An efficient and robust MRI-guided radiotherapy planning approach for targeting abdominal organs and tumours in the mouse. by Veerle Kersemans, John S Beech, Stuart Gilchrist, Paul Kinchesh, Philip D Allen, James Thompson, Ana L Gomes, Zenobia D'Costa, Luke Bird, Iain D C Tullis, Robert G Newman, Aurelien Corroyer-Dulmont, Nadia Falzone, Abul Azad, Katherine A Vallis, Owen J Sansom, Ruth J Muschel, Borivoj Vojnovic, Mark A Hill, Emmanouil Fokas, Sean C Smart

“…<h4>Results</h4>The BANG gel phantoms demonstrated a targeting efficiency error of 0.56 ± 0.18 mm. The in vivo stability tests of body motion during MR-IGRT and the associated cradle transfer showed that the residual body movements are within this MR-IGRT targeting error. …”
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Assessing the Correlation between Skeletal and Corresponding Soft-Tissue Equivalents to Determine the Relationship between CBCT Skeletal/Dental Dimensions and 3D Radiographic Soft-... by Da In Kim, Manuel O. Lagravère

“…The landmark with the highest mean error on the CBCT was 2.0 ± 1.6 mm on the z-axis for the spinal level landmark. …”
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Brain metabolic changes associated with post-stroke pathological laughing and crying: an 18F-FDG-PET study in pontine stroke by Soojin Choi, Soojin Choi, Dae Hyun Kim, Won Jun Kang, Yong Wook Kim

“…Voxel-wise two-sample t-tests were performed to compare brain metabolism between the two groups (Pfamily-wise error-corrected &lt; 0.05). Multiple regression analysis was conducted to identify brain regions significantly associated with PLC severity, adjusting for age and stroke lesion volume.ResultsCompared with that of the non-PLC group, the PLC group exhibited significant hypometabolism in the right superior frontal gyrus (Pfamily-wise error-corrected &lt; 0.05). …”
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Effect of Matrix and Source of Quality Specification Data on the Sigma Metrics of Common Chemistry Analytes in Clinical Laboratory by Srihita Mahavadi, Jayakumari Shanthakumari

“…The cumulative CV and bias were obtained using unity real-time software from Bio-Rad Laboratories. Total allowable error values were obtained from BV and CLIA guidelines. …”
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Autopsia odontolegal: revisión de las limitaciones técnicas y sus posibles soluciones by Heit O, Zemel M

“…RESULTADOS: Se analizaron 47 publicaciones (artículos y libros) y se elaboró una tabla sobre los pasos que involucra una autopsia odontolegal, de las limitaciones y posibles soluciones técnicas. CONCLUSIÓN: La autopsia odontolegal es una función del perito especializado en odontología legal y los procedimientos deben ser protocolizados para evitar errores en el proceso de recolección de datos. …”
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Analytical Validation of Wrist-Worn Accelerometer-Based Step-Count Methods during Structured and Free-Living Activities by Robert T. Marcotte, Shelby L. Bachman, Yaya Zhai, Ieuan Clay, Kate Lyden

“…During free-living activities, the method relying on frequency analysis exhibited the lowest percent error of all methods. Finally, we found that the incorporation of a locomotion classifier, wherein steps were only estimated during identified locomotion periods, reduced error for two methods when applied to data across structured and free-living settings. …”
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Cognitive considerations for adults with sickle cell disease completing the brief pain inventory by Julia A. O'Brien, Jermon A. Drake, Donald J. Bearden, Kim E. Ono, Soumitri Sil, Lindsey L. Cohen, Alana Karras, Enrico M. Novelli, Charles R. Jonassaint

“…Group differences in neurocognitive function were no longer significant after familywise error rates were controlled for. Literacy was not associated with error rates. …”
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Improvement in matching lesions in dual-view mammograms using a geometric model by Sina Wang, Zeyuan Xu, Bowen Zheng, Hui Zeng, Derun Pan, Mengwei Ma, Weiguo Chen, Genggeng Qin

“…GM outperformed both AB and SS, yielding a median absolute error of 3.03 mm (IQR 1.45–5.55 mm) versus 5.78 mm (IQR 2.44–10.71 mm) for AB and 4.59 mm (IQR 1.91–8.19 mm) for SS (P < 0.001). …”
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INVASIVE MONITORING OF CARDIAC OUTPUT BY PULSE WAVE TRANSIT TIME AFTER AORTOCORONARY BYPASS ON THE BEATING HEART by A. A. Smetkin, Ayyaz Hussain, E. V. Fot, V. I. Zakharov, N. N. Isotova, A. S. Yudina, Z. A. Dityateva, Ya. V. Gromova, V. V. Kuzkov, M. Yu. Kirov

“…Conclusion: Lower repeatability of CO measurement by PWTT and insufficient capability to follow the changes in CO after ACB without CPB don not allow recommending this method in its invasive variant for routine practice as an alternative to thermodilution methods.…”
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Heart transplant rejection pathology by Stojićević Andrea, Jovanović Milena, Matković Miloš, Nestorović Emilija, Stanojević Nemanja, Dožić Branko, Glumac Sofija

“…Endomyocardial biopsy has proven to be a safe and appropriate technique, with little sampling error, and remains, to this day, one of the most commonly used methods for diagnosing acute rejection. …”
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A hybrid deep learning framework for regional reference crop evapotranspiration estimation in the Hetao Irrigation District using limited meteorological data by Xiao Zhang, Yuxin Tao, Chenglong Zhang

“…New hydrological insights for the region: The results indicated that the mass transfer-based CNN-Informer3 model achieved the best estimation performance, with its average Determination Coefficient (R2), Nash-Sutcliffe efficiency coefficient (NSE), Root Mean Square Error (RMSE), Relative Root Mean Square Error (RRMSE), Mean Absolute Error (MAE) and Percentage Bias (PBIAS) of 0.9712, 0.9665, 0.3764 mm/d, 0.1192, 0.2591 mm/d and -3.8143 % for accuracy evaluation, significantly outperforming other models. …”
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Continuous Estimation of Cardiac Output in Critical Care: A Noninvasive Method Based on Pulse Wave Transit Time Compared with Transpulmonary Thermodilution by Ulrike Ehlers, Rolf Erlebach, Giovanna Brandi, Federica Stretti, Richard Valek, Stephanie Klinzing, Reto Schuepbach

“…The performance of COesCCO could not be linked to the patient’s condition. Conclusion. The accuracy and precision of the esCCOTM method were not clinically acceptable for our critical patients. …”
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Maintenance of the Results of Stage II Lower Limb Lymphedema Treatment after Normalization of Leg Size by Jose Maria Pereira de Godoy, Henrique Jose Pereira de Godoy, Renata Lopes Pinto, Fernando Nestor Facio, Maria de Fatima Guerreiro Godoy

“…During one week, the grosgrain stocking reduced leg volumes to baseline values (p value = 0.24). Conclusion. Higher compression of elastic stockings is better than lower compression but the inelastic grosgrain stocking is even better than both to maintain the results.…”
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The effect of conservation agriculture technologies adoption on food production and security in Northern Malawi: evidence from Mzimba district by George N. Chidimbah Munthali, George N. Chidimbah Munthali, He Puming, Lazarus Obed Livingstone Banda, Peter Stephen Donald Ngulube, Gama Rivas Daru, Thokozani Mzumara, Moses M. N. Chitete, Zondiwe Mabilabo Jere

“…Adoption of CATs significantly boosts production, with adopters experiencing lower food insecurity and better dietary diversity than non-adopters.Conclusion and recommendationThe study confirms that adopting conservation agricultural technologies is integral to improving agricultural production, but remains entangled in disparities related to gender, farm size, and education. …”
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Development of an upper limb muscle strength rehabilitation assessment system using particle swarm optimisation by Chuangan Zhou, Siqi Wang, Meiyi Wu, Wei Lai, Junyu Yao, Xingyue Gou, Hui Ye, Jun Yi, Dong Cao

“…Model performance was evaluated using R-squared (R2), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Bias Error (MBE).ResultsThe system successfully collected electromyographic and kinematic data. …”
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The neural network for measuring IOP by Maklakov method: comparison between neuronal net and experts by A.A. Rascheskov, I.A. Frolychev, N.A. Pozdeeva

“…The accuracy of AI-Tonometry: the mean absolute error (MAE) is 2.5 mmHg, the mean squared error (MSE) is 8.76, the root mean squared error (RMSE) is 2.96. …”
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Exploring the achievements and forecasting of SDG 3 using machine learning algorithms: Bangladesh perspective. by Md Maeen Molla, Md Sifat Hossain, Md Ayub Ali, Md Raqibul Islam, Mst Papia Sultana, Dulal Chandra Roy

“…<h4>Results</h4>ENET demonstrates superior performance compared to both BRNN and ARIMA in the context of NMR, achieving a Root Mean Absolute Error (RMAE) of 0.603446 and a Root Mean Square Error (RMSE) of 0.451162. …”
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Exploring the potential of deep learning models integrating transformer and LSTM in predicting blood glucose levels for T1D patients by Xin Xiong, XinLiang Yang, Yunying Cai, Yuxin Xue, JianFeng He, Heng Su

“…The model's performance is validated using real-world clinical data and error grid analysis. Results On clinical data, the model achieved root mean square error/mean absolute error of 10.157/6.377 (30-min), 10.645/6.417 (60-min), 13.537/7.283 (90-min), and 13.986/6.986 (120-min). …”
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PRONAME: a user-friendly pipeline to process long-read nanopore metabarcoding data by generating high-quality consensus sequences by Benjamin Dubois, Mathieu Delitte, Salomé Lengrand, Claude Bragard, Anne Legrève, Frédéric Debode

“…By integrating Nanopore-specific quality filtering, clustering and error correction, PRONAME produces high-precision consensus sequences. …”
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Assessing the accuracy of a machine learning prediction for 2 different shoulder prostheses: an external validation study by Gianluca Caprili, MD, Andrea G. Calamita, MD, Michele Novi, MD, Domenico A. Campanacci, MD, PhD, Simone Nicoletti, MD

“…In terms of MAE, we found a higher error than the internal validation only for forward elevation at 3-6 months in group 2 and a lower error in all the other outcome measures at all time points for both groups. …”
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