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A scoring algorithm for the Early Prediction of Academic Risk in STEM Courses

algorithmS 2025年第4期18卷 177-177页

作者： Poturic, Vanja Cotic Candrlic, Sanja Drazic, Ivan Univ Rijeka Fac Informat & Digital Technol Rijeka 51000 Croatia Univ Rijeka Fac Engn Rijeka 51000 Croatia

Educational data mining (EDM) and learning analytics (LA) are widely applied to predict student performance, particularly in determining academic success or failure. This study presents the development of a scoring algorithm for the early identification of students at risk of failing science, technology, engineering, and mathematics (STEM) courses. The proposed approach follows a structured process: First, educational data are collected, processed, and statistically analyzed. Next, numerical variables are transformed into dichotomous predictors, and their relevance is assessed using Cram & eacute;r's V measure to quantify their association with course outcomes. The final step involves constructing a scoring system that dynamically evaluates student performance over 15 weeks of instruction. Prospective validation of the model demonstrated excellent predictive performance (accuracy = 0.93, sensitivity = 0.95, specificity = 0.92), confirming its effectiveness in early risk detection. The resulting scoring algorithm is distinguished by its methodological simplicity, ease of implementation, and adaptability to different educational settings, making it a practical tool for timely interventions.

关键词： educational data mining learning analytics academic risk prediction scoring algorithm Cram & eacute r's V early intervention

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scoring algorithm-Based Genomic Testing in Dystonia: A Prospective Validation Study

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MOVEMENT DISORDERS 2021年第8期36卷 1959-1964页

作者： Zech, Michael Jech, Robert Boesch, Sylvia Skorvanek, Matej Necpal, Jan Svantnerova, Jana Wagner, Matias Sadr-Nabavi, Ariane Distelmaier, Felix Krenn, Martin Serranova, Tereza Rektorova, Irena Havrankova, Petra Mosejova, Alexandra Prihodova, Iva Sarlakova, Jana Kulcsarova, Kristina Ulmanova, Olga Bechyne, Karel Ostrozovicova, Miriam Han, Vladimir Ventosa, Joaquim Ribeiro Brunet, Theresa Berutti, Riccardo Shariati, Mohammad Shoeibi, Ali Schneider, Susanne A. Kuster, Alice Baumann, Matthias Weise, David Wilbert, Friederike Janzarik, Wibke G. Eckenweiler, Matthias Mall, Volker Haslinger, Bernhard Berweck, Steffen Winkelmann, Juliane Oexle, Konrad Helmholtz Zentrum Munchen Inst Neurogen Munich Germany Tech Univ Munich Inst Human Genet Munich Germany Charles Univ Prague Dept Neurol Fac Med 1 Prague Czech Republic Gen Univ Hosp Prague Prague Czech Republic Med Univ Innsbruck Dept Neurol Innsbruck Austria Safarik Univ Dept Neurol Kosice Slovakia Univ Hosp L Pasteur Dept Neurol Kosice Slovakia Zvolen Hosp Dept Neurol Zvolen Slovakia Comenius Univ Univ Hosp Bratislava Fac Med Dept Neurol 2 Bratislava Slovakia Mashhad Univ Med Sci Fac Med Dept Med Genet Mashhad Razavi Khorasan Iran Mashhad Univ Med Sci Fac Med Qaem Med Ctr Dept Neurol Mashhad Razavi Khorasan Iran Acad Ctr Educ Culture & Res ACECR Khorasan Razavi Mashhad Razavi Khorasan Iran Heinrich Heine Univ Univ Childrens Hosp Med Fac Dept Gen Pediat Neonatol & Pediat Cardiol Dusseldorf Germany Med Univ Vienna Dept Neurol Vienna Austria Masaryk Univ Dept Neurol 1 Fac Med St Annes Univ Hosp Brno Czech Republic Masaryk Univ CEITEC Brno Czech Republic Univ Hosp Dept Neurol Hradec Kralove Czech Republic Hosp Pisek Pisek Czech Republic Ludwig Maximilians Univ Munchen Dept Neurol Munich Germany Univ Hosp Nantes Pediat Intens Care Unit Inborn Errors Metab Nantes France Med Univ Innsbruck Dept Pediat Innsbruck Austria Asklepios Fachklinikum Stadtroda Klin Neurol Stadtroda Germany Univ Freiburg Univ Med Ctr Fac Med Dept Neuropediat & Muscle Disorders Freiburg Germany Tech Univ Munich Lehrstuhl Sozialpadiatrie Munich Germany Kbo Kinderzentrum Munchen Munich Germany Tech Univ Munich Klinikum Rechts Isar Klin & Poliklin Neurol Munich Germany Ludwig Maximilian Univ Munich Munich Germany Schoen Klin Vogtareuth Hosp Neuropediat & Neurol Rehabil Ctr Epilepsy Children & Adolescents Vogtareuth Germany Tech Univ Munich Lehrstuhl Neurogenet Munich Germany Munich Cluster Syst Neurol SyNergy Munich Germany

Background Despite the established value of genomic testing strategies, practice guidelines for their use do not exist in many indications. Objectives We sought to validate a recently introduced scoring algorithm for dystonia, predicting the diagnostic utility of whole-exome sequencing (WES) based on individual phenotypic aspects (age-at-onset, body distribution, presenting comorbidity). Methods We prospectively enrolled a set of 209 dystonia-affected families and obtained summary scores (0-5 points) according to the algorithm. Singleton (N = 146), duo (N = 11), and trio (N = 52) WES data were generated to identify genetic diagnoses. Results Diagnostic yield was highest (51%) among individuals with a summary score of 5, corresponding to a manifestation of early-onset segmental or generalized dystonia with coexisting non-movement disorder-related neurological symptoms. Sensitivity and specificity at the previously suggested threshold for implementation of WES (3 points) was 96% and 52%, with area under the curve of 0.81. Conclusions The algorithm is a useful predictive tool and could be integrated into dystonia routine diagnostic protocols. (c) 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society

关键词： exome sequencing diagnostic yield dystonia prediction scoring algorithm rare disease

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Clinical scoring algorithm for the prescription opioid misuse and abuse questionnaire (POMAQ)

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CURRENT MEDICAL RESEARCH AND OPINION 2022年第6期38卷 971-980页

作者： Coyne, Karin S. Schnoll, Sidney H. Butler, Stephen F. Barsdorf, Alexandra, I Currie, Brooke M. Maziere, Jean-Yves Pierson, Renee F. Porter, Leslie N. Franks, Capt Michael J., Jr. Farrar, John T. Evidera Patient Ctr Res Bethesda MD USA Pinney Associates Inc Pharmaceut Risk Management Bethesda MD USA Inflexxion Inc Irvine CA USA Pfizer Inc New York NY USA Evidera 7101 Wisconsin AveSuite 1400 Bethesda MD 20814 USA Astellas Pharma US Inc Med Safety Northbrook IL USA Janssen Inc Global Patient Reported Outcomes Janssen Pharmaceut Co Johnson & Johnson Raritan NJ USA Hlth ResearchTx Real World Clin Res Trevose PA USA Naval Med Ctr Portsmouth VA USA Univ Penn Ctr Clin Epidemiol & Biostat Philadelphia PA 19104 USA SF Butler Consulting LLC Punta Gorda FL USA Clin Outcome Solut Chicago IL USA GlaxoSmithKline Collegeville PA USA

Objective The Prescription Opioid Misuse and Abuse Questionnaire (POMAQ) was developed to identify prescription opioid misuse and abuse among patients with chronic pain. A clinical scoring algorithm was developed and refined to align with the patient experience. Methods This study utilized data from the POMAQ validation study (3033-4, NCT02660606) conducted on a sample of patients with chronic pain living in the United States. The study was carried out in two phases. Two purposefully enriched patient samples, one for each phase, were created based on patient responses to select POMAQ items and the availability of urine and hair samples. Two clinical experts (SHS, SFB) reviewed patient data to classify prescription opioid use behavior. Classification differences were adjudicated by a third clinical expert (JTF). Comparisons were made between the final clinical classification determined by the experts and the proposed classification based on the POMAQ algorithm. Results Sixty patients were included in Phase I (only POMAQ data) and 52 in Phase II (including POMAQ and ancillary sources [e.g. electronic medical records, urine toxicity screen]). Refinements were made to the POMAQ scoring algorithm following discussions with clinical experts to ensure it was clinically relevant. For both phases, classifications were reviewed and discussed to achieve maximal concordance of classifications across experts. The proposed scoring algorithm was then modified to maximize agreement with the expert interpretation of clinically relevant patient experiences. Conclusion The clinical scoring algorithm for the POMAQ was developed and refined to reflect clinically relevant patient behaviors identified by expert review. Future testing is needed to determine the sensitivity and specificity of this measure.

关键词： scoring algorithm misuse abuse chronic pain opioid patient-reported outcome

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A Linear scoring algorithm for Shredded Paper Reconstruction 11

A Linear Scoring Algorithm for Shredded Paper Reconstruction

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2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)

作者： Phienthrakul, Tanasanee Santitewagun, Tewan Hnoohom, Narit Mahidol Univ Fac Engn Dept Comp Engn Image Informat & Intelligence Lab I3 Lab Nakhon Pathom Thailand

ISBN: (纸本)9781467397216

This paper proposes a method of shredded paper reconstruction using a scoring algorithm. This method consists of four modules, i. e., preprocessing, scoring, searching, and reconstructing. The scoring algorithm is created to predict the location of the next black pixel using the concept of linear regression and linear combination. Three black pixels from three consecutive columns are considered to predict the position of the next black pixel. The experimental results show that the proposed method yields the better performance over directly comparing the edges of two shreds when the suitable threshold is used in the preprocessing step.

关键词： shredded paper image reconstruction scoring algorithm linear regression linear combination

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Statistical scoring algorithm for Learning and Study Skills

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Procedia - Social and Behavioral Sciences 2012年 55卷 882-886页

作者： Aytac Gogus Gurdal Ertek Center for Individual and Academic Development Sabancı University Tuzla Istanbul 34956 Turkey Faculty of Engineering and Natural Sciences Sabancı University Tuzla Istanbul 34956 Turkey

This study examines the study skills and the learning styles of university students by using scoring method. The study investigates whether the study skills can be summarized in a single universal score that measures how hard a student works. The sample consists of 418 undergraduate students of an international university. The presented scoring was method adapted from the domain of risk management. The proposed method computes an overall score that represents the study skills, using a linear weighted summation scheme. From among 50 questions regarding to learning and study skills, the 30 highest weighted questions are suggested to be used in the future studies as a learning and study skills inventor. The proposed scoring method and study yield results and insights that can guide educators regarding how they can improve their students’ study skills. The main point drawn from this study is that the students greatly value opportunities for interaction with instructors and peers, cooperative learning and active engagement in lectures.

关键词： Study skills Study habits Learning University students scoring algorithm

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Risk assessment of preterm birth through identification and stratification of pregnancies using a real-time scoring algorithm

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SAGE OPEN MEDICINE 2021年第9期9卷 2050312120986729页

作者： Shields, Lisa B. E. Weymouth, Clayton Bramer, Kevin L. Robinson, Scott McGee, Donna Richards, Lori Ogle, Corey Shields, Christopher B. Norton Healthcare Norton Neurosci Inst 210 East Gray StSuite 1102 Louisville KY 40202 USA Lucina Hlth Inc Louisville KY USA

Introduction: Preterm birth poses a significant challenge. This study evaluated a real-time scoring algorithm to identify and stratify pregnancies to indicate preterm birth. Methods: All claims data of pregnant women were reviewed between 1 January 2014 and 31 October 2018 in Kentucky. Results: A total of 29,166 unique women who were matched to a live newborn were documented, with the pregnancy identified during the first trimester in 54.1% of women. Negative predictive values, sensitivity, and positive likelihood ratios increased from the first to third trimesters as pregnant women who were matched to a live newborn had more visits with their physicians. The area under the receiving-operating characteristics curve on test data classifying preterm birth was 0.59 for pregnancies identified during the first trimester, 0.62 for pregnancies identified in the second trimester, and 0.73 for pregnancies identified in the third trimester. Conclusions: This study presents a real-time scoring algorithm of indicating preterm birth in the first trimester of gestation which permits stratification of pregnancies to provide more efficient early care management.

关键词： Obstetrics pregnancy high-risk birth preterm birth scoring algorithm

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Performance comparison of multiple scoring algorithms: A study of automatic scoring of English text

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INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS 2024年第1期18卷 397-406页

作者： Hu, Lingling Zhengzhou Normal Univ Zhengzhou Henan Peoples R China

Objective:In order to save teachers' correcting time, improve the accuracy and efficiency of English composition ***: This paper briefly introduces the algorithm of deep sentence smoothness and text semantic matching based on graph neural network, and then designs an automatic scoring algorithm for English text. Result: The experimental data was collected from 12,000 essays written by international students in the United States in the Pratt & Whitney Foundation's Automated Student Value Assessment Project (ASAP), and these data were graded through a comparative experiment,Through comparative tests, the automatic scoring algorithm designed in this paper can achieve better scoring results and better handle automatic essay scoring problems. Among all the experimental mean values of evaluation methods, the experimental mean value of the algorithm designed in this paper is 0.790, the smoothness algorithm is 0.768, and the text matching vector is 0.759. The experimental mean values of the other two traditional automatic scoring algorithms are 0.710 and 0.712 respectively, and the results are lower than the algorithm designed in this paper. Conclusion: According to the experimental results, it can be concluded that good feature selection can give good scoring performance to the algorithm and cope with the problem of automatic scoring. At the same time, it also confirms the feasibility of the algorithm designed in this paper, which can be effectively applied in practical English composition scoring.

关键词： English composition automatic scoring scoring algorithm

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Actigraphy-based sleep estimation in adolescents and adults: a comparison with polysomnography using two scoring algorithms

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NATURE AND SCIENCE OF SLEEP 2018年 10卷 13-20页

作者： Quante, Mirja Kaplan, Emily R. Cailler, Michael Rueschman, Michael Wang, Rui Weng, Jia Taveras, Elsie M. Redline, Susan Univ Tubingen Dept Neonatol Calwerstr 7 D-72076 Tubingen Germany Brigham & Womens Hosp Dept Med Div Sleep & Circadian Disorders 75 Francis St Boston MA 02115 USA Brigham & Womens Hosp Dept Neurol Div Sleep & Circadian Disorders 75 Francis St Boston MA 02115 USA Harvard Med Sch Boston MA USA Harvard TH Chan Sch Publ Hlth Dept Biostat Boston MA USA Harvard Med Sch Dept Populat Med Boston MA USA Harvard Pilgrim Hlth Care Inst Boston MA USA MassGen Hosp Children Div Gen Acad Pediat Dept Pediat Boston MA USA Beth Israel Deaconess Med Ctr Dept Med Boston MA 02215 USA

Objectives: Actigraphy is widely used to estimate sleep-wake time, despite limited information regarding the comparability of different devices and algorithms. We compared estimates of sleep-wake times determined by two wrist actigraphs (GT3X+ versus Actiwatch Spectrum [AWS]) to in-home polysomnography (PSG), using two algorithms (Sadeh and Cole-Kripke) for the GT3X+ recordings. Subjects and methods: Participants included a sample of 35 healthy volunteers (13 school children and 22 adults, 46% male) from Boston, MA, USA. Twenty-two adults wore the GT3X+ and AWS simultaneously for at least five consecutive days and nights. In addition, actigraphy and PSG were concurrently measured in 12 of these adults and another 13 children over a single night. We used intraclass correlation coefficients (ICCs), epoch-by-epoch comparisons, paired t-tests, and Bland-Altman plots to determine the level of agreement between actigraphy and PSG, and differences between devices and algorithms. Results: Each actigraph showed comparable accuracy (0.81-0.86) for sleep-wake estimation compared to PSG. When analyzing data from the GT3X+, the Cole-Kripke algorithm was more sensitive (0.88-0.96) to detect sleep, but less specific (0.35-0.64) to detect wake than the Sadeh algorithm (sensitivity: 0.82-0.91, specificity: 0.47-0.68). Total sleep time measured using the GT3X+ with both algorithms was similar to that obtained by PSG (ICC=0.64-0.88). In contrast, agreement between the GT3X+ and PSG wake after sleep onset was poor (ICC=0.00-0.10). In adults, the GT3X+ using the Cole-Kripke algorithm provided data comparable to the AWS (mean bias=3.7 +/- 19.7 minutes for total sleep time and 8.0 +/- 14.2 minutes for wake after sleep onset). Conclusion: The two actigraphs provided comparable and accurate data compared to PSG, although both poorly identified wake episodes (i.e., had low specificity). Use of actigraphy scoring algorithm influenced the mean bias and level of agreement in sleep-wake times es

关键词： validation actigraphy polysomnography scoring algorithm

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Between-country heterogeneity in EQ-5D-3L scoring algorithms: how much is due to differences in health state selection?

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EUROPEAN JOURNAL OF HEALTH ECONOMICS 2015年第8期16卷 847-855页

作者： Pullenayegum, Eleanor M. Perampaladas, Kuhan Gaebel, Kathryn Doble, Brett Xie, Feng Hosp Sick Children Child Hlth Evaluat Sci Toronto ON M5G 1X8 Canada McMaster Univ Dept Clin Epidemiol & Biostat Hamilton ON Canada Monash Univ Fac Business & Econ Ctr Hlth Econ Clayton Vic Australia

EQ-5D-3L scoring algorithms vary amongst countries, not only in the values of regression coefficients but also in the independent variables included in the regression model (hereafter referred to as model specification). It is unclear how much of this variation is due to differences in health state selection, the relative frequencies with which health states were valued, and model diagnostics, rather than to genuine differences in population preferences. Using aggregate data from a recent review, we noted all model specifications that were used. For each country the country's own model was re-fitted, as were all other model specifications. This was done twice: once using all valued health states for each country, and again using a common set of 17 health states for all countries. Goodness of fit was assessed using the following model diagnostics: mean absolute error (MAE), mean squared error (MSE) and rho (the Pearson correlation coefficient between predicted and observed mean utilities), both with and without leave-one-out cross-validation. Thirteen countries contributed data. Even when using a common set of health states, the preferred model varied across countries. However, choice of health states did impact the preferred model specification: when using cross-validation, the preferred specification changed in five of ten countries when moving from 17 health states to all valued health states. The relative frequency with which health states were valued had little impact on the preferred model. Variation in choices of health states to value is responsible for some, but not all, of the observed heterogeneity in model specification. Relative frequency of health state valuation and choice of model diagnostic has a limited impact on model preference, however, use of cross-validation has a substantial impact. The use of cross-validation, implemented through omitting health states rather than respondents, is recommended as one approach to assessing model fit.

关键词： Health utility EQ-5D scoring algorithm Heterogeneity

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Criteria for the Evaluation of Automated Speech-Recognition scoring algorithms

ELEKTROTEHNISKI VESTNIK-ELECTROCHEMICAL REVIEW

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ELEKTROTEHNISKI VESTNIK-ELECTROCHEMICAL REVIEW 2008年第4期75卷 229-234页

作者： Dobrisek, Simon Univ Ljubljana Fac Elect Engn Trzaska 25 Ljubljana 1000 Slovenia

Variations of the basic string-alignment algorithm are commonly used for the detection and classification of speech-recognition errors. In this procedure, reference and system-output hypothesis speech transcriptions are first aligned using the string-alignment algorithm that is based on primitive edit operations. The edit operations needed to transform one transcription into the other are then tallied as speech-recognition errors. The algorithms normally detect approximately the same total number of errors;however, they can produce different error classifications. This paper investigates these differences and several criterion functions that can be used for the comparison and evaluation of the algorithms for the detection and classification of speech-recognition errors. The proposed criterion functions were used for the experimental evaluation of the standard algorithms that are implemented as part of the CUED HTK and the NIST SCTK, and were used for the detection and classification of phone-recognition errors from the TIMIT speech database.

关键词： speech recognition scoring algorithm error classification classification agreement confusion matrix

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