Applying Machine Learning to Develop Lane Control Principles for Mixed Traffic

The mixed traffic environment often has high accident rates. Therefore, many motorcycle-related traffic improvements or control methods are employed in countries with mixed traffic, including slow-traffic lanes, motorcycle two-stage left turn areas, and motorcycle waiting zones. In Taiwan, motorcycles can ride in only the two outermost lanes, including the curb lane and a mixed traffic lane. This study analyzed the new motorcycle-riding space control policy on 27 major arterial roads containing 248 road segments in Taipei by analyzing before-and-after accident data from the years 2012–2018. In this study, the equivalent-property-damage-only (EPDO) method was used to evaluate the severity of crashes before and after the cancelation of the third lane prohibition of motorcycles (TLPM) policy. After EPDO analysis, the random forest analysis method was used to screen the crucial factors in accidents for specific road segments. Finally, a classification and regression tree (CART) was created to predict the accident improvement effects of the road segments with discontinued TLPM in different situations. Furthermore, to provide practical applications, this study integrated the CART results and the needs of traffic authorities to determine four rules for canceling TLPM. In the future, on the accident-prone road segment with TLPM, the inspection of the four rules can provide the authority to decide whether to cancel TLPM to improve the accident or not.

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Predicting the Recurrence of Child Maltreatment: A Classification and Regression Tree Analysis

PsycEXTRA Dataset ◽

10.1037/e517322011-501 ◽

2007 ◽

Author(s):

Eve Sledjeski ◽

Lisa Dierker ◽

Rebecca Brigham ◽

Eileen Breslin

Keyword(s):

Child Maltreatment ◽

Regression Tree ◽

Classification And Regression Tree ◽

Tree Analysis ◽

Regression Tree Analysis ◽

Classification And Regression

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Determining late predictors of outcome for acetaminophen- induced acute liver failure using classification and regression tree modeling analysis

Critical Care ◽

10.1186/cc13389 ◽

2014 ◽

Vol 18 (Suppl 1) ◽

pp. P199

Author(s):

C Karvellas ◽

J Speiser ◽

W Lee

Keyword(s):

Liver Failure ◽

Acute Liver Failure ◽

Regression Tree ◽

Classification And Regression Tree ◽

Predictors Of Outcome ◽

Modeling Analysis ◽

Tree Modeling ◽

Classification And Regression ◽

Regression Tree Modeling

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8 Developing a casemix classification for specialist palliative care: a multi-centre cohort study to develop a patient-specific prediction model for the cost of specialist palliative care using classification and regression tree analysis

10.1136/spcare-2021-pcc.8 ◽

2021 ◽

Author(s):

Fliss EM Murtagh ◽

Alice Firth ◽

Ping Guo ◽

Ka Man Yip ◽

Christina Ramsenthaler ◽

...

Keyword(s):

Palliative Care ◽

Regression Tree ◽

Classification And Regression Tree ◽

Patient Specific ◽

Specialist Palliative Care ◽

Tree Analysis ◽

Regression Tree Analysis ◽

Specific Prediction ◽

Classification And Regression ◽

The Cost

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GCS-Pupil Score Has a Stronger Association with Mortality and Poor Functional Outcome than GCS Alone in Pediatric Severe Traumatic Brain Injury

Pediatric Neurosurgery ◽

10.1159/000517330 ◽

2021 ◽

pp. 1-8

Author(s):

Binod Balakrishnan ◽

Heather VanDongen-Trimmer ◽

Irene Kim ◽

Sheila J. Hanson ◽

Liyun Zhang ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Functional Outcome ◽

Cerebral Performance Category ◽

Regression Tree ◽

Classification And Regression Tree ◽

Continuous Variables ◽

Poor Functional Outcome ◽

Severity Scores ◽

Pupil Reactivity

Background: The Glasgow Coma Scale (GCS), used to classify the severity of traumatic brain injury (TBI), is associated with mortality and functional outcomes. However, GCS can be affected by sedation and neuromuscular blockade. GCS-Pupil (GCS-P) score, calculated as GCS minus Pupil Reactivity Score (PRS), was shown to better predict outcomes in a retrospective cohort of adult TBI patients. We evaluated the applicability of GCS-P to a large retrospective pediatric severe TBI (sTBI) cohort. Methods: Admissions to pediatric intensive care units in the Virtual Pediatric Systems (VPS, LLC) database from 2010 to 2015 with sTBI were included. We collected GCS, PRS (number of nonreactive pupils), cardiac arrest, abusive head trauma status, illness severity scores, pediatric cerebral performance category (PCPC) score, and mortality. GCS-P was calculated as GCS minus PRS. χ2 or Fisher’s exact test and Mann-Whitney U test compared categorical and continuous variables, respectively. Classification and regression tree analysis identified thresholds of GCS-P and GCS along with other independent factors which were further examined using multivariable regression analysis to identify factors independently associated with mortality and unfavorable PCPC at PICU discharge. Results: Among the 2,682 patients included in the study, mortality was 23%, increasing from 4.7% for PRS = 0 to 80% for PRS = 2. GCS-P identified more severely injured patients with GCS-P scores 1 and 2 who had worse outcomes. GCS-P ≤ 2 had higher odds for mortality, OR = 68.4 (95% CI = 50.6–92.4) and unfavorable PCPC, OR = 17.3 (8.1, 37.0) compared to GCS ≤ 5. GCS-P ≤ 2 also had higher specificity and positive predictive value for both mortality and unfavorable PCPC compared to GCS ≤ 5. Conclusions: GCS-P, by incorporating pupil reactivity to GCS scoring, is more strongly associated with mortality and poor functional outcome at PICU discharge in children with sTBI.

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Edible Insects: Preliminary Study about Perceptions, Attitudes, and Knowledge on a Sample of Portuguese Citizens

Foods ◽

10.3390/foods10040709 ◽

2021 ◽

Vol 10 (4) ◽

pp. 709

Author(s):

Sofia G. Florença ◽

Paula M. R. Correia ◽

Cristina A. Costa ◽

Raquel P. F. Guiné

Keyword(s):

Nutritive Value ◽

Meat Products ◽

Regression Tree ◽

Good Alternative ◽

Classification And Regression Tree ◽

Categorical Variables ◽

Final Conclusion ◽

Edible Insects ◽

Chi Square ◽

Alternative Sources

This study investigated the knowledge, attitudes, consumption habits, and degree of acceptability of edible insects (EI) or derived products among Portuguese consumers. This work consisted of a questionnaire survey, undertaken on a sample of 213 participants. For the treatment of data, basic descriptive statistics were used, complemented with chi-square tests to assess some associations between categorical variables. Moreover, a tree classification analysis was carried out using a classification and regression tree (CRT) algorithm with cross-validation. The results indicated that people tend to have correct perceptions about the sustainability issues associated with the use of insects as alternative sources of protein; however, the level of knowledge and overall perception about their nutritive value is low. Regarding the consumption of EI, it was found that only a small part of the participants had already eaten them, doing it mostly abroad, by self-initiative, in a restaurant or at a party or event. Additionally, it was found that the reluctance to consume insects is higher if they are whole, but when they are transformed into ingredients used in food formulations, the level of acceptance increases. Furthermore, men have shown to have a better perception about EI, be more informed about sustainability, and have a higher level of acceptability when compared to women. As a final conclusion, it was observed that the Portuguese still show some resistance to adhere to the use of insects as replacements for meat products, but the market of insect based products can be a good alternative to overpass the neophobia associated with this type of food.

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Validation and verification of predictive salivary biomarkers for oral health

Scientific Reports ◽

10.1038/s41598-021-85120-w ◽

2021 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Nagihan Bostanci ◽

Konstantinos Mitsakakis ◽

Beral Afacan ◽

Kai Bao ◽

Benita Johannsen ◽

...

Keyword(s):

Oral Health ◽

Predictive Accuracy ◽

Statistical Tests ◽

Area Under The Curve ◽

Regression Tree ◽

High Sensitivity ◽

Oral Health Status ◽

Classification And Regression Tree ◽

Cart Analysis ◽

Salivary Biomarkers

AbstractOral health is important not only due to the diseases emerging in the oral cavity but also due to the direct relation to systemic health. Thus, early and accurate characterization of the oral health status is of utmost importance. There are several salivary biomarkers as candidates for gingivitis and periodontitis, which are major oral health threats, affecting the gums. These need to be verified and validated for their potential use as differentiators of health, gingivitis and periodontitis status, before they are translated to chair-side for diagnostics and personalized monitoring. We aimed to measure 10 candidates using high sensitivity ELISAs in a well-controlled cohort of 127 individuals from three groups: periodontitis (60), gingivitis (31) and healthy (36). The statistical approaches included univariate statistical tests, receiver operating characteristic curves (ROC) with the corresponding Area Under the Curve (AUC) and Classification and Regression Tree (CART) analysis. The main outcomes were that the combination of multiple biomarker assays, rather than the use of single ones, can offer a predictive accuracy of > 90% for gingivitis versus health groups; and 100% for periodontitis versus health and periodontitis versus gingivitis groups. Furthermore, ratios of biomarkers MMP-8, MMP-9 and TIMP-1 were also proven to be powerful differentiating values compared to the single biomarkers.

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Implications of Lifestyle and Occupational Factors on the Risk of Breast Cancer in Shiftwork Nurses

Healthcare ◽

10.3390/healthcare9060649 ◽

2021 ◽

Vol 9 (6) ◽

pp. 649

Author(s):

Javier Fagundo-Rivera ◽

Regina Allande-Cussó ◽

Mónica Ortega-Moreno ◽

Juan Jesús García-Iglesias ◽

Adolfo Romero ◽

...

Keyword(s):

Breast Cancer ◽

Shift Work ◽

Regression Tree ◽

Night Work ◽

Circadian Disruption ◽

Classification And Regression Tree ◽

Baseline Risk ◽

Unhealthy Lifestyle ◽

Cross Sectional ◽

Occupational Factors

Shift work that involves circadian disruption has been highlighted as a likely carcinogenic factor for breast cancer in humans. Also, unhealthy lifestyle habits observed in night work nurses could be causally related to an increase in the incidence of estrogen-positive breast tumours in this population. Assessing baseline risk of breast cancer in nurses is essential. The objective of this study was to analyze the risk of breast cancer that nurses had in relation to their lifestyle and labour factors related to shift work. A cross-sectional descriptive study through a questionnaire about sociodemographic variables, self-perception of health, and working life was designed. The sample consisted of 966 nurses. The relationship between variables was tested. A binary logistic regression and a classification and regression tree were performed. The most significant labour variables in relation to the risk of breast cancer were the number of years worked (more than 16 years; p < 0.01; OR = 8.733, 95% CI = 2.811, 27.134) and the total years performing more than 3 nights per month (10 or more years; p < 0.05; OR = 2.294, 95% CI = 1.008, 5.220). Also, the nights worked throughout life (over 500; OR = 4.190, 95% CI = 2.118, 8.287) were significant in the analysis. Nurses who had or ever had breast cancer valued their self-perceived health more negatively (p < 0.001) and referred a lower quality of sleep (p < 0.001) than the non-cases nurses. The occupational factors derived from night work could have several impacts on nurses’ health and their family-work balance. Promoting healthy lifestyles, informing about shift work risks, and adjusting shift work schedules are critical methods to decrease the possible effects of circadian disruption in nurses.

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