Comparative performance of PROMIS Sleep Disturbance computerized adaptive testing algorithms and static short form in postmenopausal women by Andrew Trigg, Claudia Haberland, Huda Shalhoub, Christoph Gerlinger, Christian Seitz

“…Two CAT algorithms were tested: CAT1 (stop once standard error <0.3 or 12 items administered) and CAT2 (stop once 8 items administered). …”
Get full text

Forecasting invasive mosquito abundance in the Basque Country, Spain using machine learning techniques by Vanessa Steindorf, Hamna Mariyam K. B., Nico Stollenwerk, Aitor Cevidanes, Jesús F. Barandika, Patricia Vazquez, Ana L. García-Pérez, Maíra Aguiar

“…Forecasting models, including random forest (RF) and seasonal autoregressive integrated moving average (SARIMAX), were evaluated using root mean squared error (RMSE) and mean absolute error (MAE) metrics. …”
Get full text

The Potential of SHAP and Machine Learning for Personalized Explanations of Influencing Factors in Myopic Treatment for Children by Jun-Wei Chen, Hsin-An Chen, Tzu-Chi Liu, Tzu-En Wu, Chi-Jie Lu

“…The average age of the whole group was 10.6 ± 2.5 years old. The refractive error of spherical equivalent (SE) in myopia degree was base SE at 2.63D and end SE at 3.12D. …”
Get full text

The success of critical velocity protocol on predicting 10000 meters running performance by Barış Çabuk, Onur Demirarar, Merve Cin, Refik Çabuk, Bahtiyar Özçaldıran

“…Conclusions. Three mathematical models predicted 10000 meters of race velocity when an exhaustion interval between 2-15 minutes was used. …”
Get full text

Mixed-methods evaluation of acceptability of the District Health Information Software (DHIS2) for neglected tropical diseases program data in Cameroon by Henri C Moungui, Hugues C Nana-Djeunga, Georges B Nko’Ayissi, Aboubakary Sanou, Joseph Kamgno

“… # Results We found 81.9% (95% confidence interval, CI=0.784-0.859; standard error=0.019) of intention to use DHIS2 for NTDs program data and 18.4% (95% CI=0.130-0.289; standard error=0.041) of actual use among survey participants. …”
Get full text

Performance of Large Language Models in the Non-English Context: Qualitative Study of Models Trained on Different Languages in Chinese Medical Examinations by Zhong Yao, Liantan Duan, Shuo Xu, Lingyi Chi, Dongfang Sheng

“…All models except Llama generally had higher accuracy rates for simple questions than for complex ones. The error set of ChatGPT was similar to those of other Chinese models. …”
Get full text

A Paired Kidney Analysis of Simultaneous Heart-Kidney Transplantation and Kidney Transplantation After Heart Transplantation by Kenji Okumura, MD, Suguru Ohira, MD, PhD, Ryosuke Misawa, MD, PhD, Seigo Nishida, MD, PhD, Steven Lansman, MD, PhD, Abhay Dhand, MD

“…This resulted in lower mean graft years [SHKT (3.98 years, standard error = 0.06) vs kidney-alone (4.55 years, standard error = 0.04); P < 0.001] and an additional loss of 57 kidney graft years per 100 transplants (P < 0.01) during the study period. …”
Get full text

Exploring the Dynamics of Dietary Self-Monitoring Adherence Among Participants in a Digital Behavioral Weight Loss Program: Model Development Study by Hui Lin, Min Yang, Zhiheng Zhou, Yu Zhang, Ning Deng

“…Model performance was evaluated using mean square error, root mean square error (RMSE), and goodness of fit. …”
Get full text

RETRACTED ARTICLE: Long non-coding RNA SNHG16 reduces hydrogen peroxide-induced cell injury in PC-12 cells by up-regulating microRNA-423-5p by Haochuan Liu, Bing Chen, Qingsan Zhu

“…Artificial Cells, Nanomedicine, and Biotechnology. 47:1, 1444–1451, DOI: 10.1080/21691401.2019.1600530Since publication, the authors noticed that an inappropriate cell line was used. As this error directly impacts the reported results and conclusions the authors alerted the issue to the Editor and Publisher and all have agreed to retract the article to ensure correction of the scholarly record.We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions.The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as ‘Retracted’.…”
Get full text

Prediction of oxidation resistance of Ti-V-Cr burn resistant titanium alloy based on machine learning by Yuanzhi Sun, Guangbao Mi, Peijie Li, Liangju He

“…The coefficient of determination R 2 of the models are 0.98 and the maximum error is 6.57 and 6.40%, respectively. The importance and interpretability of the input features were analyzed. …”
Get full text

Comparison of total event analysis and first event analysis in relation to heterogeneity in cardiovascular trials by Shun-Fu Lee, Chinthanie Ramasundarahettige, Hertzel C. Gerstein, William F. McIntyre, John Eikelboom, Martin J. O’Donnell, Yueci Zhou, Shrikant I. Bangdiwala, Lehana Thabane

“…Among the total event methods, AG, PWP gap, and LWYY demonstrated better power, with AG and LWYY also achieving the smallest mean squared error (MSE). Conclusions High heterogeneity arises when a small number of patients experience a disproportionately large number of events. …”
Get full text

Prediction and optimization of robot processing technology based on neural network and genetic algorithm by Fusen WU

“…The maximum absolute relative error of the axial grinding force is 7.84%, and the correlation coefficient of the model is as high as 0.998 09, indicating significant prediction accuracy of the mpdel. …”
Get full text

Corrigendum: The accuracy and precision of CT-RSA in arthroplasty: a systematic review and meta-analysis by Sjors F van de Vusse, Nienke N de Laat, Lennard A Koster, Bart Kaptein

“…These requested changes do not alter our conclusions of the systematic review. On behalf of all authors Bart Kaptein …”
Get full text

FDI and Trade Connectivity in EU: New Evidence from a Non-Linear Panel Smooth Transition VECM by Pavlos Stamatiou, Nikolaos Dritsakis

“…Policy implications are then explored in the conclusions.…”
Get full text

Treelike process tensor contraction for automated compression of environments by Moritz Cygorek, Brendon W. Lovett, Jonathan Keeling, Erik M. Gauger

“…The drawbacks of the preselection approach are that the MPO compression is suboptimal and that it is more prone to error accumulation than sequential combination and compression. …”
Get full text

PREVALENCE AND TYPES OF AZF MICRODELETIONS IN INFERTILE MEN by ALEXEY N. Volkov, ELENA V. Tsurkan

“…Microdeletions in AZFс subregion, frequently correctable by assisted reproductive technology, were the predominant type. Conclusions. We recommend genotyping of the AZF locus to all male patients with primary infertility to exclude other causes of this disorder. …”
Get full text

Drive electrical parameters applicability evaluation to determine loads on bridge crane lifting mechanism by S. D. Ivanov, A. N. Nazarov

“…Formulas for determining the error of calculating the stator current and active power parameters and for determining the coefficient of proportionality of the load on the drive and the information parameter are given.Results. …”
Get full text

Efficiency comparison of exact and approximate algorithms for solving set covering problem by Igor S. Konovalov, Sergey S. Ostapenko, Valery G. Kobak

“…For large sets, it is recommended to use the genetic algorithm which guarantees receiving a result with a negligible error where the execution time shift is stable and predictable.…”
Get full text

Intra-Session Reliability and Predictive Value of Maximum Voluntary Isometric Contraction for Estimating One-Repetition Maximum in Older Women: A Randomised Split-Sample Study by José Aldo Hernández-Murúa, Ena Monserrat Romero-Pérez, Jorge Luis Guajardo-Cruztitla, Blas Sinahí Madrigal Olivares, Ángel Gallego-Selles, Diego González-Martín, Francisca Reyes-Merino, Nidia Sánchez-García, José Antonio de Paz

“…Although the predictive equation 1RM = [(0.932 × MVIC) − 3.852] did not yield statistically significant differences between the estimated and actual 1RM values (<i>p</i> = 0.791), it exhibited a prediction error of 13.4%. <b>Conclusions</b>: MVIC is a highly reliable measure in older women and represents a practical tool for estimating 1RM. …”
Get full text

Physiological Profile Assessment and Self-Measurement of Healthy Students through Remote Protocol during COVID-19 Lockdown by Tommaso Di Libero, Lavinia Falese, Annalisa D’Ermo, Beatrice Tosti, Stefano Corrado, Alice Iannaccone, Pierluigi Diotaiuti, Angelo Rodio

“…<b>Conclusions</b>: The findings indicate that remote fitness testing is a promising method for evaluating motor abilities. …”
Get full text