Relevant bibliographies by topics / Admission Prediction

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Admission Prediction'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Admission Prediction"

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Honwadkar, Prof K. N. "COLLEGE PREDICTION SYSTEM." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 10 (2023): 1–11. http://dx.doi.org/10.55041/ijsrem26421.

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The journey towards higher education is a pivotal chapter in a student's life, often marked by uncertainty and high stakes. In the context of engineering admissions in Maharashtra, where over 400 colleges are governed by the Directorate of Technical Education (DTE), the process can be labyrinthine. The Centralised Admission Process (CAP) involving multiple rounds further amplifies the complexity, leaving students perplexed about selecting the ideal college for their academic aspirations. The College Admission Prediction System is an innovative web application designed to address these challeng
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Shaik Naveed and K.Kumara Swamy. "Prediction of Graduation Admission." international journal of engineering technology and management sciences 9, no. 2 (2025): 628–37. https://doi.org/10.46647/ijetms.2025.v09i02.080.

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In recent years, the prediction of graduate admission has garnered significant attention due to theincreasing competitiveness and demand for higher education. This study explores the utilization ofmachine learning techniques to predict the likelihood of admission for prospective graduate students.By leveraging a dataset comprising various academic and non-academic factors, such as GREscores, undergraduate GPA, research experience, and letters of recommendation, we aim to developa predictive model that can assist both applicants and admissions committees. The primary objective of this research
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Boardman, Anthony P., Richard E. Hodgson, Martyn Lewis, and Keith Allen. "Social indicators and the prediction of psychiatric admission in different diagnostic groups." British Journal of Psychiatry 171, no. 5 (1997): 457–62. http://dx.doi.org/10.1192/bjp.171.5.457.

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BackgroundRecent findings indicate that the established association between social indicators of deprivation and psychiatric admission rates may not hold across all diagnoses.MethodAdmission rates in individuals aged 16–64 years for 71 electoral wards in North Staffordshire were calculated for six diagnostic groups using data from the Korner Episode System for 1987–1993. These were correlated with selected individual census variables, Townsend and Jarman indices. The ability of regression models to predict admission rates was tested.ResultsThe strongest correlations were found for total admiss
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Feigon, Sarah, and J. Ray Hays. "Prediction of Readmission of Psychiatric Inpatients." Psychological Reports 93, no. 3 (2003): 816–18. http://dx.doi.org/10.2466/pr0.2003.93.3.816.

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Using demographic and episode-based variables this study attempted to predict which patients would require frequent psychiatric hospitalizations. Records of 943 patients were randomly selected from 14,649 admissions and examined for a 5-yr. period following initial admission. Sex, ethnicity, and age at first admission were not significantly related to readmission. Among the demographic variables, marriage was inversely related to readmission. Involuntary commitment and a longer length of stay at the original admission were associated with a higher rate of readmission. Despite the results being
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Jawad, Baker Nawfal, Izzet Altintas, Jesper Eugen-Olsen, et al. "Prospective and External Validation of Machine Learning Models for Short- and Long-Term Mortality in Acutely Admitted Patients Using Blood Tests." Journal of Clinical Medicine 13, no. 21 (2024): 6437. http://dx.doi.org/10.3390/jcm13216437.

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Background: Predicting mortality in emergency departments (EDs) using machine learning models presents challenges, particularly in balancing simplicity with performance. This study aims to develop models that are both simple and effective for predicting short- and long-term mortality in ED patients. Our approach uses a minimal set of variables derived from one single blood sample obtained at admission. Methods: Data from three cohorts at two large Danish university hospitals were analyzed, including one retrospective and two prospective cohorts where prognostic models were applied to predict i
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Laios, Alexandros, Raissa Vanessa De Oliveira Silva, Daniel Lucas Dantas De Freitas, et al. "Machine Learning-Based Risk Prediction of Critical Care Unit Admission for Advanced Stage High Grade Serous Ovarian Cancer Patients Undergoing Cytoreductive Surgery: The Leeds-Natal Score." Journal of Clinical Medicine 11, no. 1 (2021): 87. http://dx.doi.org/10.3390/jcm11010087.

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Achieving complete surgical cytoreduction in advanced stage high grade serous ovarian cancer (HGSOC) patients warrants an availability of Critical Care Unit (CCU) beds. Machine Learning (ML) could be helpful in monitoring CCU admissions to improve standards of care. We aimed to improve the accuracy of predicting CCU admission in HGSOC patients by ML algorithms and developed an ML-based predictive score. A cohort of 291 advanced stage HGSOC patients with fully curated data was selected. Several linear and non-linear distances, and quadratic discriminant ML methods, were employed to derive predi
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Barak Corren, Yuval, Joshua Merrill, Ronald Wilkinson, Courtney Cannon, Jonathan Bickel, and Ben Y. Reis. "Predicting surgical department occupancy and patient length of stay in a paediatric hospital setting using machine learning: a pilot study." BMJ Health Care Inform 29, no. 1 (2022): e100498. http://dx.doi.org/10.1136/bmjhci-2021-100498.

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ObjectiveEarly and accurate prediction of hospital surgical-unit occupancy is critical for improving scheduling, staffing and resource planning. Previous studies on occupancy prediction have focused primarily on adult healthcare settings, we sought to develop occupancy prediction models specifically tailored to the needs and characteristics of paediatric surgical settings.Materials and methodsWe conducted a single-centre retrospective cohort study at a surgical unit in a tertiary-care paediatric hospital in Boston, Massachusetts, USA. We developed a hierarchical modelling framework for predict
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Gao, Yan, Sunku Srivatsava, Hong Choon Oh, Siang Hiong Goh, and Hoon Chin Steven Lim. "Development and Validation of a Machine Learning Model That Predicts Short Inpatient Stays Among Urgent Admissions." Emergency Care and Medicine 2, no. 1 (2025): 11. https://doi.org/10.3390/ecm2010011.

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Background/Objectives: This study aimed to explore the feasibility of predicting short stays among urgent admissions to an acute hospital in Singapore. With an increase in the average length of stay (LOS) in hospitals in recent years, accurately predicting short stays could enable hospitals to better manage inpatient demand and reduce emergency department (ED) overcrowding. Methods: This was a retrospective study of urgent admissions to Changi General Hospital, Singapore, from 1 January 2016 to 30 June 2022. To identify potential short stayers, a total of 25 features comprising demographic cha
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Raftopoulos, George, Gregory Davrazos, and Sotiris Kotsiantis. "Fair and Transparent Student Admission Prediction Using Machine Learning Models." Algorithms 17, no. 12 (2024): 572. https://doi.org/10.3390/a17120572.

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Student admission prediction is a crucial aspect of academic planning, offering insights into enrollment trends, resource allocation, and institutional growth. However, traditional methods often lack the ability to address fairness and transparency, leading to potential biases and inequities in the decision-making process. This paper explores the development and evaluation of machine learning models designed to predict student admissions while prioritizing fairness and interpretability. We employ a diverse set of algorithms, including Logistic Regression, Decision Trees, and ensemble methods,
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Khan, Nikhat. "Prediction of Student Admission using Fuzzy based Education Data Mining." International Journal of Science and Research (IJSR) 11, no. 10 (2022): 660–67. http://dx.doi.org/10.21275/sr221014151159.

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Dissertations / Theses on the topic "Admission Prediction"

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Kyei-Blankson, Lydia S. "Predictive Validity, Differential Validity, and Differential Prediction of the Subtests of the Medical College Admission Test." Ohio University / OhioLINK, 2005. http://www.ohiolink.edu/etd/view.cgi?ohiou1125524238.

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陳衍輝 and Hin-fai Gregory Chan. "Selection for admission to the undergraduate programmes of the University of Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1990. http://hub.hku.hk/bib/B29910857.

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Sandholm, Thomas. "Statistical Methods for Computational Markets : Proportional Share Market Prediction and Admission Control." Doctoral thesis, KTH, Data- och systemvetenskap, DSV, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4738.

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We design, implement and evaluate statistical methods for managing uncertainty when consuming and provisioning resources in a federated computational market. To enable efficient allocation of resources in this environment, providers need to know consumers' risk preferences, and the expected future demand. The guarantee levels to offer thus depend on techniques to forecast future usage and to accurately capture and model uncertainties. Our main contribution in this thesis is threefold; first, we evaluate a set of techniques to forecast demand in computational markets; second, we design a scalab
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Mehrvar, Hamid-Reza. "Prediction of cell loss rate and its application to connection admission control." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/NQ63991.pdf.

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Nizampuram, Pranay. "Prediction of re-admissions for critical health conditions : A Machine Learning Approach." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-10821.

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Context. Re-admission is the return hospitalization within 30 days from the date of original admission or discharge from hospital. Thecosts of the unplanned re-admissions were estimated to $25 billion per year alone in the U.S. Re-admission rate also has a huge impact onquality of care provided to the patients, cost of health care, and utilization of hospital resources and the image of the care provider. Studies indicate huge potential of savings that can be achieved with incremental performance improvements in detecting cases of preventable re-admissions. Objectives. In this study we find the
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Roberts, Charlene M. "Relationships among admission variables, professional education outcome measures, and job performance of University of Missouri physical therapy graduates /." free to MU campus, to others for purchase, 1996. http://wwwlib.umi.com/cr/mo/fullcit?p9737870.

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Wildman, Martin James. "Outcome prediction for patients with obstructive lung disease considered for admission to critical care units in England, Wales and Northern Ireland." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2005. http://researchonline.lshtm.ac.uk/682336/.

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Objective. To develop an outcome prediction score for patients with obstructive lung disease considered for admission to critical care. Design. Prospective cohort study using multivariate logistic regression for model building followed by score development and bootstrapping to adjust for over fitting. Setting. Critical care and respiratory high dependency units in England Wales and Northern Ireland. Participants. Patients aged 45 years and older with a clinical diagnosis of breathlessness, respiratory failure or change in mental status due to an exacerbation of COPD, asthma or a combination of
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Bishop, Malachy Liam. "The Predictive Validity of the Admission Criteria for the Counselor Education Program at Portland State University." PDXScholar, 1995. https://pdxscholar.library.pdx.edu/open_access_etds/4971.

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The Counselor Education Program at Portland State University currently uses five admission criteria to determine the acceptance or rejection of applicants. These criteria include letters of reference, a panel interview, a writing sample, the applicant's undergraduate GPA (UGPA), and the applicant's score on either the MAT or the GRE. Scores on these measures are adjusted and combined to create a single total score upon which admission decisions are based. The present study attempts to evaluate the validity of these admission criteria in predicting success in the Counselor Education Program at
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Huarng, Yih-Yuung. "Analysis of Relationships Between Selected Requirements for Admission to Elementary Teacher Education and Teaching Performance." Thesis, North Texas State University, 1985. https://digital.library.unt.edu/ark:/67531/metadc331280/.

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The problem of this study is concerned with the relationships between selected requirements for admission to elementary teacher education and teaching performance. The purposes of this study were (1) to investigate the relationships between teaching performance, as evaluated by a principal, and five selected admission criteria (the GPA at the time of admittance to teacher education; achievement test scores in reading, language, mathematics; and instructor appraisal of the student during the first education course); (2) to determine whether or not the five selected admission criteria used singl
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Nagatsuka, Jacqueline Myra. "The decline in the admission of underrepresented minority students to selective public institutions after the implementation of anti-affirmative action legislation." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1580936661&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Books on the topic "Admission Prediction"

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Harris, Vincent F. Analysis of differential prediction of law school performance by gender subgroups. Law School Admission Council, 2006.

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Sheldon, Zedeck, ed. Final report: Identification, development, and validation of predictors for successful lawyering. [s.n.], 2008.

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Anthony, Lisa C. Analysis of differential prediction of law school performance by racial/ethnic subgroups based on the 1996-1998 entering law school classes. Law School Admission Council, 2003.

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Duffy, Jennifer R. Analysis of differential prediction of law school performance by gender subgroups based on the 1996-1998 entering law school classes. Law School Admission Council, 2006.

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Wightman, Linda F. Beyond FYA: Analysis of the utility of LSAT scores and UGPA for predicting academic success in law school. Law School Admission Council, 2000.

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Stilwell, Lisa Anthony. Predictive validity of the LSAT: A national summary of the 1997-1998 correlation studies. Law School Admission Council, 1999.

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Rowsome, Wayne. From high school to university: An alternate method for selecting university entrants. Department of Geography, Faculty of Sciences, Carleton University, 1987.

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Dalessandro, Susan P. Predictive validity of the LSAT: A national summary of the 2003-2004 correlation studies. Law School Admission Council, 2005.

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Ontario. Ministry of Colleges and Universities. A study of the impact of OS:IS implementation on the post-secondary system in Ontario : phase IV report. Ministry of Colleges and Universities, 1989.

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Alison, Hegarty, ed. A study of the impact of OS:IS implementation on the post-secondary system in Ontario: Phase II report. Ministry of Colleges and Universities, 1987.

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Book chapters on the topic "Admission Prediction"

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Bekelaar, Jorg W. R., Jolanda J. Luime, and Renata M. de Carvalho. "Predicting Patient Care Acuity: An LSTM Approach for Days-to-day Prediction." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27815-0_28.

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AbstractIn recent years, hospitals and other care providers in the Netherlands are coping with a widespread nursing shortage and a directly related increase in nursing workload. This nursing shortage combined with the high nursing workload is associated with higher levels of burnout and reduced job satisfaction among nurses. However, not only the nurses, but also the patients are affected as an increasing nursing workload adversely affects patient safety and satisfaction. Therefore, the aim of this research is to predict the care acuity corresponding to an individual patient for the next admis
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Aberer, Karl, and Silvia Hollfelder. "Resource Prediction and Admission Control for Interactive Video." In Database Semantics. Springer US, 1999. http://dx.doi.org/10.1007/978-0-387-35561-0_4.

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Shaik, Subhani, V. Raju, T. Manohar, A. Anusha, and B. Sai Jitendra. "Admission Prediction for Higher Studies in Foreign Universities." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8628-6_9.

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Raut, Roshani, Jayant Abnave, Sushil Dikondwar, Shivani Pandita, and Atharva Marudwar. "Undergraduate College Admission Prediction System Using Decision Tree Classifier." In Micro-Electronics and Telecommunication Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9512-5_27.

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Pla, Vicent, Jose Manuel Gimenez-Guzman, Jorge Martinez-Bauset, and Vicente Casares-Giner. "Optimal Admission Control Using Handover Prediction in Mobile Cellular Networks." In Mobility Management and Quality-Of-Service for Heterogeneous Networks. River Publishers, 2022. http://dx.doi.org/10.1201/9781003338840-10.

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Grampurohit, Sneha. "Diabetes Patients Hospital Re-admission Prediction Using Machine Learning Algorithms." In Intelligent Manufacturing and Energy Sustainability. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4443-3_47.

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Bal, Sauvik, Ashish Kumar Singh, Suramya Prakash, et al. "An Intelligent Chatbot for Admission System of an Educational Institute and Prediction of User Interest in Taking Admission." In Applications of Machine Intelligence in Engineering. CRC Press, 2022. http://dx.doi.org/10.1201/9781003269793-16.

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Bhatt, Vaidik, Tulika Chakravorty, and Samyadip Chakraborty. "Re-admission Rate Prediction of Diabetes Patient: Health Analytics-based Approach." In Proceedings of International Conference on Data Science and Applications. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5120-5_56.

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Gharbi, Mohamed, Christine Verdier, Maria Di Mascolo, and Jean-Marc Babouchkine. "Early Length of Stay Prediction at Admission in Short-Stay Hospitals." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-92471-2_4.

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Trivedi, Khushbu, Jenisia Dsouza, Shivam Kumar, et al. "Admission Prediction for Universities Using Decision Tree Algorithm and Support Vector Machine." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. https://doi.org/10.1007/978-981-97-7356-5_17.

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Conference papers on the topic "Admission Prediction"

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Rani, K. Suvarchala, A. Rajini, and Kavitha Lal. "Automated Prediction Model for Graduate Admission in Foreign Universities." In 2024 Asia Pacific Conference on Innovation in Technology (APCIT). IEEE, 2024. http://dx.doi.org/10.1109/apcit62007.2024.10673535.

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H S, Suresh Kumar, Vineeth Raghavan, Harshvardhan Harivitthal Patil, Pratheeth Adiga, Pushpa C. N, and Thriveni J. "Enhancing ICU Admission Prediction for COVID-19 Patients using Decision Trees." In 2024 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT). IEEE, 2024. http://dx.doi.org/10.1109/conecct62155.2024.10677322.

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Zhang, Xiao, and Àngela Nebot. "Semi-Supervised Dual-Manifold Regularized Fuzzy Broad Learning for ICU Admission Prediction in Post-COVID Transplant Recipients." In 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2024. http://dx.doi.org/10.1109/fuzz-ieee60900.2024.10612100.

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Ma, Ji, Tiantian Liu, Wentao Li, et al. "A college entrance exam score prediction model based on improved TF-IDF and LSTM and its application in an AI admission platform." In Second International Conference on Power Electronics and Artificial Intelligence (PEAI 2025), edited by Qiang Yang, Parikshit N. Mahalle, and Xuehe Wang. SPIE, 2025. https://doi.org/10.1117/12.3066734.

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Nalam, Srujan, Mohd Aleemuddin, Yuva Teja Kadari, and Nanda Kumar M. "Advanced Graduate Admission Prediction." In 2023 IEEE 8th International Conference for Convergence in Technology (I2CT). IEEE, 2023. http://dx.doi.org/10.1109/i2ct57861.2023.10126307.

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Patel, Ananya R., Bhuvana K S, Dhanya R S, D. A. Akshay, Shridhar B. Devamane, and Tushar N. "Machine Learning Based Graduate Admission Prediction." In 2023 International Conference on Computational Intelligence for Information, Security and Communication Applications (CIISCA). IEEE, 2023. http://dx.doi.org/10.1109/ciisca59740.2023.00072.

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Huo, Zepeng, Harinath Sundararajhan, Nathan C. Hurley, Adrian Haimovich, R. Andrew Taylor, and Bobak J. Mortazavi. "Sparse Embedding for Interpretable Hospital Admission Prediction." In 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2019. http://dx.doi.org/10.1109/embc.2019.8856800.

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Li, Jiexun, Lifan Guo, and Neal Handly. "Hospital Admission Prediction Using Pre-hospital Variables." In 2009 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2009. http://dx.doi.org/10.1109/bibm.2009.45.

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Nakhjiri, Mehdi, and Peter F. Pelz. "Turbomachines Under Periodic Admission: Axiomatic Performance Prediction." In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-68398.

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In calibration tasks under engine conditions, steady-state manufacturer performance maps are applied to periodic turbocharger operation. This procedure is exposed to considerable uncertainties. In this work the axiomatic form of the energy equation as well as Euler turbomachinery equation are used to generate a general form of the respective equations which allow for periodicity. Thus, the concept of apparent speed and apparent efficiency is introduced. The latter can attain values greater than unity.
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Katti, Jayashree, Jony Agarwal, Swapnil Bharata, Swati Shinde, Saral Mane, and Vinod Biradar. "University Admission Prediction Using Google Vertex AI." In 2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR). IEEE, 2022. http://dx.doi.org/10.1109/icaitpr51569.2022.9844176.

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Reports on the topic "Admission Prediction"

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Bates Mike, Paula. Evaluation of the Admissions Process at Portland State University School of Social Work : Prediction and Performance. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.1808.

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Bishop, Malachy. The Predictive Validity of the Admission Criteria for the Counselor Education Program at Portland State University. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.6847.

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Introducing a primary care risk prediction tool did not reduce emergency admissions. National Institute for Health Research, 2018. http://dx.doi.org/10.3310/signal-000557.

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