Clinical Features of Juvenile Open-angle Glaucoma by A. V. Malyshev, A. S. Apostolova, A. A. Sergienko, A. F. Teshev, G. Yu. Karapetov, M. K. Ashhamahova, B. N. Hatsukova

“…The given parameters with normal distribution were presented in the format M ± m, where M is the mean value, m is the standard error of the mean.Results. JOAG patients were younger than the control group — 30.1 ± 1.5 and 37.0 ± 1.9 years, p = 0.007, there were 58 % men versus 42 % women. …”
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Relative contribution of diet and physical activity to increased adiposity among rural to urban migrants in India: A cross-sectional study. by Sanjay Kinra, Poppy Alice Carson Mallinson, Jenny A Cresswell, Liza J Bowen, Tanica Lyngdoh, Dorairaj Prabhakaran, Kolli Srinath Reddy, Mario Vaz, Anura V Kurpad, George Davey Smith, Yoav Ben-Shlomo, Shah Ebrahim

“…<h4>Conclusions</h4>We found that increased energy intake and reduced energy expenditure contributed equally to greater adiposity among urban migrants in India. …”
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Segmentation of ADPKD Computed Tomography Images with Deep Learning Approach for Predicting Total Kidney Volume by Ting-Wen Sheng, Djeane Debora Onthoni, Pushpanjali Gupta, Tsong-Hai Lee, Prasan Kumar Sahoo

“…However, manual localization and segmentation are tedious, time-consuming tasks and are prone to human error. Specifically, there is a lack of studies that focus on CT modality variation. …”
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Incident prescriptions for common cardiovascular medications: comparison of recent versus pre-2020 medication adherence and discontinuation in three universal health care systems by Candace D. McNaughton, Peter C. Austin, Cynthia A. Jackevicius, Anna Chu, Jessalyn K. Holodinsky, Michael D. Hill, Colleen M. Norris, Mukesh Kumar, Noreen Kamal, Douglas S. Lee, Nadia Khan, Manav V. Vyas, Raed A. Joundi, Moira K. Kapral, Amy Y. X. Yu

“…For each medication class, adherence in the recent period, defined as ≥ 0.80 proportion-of-days-covered (PDC), was compared to the pre-pandemic period using modified Poisson regression with robust error variance, adjusted for patient characteristics. …”
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Evaluation of the Biolabo Turbidimetric Assay for Automated Determination of Haemoglobin A1c by Lorenza Fagnani, Simonetta De Angelis, Pierangelo Bellio, Patrizia Frascaria, Rita Tennina, Giovanni Alloggia, Francesco Gentile, Alessandra Piccirilli, Mariagrazia Perilli, Giuseppe Celenza

“…The risk assessment of diagnostic misinterpretation indicated minimal deviation from an ideal analytical system, in which the measurement uncertainty was regarded as zero. <b>Conclusions</b>: The findings establish the immunoturbidimetric method as a reliable and cost-effective alternative to HPLC for routine HbA1c determination. …”
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Transformers for Neuroimage Segmentation: Scoping Review by Maya Iratni, Amira Abdullah, Mariam Aldhaheri, Omar Elharrouss, Alaa Abd-alrazaq, Zahiriddin Rustamov, Nazar Zaki, Rafat Damseh

“…Manual segmentation is time-consuming, apart from being prone to human error and variability. Transformers are a promising deep learning approach for automated medical image segmentation. …”
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Pathways Between Parental Attitudes and Early Childhood Caries in Preschool Children by Apolinaras Zaborskis, Aistė Kavaliauskienė, Jaunė Razmienė, Augustė Razmaitė, Vilija Andruškevičienė, Julija Narbutaitė, Eglė Aida Bendoraitienė

“…The final model met all goodness-of-fit criteria: Chi-square test <i>p</i> = 0.211, Incremental Fit Index IFI = 0.994, Tucker–Lewis Index TLI = 0.982, Comparative Fit Index CFI = 0.994, and Root Mean Square Error of Approximation RMSEA = 0.038. <b>Conclusions</b>: Findings from this study demonstrate that parents play a significant role in determining children’s oral health. …”
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The influence of tactical models of team play on the dynamics of collective ball control indicators in football by Pavlo Perepelytsia, Volodymyr Perevoznyk, Volodymyr Paievskyi, Anatoliy Abdula, Irina Pomeshchikova, Betrix Yachsie

“…All data obtained during the experimental study were processed using well-known methods of mathematical statistics: x̄ - arithmetic mean; σ - standard deviation; m – error of representativeness of the arithmetic mean; t – reliability of the difference between the mean values ​​(according to the Student’s t-test). …”
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Assessing the measurement properties of PROMIS Computer Adaptive Tests, short forms and legacy patient reported outcome measures in patients undergoing total hip arthroplasty by C. Braaksma, N. Wolterbeek, M. R. Veen, R. W. Poolman, Y. Pronk, A. D. Klaassen, R. W. J. G. Ostelo, C. B. Terwee

“…The reliability, measurement precision (Standard Error of Measurement (SEM)), smallest detectable change (SDC), and burden of PROMIS instruments were presented head-to-head to legacy PROMs. …”
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Feasibility study of automatic radiotherapy treatment planning for cervical cancer using a large language model by Shuoyang Wei, Ankang Hu, Yongguang Liang, Jingru Yang, Lang Yu, Wenbo Li, Bo Yang, Jie Qiu

“…Abstract Background Radiotherapy treatment planning traditionally involves complex and time-consuming processes, often relying on trial-and-error methods. The emergence of artificial intelligence, particularly Large Language Models (LLMs), surpassing human capabilities and existing algorithms in various domains, presents an opportunity to automate and enhance this optimization process. …”
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The effects of fixation stability, corneal density, and epithelial hyperplasia on the efficacy of astigmatism correction by transepithelial photorefractive keratectomy by Junjie Yu, Hao Zhou, Minjie Chen, Zhiqiang Yu, Xingtao Zhou, Yishan Qian

“…No significant associations were found between ORA and CI or AOE. Conclusions Postoperative changes in epithelial thickness were associated with the efficacy of transPRK in both the low and high RA groups, whereas the pupil center shift and anterior CD were associated with the efficacy of transPRK in the low RA group.…”
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Minimum required distance for clinically significant measurement of habitual gait speed by Myung Woo Park, Sun Gun Chung, Jaewon Beom, Kyung Su Kim, Joonghee Kim, Chul-Hyun Park, Jinkyu Lee, Keewon Kim

“…We also investigated which clinical, anthropometric, or epidemiological variables might influence it by assessing their association with gait speed variance using mean squared error from linear regression. Results Gait speed measured by pose estimation (1.55 ± 0.18 m/s) showed a high level of agreement with manual measurement (1.56 ± 0.14 m/s), with an intraclass correlation coefficient of 0.889 (95% CI: 0.822–0.931). …”
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A novel equation synthesis for estimating resting energy expenditure in prostate cancer patients by Nilüfer Acar Tek, Tevfik Koçak, Süleyman Yeşil, Tevfik Sinan Sözen

“…The smallest root mean squared error (RMSE) values in the malign and benign prostate groups were novel equation MPG (149 kcal/d) and novel equation BPG (202 kcal/d). …”
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Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations by Yuchao Miao, Jiwei Li, Ruigang Ge, Chuanbin Xie, Yaoying Liu, Gaolong Zhang, Mingchang Miao, Shouping Xu

“…The AB model matched well with the clinical plan’s dose-volume histograms, and the average dose error for all organs was 1.65 ± 0.69%. Conclusions Our proposed new model signifies a crucial advancement in predicting CK 3D dose distributions for clinical applications. …”
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Validation of the Perceived Barriers to Antiretroviral Therapy Adherence (PEDIA) Scale Among Gay, Bisexual, and Other Men Who Have Sex With Men and Transgender and Nonbinary Person... by Victor C Matos, Dyego Carlos Araújo, Thiago S Torres, Paula M Luz

“…CFA fit indices for PEDIAr were adequate (root mean square error of approximation=0.07, comparative fit index=0.95, Tucker-Lewis Index=0.94, standardized root mean square residual=0.05). …”
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Using a large language model (ChatGPT) to assess risk of bias in randomized controlled trials of medical interventions: protocol for a pilot study of interrater agreement with huma... by Christopher James Rose, Julia Bidonde, Martin Ringsten, Julie Glanville, Rigmor C. Berg, Chris Cooper, Ashley Elizabeth Muller, Hans Bugge Bergsund, Jose F. Meneses-Echavez, Thomas Potrebny

“…RoB assessment is subject to human error and is time-consuming. Machine learning-based tools have been developed to automate RoB assessment using simple models trained on limited corpuses. …”
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Demographic Characteristics of Patients Applying for Legal Pregnancy Evacuation and the Incidence of Depression in Post-Discharge Patients-Prospective Cross-Sectional Study by İsa Kaplan, Burcu Bıçakçı, Hasan Yüksel, Ali Yıldızbakan

“…The work-life of 57.1%, the social life of 45.7%, the private life of 71.4%, and the sexual life of 82.9% of women who had a legal abortion were affected. Conclusions: The incidence of depression after legal medical termination of pregnancy is not to be underestimated. …”
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Can machine-learning algorithms improve upon classical palaeoenvironmental reconstruction models? by P. Sun, P. B. Holden, H. J. B. Birks, H. J. B. Birks

“…In general, the MEMLM approaches, even when trained on only dimensionally reduced assemblage data, performed substantially better than the WA approaches in the larger training sets, as judged by cross-validatory prediction error. When applied to fossil data, MEMLM variants sometimes generated qualitatively different palaeoenvironmental reconstructions from each other and from reconstructions based on WA approaches. …”
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CALCULATION OF INTERMICROBIAL INTERACTIONS OF ORAL BIOTOPE by A.V. Zaitsev, N.V. Kotelevskaya, O.M. Boychenko, A.K. Nikolishin

“…For fungi of the genus Candida, the error at CPV ≤ 6 is due to the fact that at CPV = 0 they are absent in the biocenosis. …”
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Efficacy of Asymmetric Myopic Peripheral Defocus Lenses in Spanish Children: 24-Month Randomized Clinical Trial Results by Clara Martinez-Perez, Miguel Ángel Sánchez-Tena, Jose Miguel Cleva, Cesar Villa-Collar, Marta Álvarez, Eva Chamorro, Cristina Alvarez-Peregrina

“…Baseline characteristics, including age, refractive error, and AL, were comparable between groups. Dropout rates were 15.9%, with 14 participants lost to follow-up, distributed equally between the two groups. …”
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