Evaluation of polygenic prediction methodology within a reference-standardized framework. by Oliver Pain, Kylie P Glanville, Saskia P Hagenaars, Saskia Selzam, Anna E Fürtjes, Héléna A Gaspar, Jonathan R I Coleman, Kaili Rimfeld, Gerome Breen, Robert Plomin, Lasse Folkersen, Cathryn M Lewis

“…This study evaluates the predictive utility of polygenic scoring methods within a reference-standardized framework, which uses a common set of variants and reference-based estimates of linkage disequilibrium and allele frequencies to construct scores. …”
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Psychometric Evaluation of Large Language Model Embeddings for Personality Trait Prediction by Julina Maharjan, Ruoming Jin, Jianfeng Zhu, Deric Kenne

“…ObjectiveThis study evaluates LLM embeddings for personality trait prediction through four key analyses: (1) performance comparison with zero-shot methods on PANDORA Reddit data, (2) psychometric validation and correlation with LIWC (Linguistic Inquiry and Word Count) and emotion features, (3) benchmarking against traditional feature engineering approaches, and (4) assessment of model size effects (OpenAI vs BERT vs RoBERTa). …”
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The specification game: rethinking the evaluation of drug response prediction for precision oncology by Francesco Codicè, Corrado Pancotti, Cesare Rollo, Yves Moreau, Piero Fariselli, Daniele Raimondi

“…Scientific contribution In this paper we show that the commonly used evaluation strategies for DRP methods can be easily fooled by commonly occurring dataset biases, and they are therefore not able to truly measure the ability of DRP methods to generalize over drugs and cell lines (”specification gaming”). …”
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Research progress on evaluation and prediction of degradation in service performance for asphalt pavement by Ran Zhang, Pengkun Hu, Yuhui Zhong, Long Wen, Jie Ji, Long Liang

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On Evaluation and Comparison of Blast Loading Methods Used In Numerical Simulations by Vahdet Uçar, Atıl Erdik

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Multivariate Methods Based Soft Measurement for Wine Quality Evaluation by Shen Yin, Lei Liu, Xin Gao, Hamid Reza Karimi

“…By comparing the performance of the four methods, the MPLSR prediction model shows superior results than the others. …”
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Progress on Respiratory Syncytial Virus Vaccine Development and Evaluation Methods by Lie Deng, Hongjie Cao, Guichang Li, Kaiwen Zhou, Zihan Fu, Jiaying Zhong, Zhongfang Wang, Xiaoyun Yang

“…This review comprehensively explores the progress in RSV vaccine development, the immune evaluation methods, and immunological surrogate. The RSV fusion (F) protein, a primary target for vaccine development, has been engineered in prefusion conformation to elicit potent neutralizing antibodies, while the attachment (G) glycoprotein and other immunogens are also being explored to broaden immune responses. …”
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Machine learning-based prediction of LDL cholesterol: performance evaluation and validation by Jing-Bi Meng, Zai-Jian An, Chun-Shan Jiang

“…Predictive performance was evaluated using R-squared (R2), mean squared error (MSE), and Pearson correlation coefficient (PCC) against measured LDL-C values. …”
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Evaluation of the Reliability of Thermogravimetric Indices for Predicting Coal Performance in Utility Systems by Krzysztof M. Czajka

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Evaluating of spatial interpolation techniques for accurate air quality prediction: An overview by Abdulkareem Sarah K., Alhadithi Mufid, Amer Wadhah

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Evaluating the Role of Genetic Markers in Predicting Oral Leukoplakia Malignancy Transformation by Ahtesham Ahmad Qurishi, Mohamed S. Mohamed Morsy, Abeer M. Atout, Shahad Essa Abzoah, Mohammed Hasan M. Wadani, Nawaf Hussain Ali Ghazwani, Shatha Ahmad Mohammad Jafari

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Evaluation of Complete Blood Count Parameters to Predict Abnormal Uterine Bleeding by Defne Ay Tuncel, Can Acıpayam

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Evaluation of Mannheim Peritonitis Index Score for predicting the outcomes in patients with peritonitis by Raiba Deshmukh, Avishkar K Barase, Rutik P Gandhi, Aniket Chaware, Avinash Dhumal

“…Conclusion: MPI score is a simple, effective, and useful system for predicting post-operative mortality and morbidity in cases of peritonitis. …”
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Risk prediction and effect evaluation of complicated appendicitis based on XGBoost modeling by Sunmeng Chen, Jianfu Xia, Beibei Xu, Yi Huang, Miaomiao Teng, Juyi Pan

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Review and Evaluation of Slip-ratio-based Void Fraction Prediction Models by HE Wen, HAN Jinyu, ZHAO Chenru, LI Yanlin, BO Hanliang

“…There are many methods for the prediction of void fraction, among which the slip-ratio-based method is the most popular one. …”

Construction and evaluation of an aspirin resistance risk prediction model for ischemic stroke by Tianyu Ma, Xue Wang, Yan Song, Junying Liu, Min Zhang

“…The AR risk assessment criteria for ischemic stroke were established based on the β values ​​of each risk factor and its variable types in the prediction model. The two evaluation criteria were compared and analyzed to determine the best criteria. …”
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Evaluation of PEscore performance in predicting platelet transfusion efficacy in hematological patients by LI Jun, WANG Lan, XIE Yihua, CHEN Ziqi, ZHAO Gang

“…[Objective] To evaluate the performance of platelet efficacy score (PEscore) in predicting platelet transfusion efficacy in hematological patients. …”
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Comprehensive Evaluation of Frailty and Sarcopenia Markers to Predict Survival in Glioblastoma Patients by Chao Yang, Chao Ma, Cheng‐Shi Xu, Si‐Rui Li, Chen Li, Ze‐Fen Wang, Zhi‐Qiang Li

“…Methods Between January 2016 and September 2022, we enrolled 309 adult GBM patients. …”
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Gravity Predictions in Data-Missing Areas Using Machine Learning Methods by Yubin Liu, Yi Zhang, Qipei Pang, Sulan Liu, Shaobo Li, Xuguo Shi, Shaofeng Bian, Yunlong Wu

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Machine Learning Methods for Predicting Cardiovascular Diseases: A Comparative Analysis by Aiym B. Temirbayeva, Arshyn Altybay

“…Logistic Regression and Random Forest were identified as the most reliable models for predicting heart disease in this dataset. Future work will explore hyperparameter tuning and ensemble methods to further enhance model performance, providing valuable insights for early diagnosis and treatment of cardiovascular diseases.…”
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