Screening for endometriosis: A scoping review of screening measures that could support early diagnosis by Brittany N. Rosenbloom, Tania Di Renna, Adriano Nella, Mathew Leonardi, Maggie Tiong, Seungmin Lee, Rachael Bosma

“…A majority of the included studies assessed very few measurement properties (e.g., measurement error, structural validity, construct validity or responsiveness, etc…) of the PROM, leaving their quality unknown. …”
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The influence of jittering DHS cluster locations on geostatistical model-based estimates of malaria risk in Cameroon by Salomon G. Massoda Tonye, Romain Wounang, Celestin Kouambeng, Penelope Vounatsou

“…The various sets of selected environmental factors were able to capture the main spatial patterns of the disease risk, but the jittering increased the prediction error. The parameter estimates of the effects of socio-economic factors and intervention indicators were relatively stable in the simulated data. …”
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Detecting depression in patients with coronary heart disease: a diagnostic evaluation of the PHQ-9 and HADS-D in primary care, findings from the UPBEAT-UK study. by Mark Haddad, Paul Walters, Rachel Phillips, Jacqueline Tsakok, Paul Williams, Anthony Mann, André Tylee

“…Areas under the curves (AUC) (standard error) were 0.95 (0.01) and 0.88 (0.02) for the PHQ-9 and HADS-D, and 0.91 (0.02) for PHQ-9 using the categorical algorithm. …”
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Coffee and tea consumption and glioma risk: a meta-analysis of cohort studies by Jinyu Pan, Chuan Shao, Hui Tang, Nan Wu

“…The analysis explored glioma risk concerning the highest versus lowest levels of coffee and tea intake, supplemented by a dose–response evaluation using a one-stage robust error meta-regression model.ResultsA total of nine studies, published between 2004 and 2020, were included. …”
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An enhanced method of CNNs by incorporating the clustering-guided block for concrete crack recognition by Hui Li, Chenyu Liu, Ning Zhang, Wei Shi

“…Notably, the CG-DeepLabV3 + model significantly reduced the recognition error for locating crack edges to a mere 2.31 pixels. …”
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Experimentally profiling dielectric properties of Escherichia coli and Staphylococcus aureus by movement velocity and force by Akmal Suhaimi, Arash Zulkarnain, Noraziah Mohamad Zin, Abdullah Abdulhameed, Aminuddin Ahmad Kayani, Ramdzan Buyong

“…The benefits of AI integration into DEP systems include improving position and accuracy, faster processing and decision-making, enhancing particle classification, reducing human error, and many others. On the other hand, DEP research often focuses on CMF values of the particles. …”
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Development of a deep learning method to identify acute ischaemic stroke lesions on brain CT by Emanuele Trucco, Joanna M Wardlaw, Wenwen Li, Grant Mair, Amos Storkey, Alessandro Fontanella, Antreas Antoniou, Eleanor Platt, Paul Armitage

“…Chronic brain conditions reduced accuracy, particularly non-stroke lesions and old stroke lesions (32% and 31% error rates, respectively).Conclusion DL methods can be designed for ischaemic lesion detection on CT using the vast quantities of routinely collected brain scans without the need for lesion annotation. …”
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THE EFFECT OF DELAY IN TEMPERATURE VARIATIONS ON RESULTS OF GLUCOSE TEST IN DM PATIENTS WITH HYPERCHOLESTEROLEMIA by Chori Khotul Ula, Edy Haryanto Edy Haryanto, Syamsul Arifin Syamsul Arifin, Wisnu Istanto

“…Background: The pre-analytic stage has the most significant contribution to error, which is 60% to 70%. This is an excellent contribution to the dependability of laboratory results. …”
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Assessment of GEP and ANN for Predicting Suspended Sediment Load: A Case Study of Ghatoor and Aland Rivers, West Azerbaijan, Iran by Emad Fardoost, Majid Dastgahi, Reyhane Nourali, Elham Ayati

“…Two statistical indices were used to evaluate the models: the coefficient of determination (R-squared) and the Mean Absolute Error (MAE). Based on these indices, the intelligent models performed better than the SRC in estimating the suspended sediment volume. …”
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Predicting carbohydrate quality in a global database of packaged foods by Eric Antoine Scuccimarra, Alexandre Arnaud, Marie Tassy, Marie Tassy, Kim-Anne Lê, Fabio Mainardi

“…The overall mean absolute error on the test set was 0.96 g/100 g of product. …”
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Predicting kidney graft function and failure among kidney transplant recipients by Yi Yao, Brad C. Astor, Wei Yang, Tom Greene, Liang Li

“…Results For prediction up to the next 1 to 5 years, the model achieved high accuracy in predicting graft failure, with the AUC between 0.80 and 0.95, and moderately high accuracy in predicting eGFR, with the root mean squared error between 10 and 18 mL/min/1.73m2 and 70%-90% of predicted eGFR falling within 30% of the observed eGFR. …”
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A reliable tool for assessment of acceptance of e-consultation service in hospitals: the modified e-consultation Technology Acceptance Model (TAM) questionnaire by Rasha Ashmawy, Sally Zeina, Ehab Kamal, Khaled Shelbaya, Nermeen Gawish, Sandy Sharaf, Elrashdy M. Redwan, Azza Mehanna

“…Confirmatory factor analysis (CFA) confirmed the two-factor model, with standardized factor loadings between 0.80 and 0.95, a Comparative Fit Index (CFI) of 0.95, and a Root Mean Square Error of Approximation (RMSEA) of 0.084. Conclusion The modified e-consultation TAM questionnaire proves to be a reliable and valid tool for evaluating physicians’ acceptance of and satisfaction with e-consultation service. …”
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Psychometric evaluation and derivation of the Kannada version of the modified (29-item model) Indian Vision Function Assessment Questionnaire by Soujanya Kaup, Jyoshma Dsouza, Siddharudha Shivalli, Sheetal Savur, Vidya Hegde

“…The model-fit to the data assessed by various indices [Root Mean Squared Error of Approximation = 0.08 (90% CI: 0.081–0.091); Comparative Fit Index = 0.877; Tucker-Lewis Index = 0.866; Akaike’s Information Criterion = 23447.133; Bayesian Information Criterion = 23800.45, and Coefficient of Determination = 0.998] demonstrated acceptable fit. …”
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The combined impact of AI and VR on interdisciplinary learning and patient safety in healthcare education: a narrative review by Emmanuel Aoudi Chance

“…Strategic implementation can contribute to error reduction, improved patient outcomes, and a culture of safety. …”
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Reliability of the Tuck Jump Assessment Using Standardized Rater Training by Kevin Racine, Meghan Warren, Craig Smith, Monica R. Lininger

“…The total score had moderate interrater reliability in both sessions (Session 1: ICC~2,2~ = 0.64; 95% CI (Confidence Interval) (0.34-0.81); Standard Error Measurement (SEM) = 0.66 technique flaws and Session 2: ICC~2,2~ = 0.56; 95% CI (0.04-0.79); SEM = 1.30). …”
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Cross-cultural adaption and validation of the Chinese version of the Child Food Neophobia Scale by Yan Liu, JiaoJiao Zou, Qiping Yang, Hanmei Liu, Jing Luo, Yufeng Ouyang, Joyce Wang, Qian Lin

“…A normal χ2/df, CMIN/DF=3.302, Comparative Fit Index, CFI=0.993, Tucker-Lewis Index, TLI=0.986 and root mean square error of approximation, RMSEA=0.077 were found. The CFA results showed that the model indicators were acceptable. …”
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Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds by Vittoria Asti, Michela Ablondi, Arnaud Molle, Andrea Zanotti, Matteo Vasini, Alberto Sabbioni

“…Overall, the GBM model exhibits the highest accuracy and the lowest error. In conclusion, integrating IMU technology into horse performance evaluation offers valuable insights, with implications for breeding and training.…”
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The relationship between attentional control and injury-related biomechanics in young female volleyball players by Ivana Hanzlíková, Karolína Válová, Michal Lehnert, Martin Dvořáček, Elisa Doleželová, Adam Grinberg

“…Biomechanical measures included the Landing Error Scoring System (LESS), single-leg dynamic balance (center of pressure [CoP] movement), leg stiffness during submaximal hopping, and reactive strength index (RSI) during drop jumps. …”
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Causality Between 91 Circulating Inflammatory Proteins and Various Asthma Phenotypes: A Mendelian Randomization Study by Zhang S, Zhang X, Wei C, Zhang L, Li Z

“…The FDR correction was performed due to the possibility of a type 1 error.Results: Genetically predicted IVW results revealed a total of 30 data sets suggesting a potential causal relationship between circulating inflammatory proteins and asthma phenotypes. …”
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Calculation of IOL Optical Power Using OKULIX Ray-Tracing Software in Real Clinical Practice by K. B. Pershin, N. F. Pashinova, A. Yu. Tsygankov, I. V. Kosova

“…When comparing the devices under study, significant differences were found for the rate of refractive power within ±0.5 D when using the IOLMaster on the one hand and OKULIX on the other (p < 0.05). The refractive error rate of ±1.0 D using the biometric devices did not differ significantly (p > 0.05).Conclusion. …”
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