descriptive statistic summary of low-cost sensor and governmental BAM (before calibration).

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Comparison between low-cost sensors and governmental BAM (after calibration).

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques: Comparison

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Correlation coefficient and metrics of low-cost sensor and governmental BAM (after calibration).

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Descriptive statistic summary of low-cost sensor and governmental BAM (after calibration).

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Comparison of output plot between low-cost sensor and governmental BAM–SMART calibration signal (green line)/BAM signal (blue line)/raw signal (red line).

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques: Comparison

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Metric analysis of various calibration methods (sequential method, 5 min sampling interval condition).

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques: Sampling

Journal: Sensors (Basel, Switzerland)

Article Title: Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

doi: 10.3390/s20133617

Figure Lengend Snippet: Performance comparison by group & method.

Article Snippet: The most common calibration methods on PM2.5 calibration are a linear calibration accounting for two-thirds of total calibration cases according to a technical report from the Joint Research Center of the European Commission [ ] (univariate linear regression (ULR)—46%/multivariate linear regression (MLR)—22%).

Techniques: Comparison