An examination of the effectiveness of mindfulness-integrated cognitive behavior therapy on depression, anxiety, stress and sleep quality in Iranian women with breast cancer: a ran... by Mahboobeh Soleymani Moghadam, Aliakbar Parvizifard, Aliakbar Foroughi, Seyed Mojtaba Ahmadi, Negin Farshchian

“…Then, 15 participants were placed in the intervention group and 15 in the control group with four random blocks. …”
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Absolute Quantitative Photoacoustic Imaging for Contrast Agents Concentration Estimation Using a Spectral Decomposition Approach by Shang Gao PhD, Liudmila Serebrennikova MS, Ryo Murakami MS, Srikanth Boinapally PhD, Sangeeta Ray PhD, Martin G. Pomper MD, PhD, Haichong K. Zhang PhD

“…The method achieved significantly lower concentration estimation errors, with average absolute errors of 1.80 µM in saline and 3.34 µM in blood. …”
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An Exploratory Study: Performance Differences Between Novice Teen and Senior Drivers Using Interactive Exercises on a Driving Simulator by Johnell O. Brooks, Rakesh Gangadharaiah, Patrick J. Rosopa, Casey Jenkins, Elenah B. Rosopa, Rebecca Pool, Lauren Mims, Breno Schwambach, Timothy Jenkins, Ken Melnrick

“…Overall, teens had faster reaction times and fewer errors than seniors, yet seniors demonstrated greater improvement over time. …”
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Standardised self-management kits for children with type 1 diabetes: pragmatic randomised trial of effectiveness and cost-effectiveness by Davina Allen, Ian T Russell, John W Gregory, Daphne Russell, Cynthia Carter, Deborah Edwards, Llinos Haf Spencer, Yvonne Sylvestre, Rhiannon Whitaker, Seow Tien Yeo

“…Objective To estimate the effectiveness of standardised self-management kits for children with type 1 diabetes.Design Pragmatic trial with randomisation ratio of two intervention: one control. Qualitative process evaluation.Setting 11 diabetes clinics in England and Wales.Participants Between February 2010 and August 2011, we validly randomised 308 children aged 6–18 years; 201 received the intervention.Intervention We designed kits to empower children to achieve glycaemic control, notably by recording blood glucose and titrating insulin. …”
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Ultrasound cases of an elongated left lobe of the liver as an anatomical variant by N. V. Ischenko, N. K. Vinogradova, L. A. Titova, E. M. Tolstykh, S. I. Marks

“…Due to the fact that the elongated left lobe of the liver is more often susceptible to injury and, in some cases, can imitate a subcapsular hematoma of the spleen, it seems important to increase the awareness among doctors of various specialties about the variety of morphological variations in the structure of the liver, in particular about the elongated left lobe of the liver, to unify approaches to the description and establish uniformity of wording to designate this feature of the anatomical structure of the left lobe of the liver, which will reduce the risk of diagnostic errors and errors during surgical interventions, especially in cases of blunt abdominal trauma.The article presents clinical cases with ultrasound examination of 10 patients of different ages (from 1 month to 38 years) and gender with a newly diagnosed anomaly in the structure of the left lobe of the liver, i.e an elongated left lobe. …”
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Perspectives of Targeting Autophagy as an Adjuvant to Anti-PD-1/PD-L1 Therapy for Colorectal Cancer Treatment by Nasrah ALKhemeiri, Sahar Eljack, Maha Mohamed Saber-Ayad

“…The beneficial effect of immune checkpoint inhibitors, specifically anti-PD-1/ PD-L1, has been ascribed to the abundance of DNA replication errors that result in the formation of neoantigens. …”
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210 Addressing burnout in radiologists: Causes, impact on patient care, and potential solutions by Pardaman Setia, Linette Penney, Vedant Shukla, Mikhail Lobo

“…Early and effective interventions are essential for improving job satisfaction, reducing medical errors resulting in enhanced patient care. …”
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Effects of aquatic exercises in a rat model of brainstem demyelination with ethidium bromide on the beam walking test Efeitos de exercícios aquáticos no desempenho motor de ratos s... by Cíntia Cristina Souza Nassar, Eduardo Fernandes Bondan, Sandra Regina Alouche

“…We quantified the number of footsteps and errors during the beam walking test. The demyelinated animals walked fewer steps with a greater number of errors than the control group. …”
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Peculiarities and Consequences of Different Angiographic Patterns of STEMI Patients Receiving Coronary Angiography Only: Data from a Large Primary PCI Registry by Alexandru Burlacu, Grigore Tinica, Bogdan Artene, Paul Simion, Diana Savuc, Adrian Covic

“…Patients with diagnostic errors and normal arteries displayed strong correlations with all cardiovascular risk factors. …”
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ACO-NM hybrid optimization calculation method for transit time of oxygen activation logging in CO2 injection profile by WANG Zhengyan, CHEN Meng, YANG Guofeng, LIU Guoquan, PEI Yang, CHEN Qiang

“…Compared with the traditional methods involving manual peak boundary determination combined with weighted average or Gaussian function fitting methods, this approach offered higher fitting efficiency, reduced human intervention, and lower calculation error.Through a comparative analysis of pulse neutron oxygen activation data processing and interpretation in well X (CO2 injection well) of the M oilfield, the established ACO-NM optimization model could effectively realize the bimodal separation of overlapping peaks in tubing and casing spaces. …”
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Leveraging deep neural network and language models for predicting long-term hospitalization risk in schizophrenia by Yihang Bao, Wanying Wang, Zhe Liu, Weidi Wang, Xue Zhao, Shunying Yu, Guan Ning Lin

“…By utilizing language models, our developed algorithm efficiently extracts 95% of the unstructured electronic health records data needed for this work, while ensuring data privacy and low error rate. This paradigm has also been demonstrated to have significant advantages in reducing potential discrimination and erroneous dependencies. …”
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Toward the Development of a Novel Flexible Sensor for Simultaneous Measurement of Acupoint Resistance and Temperature in Human Subjects by Zheng Yu, Yusheng Tang, Linshuai Zhang, Ziqian Wang, Xuanhao Shu, Hang Li, Yafei Zhang, Xuerong Luo, Xihong Yang, Xianfeng Cao, Shuguang Yu, Chuanbiao Wen

“…Furthermore, the designed sensor has been applied to human sensitized acupoint monitoring and intervention experiments, demonstrating favorable performance, which offers potential for future acupoint sensitization research.…”
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Effectiveness of Dietary Guidelines for Reducing Free Sugar Intakes: A Randomised Controlled Trial by Lucy Boxall, Katherine M. Appleton, Emily Arden-Close, Janet James

“…There were no significant differences at baseline %FS (mean with standard error in parentheses); control with 10.36% (0.67), N with 10.15% (0.66), NF with 10.68% (0.62), and NFS with 10.19% (0.56). …”
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Epileptic Encephalopathy Related to CAD Deleterious Variants—A Case Series by Adelina Glangher, Magdalena Budișteanu, Diana Bârcă, Dana Șurlică, Florentina Ionela Lincă, Doina Ioana, Laurentiu-Camil Bohîlțea, Ina-Ofelia Focșa, Catrinel Iliescu

“…Background: Epilepsy, particularly early-onset and drug-resistant forms, presents a significant challenge in pediatric neurology. Inborn errors of metabolism are increasingly recognized as important contributors to these types of epilepsy. …”
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Cross-sectional and longitudinal Biomarker extraction and analysis for multicentre FLAIR brain MRI by J. DiGregorio, A. Gibicar, H. Khosravani, P. Jabehdar Maralani, J.-C. Tardif, P.N. Tyrrell, A.R. Moody, A. Khademi

“…This demonstrates that FLAIR MRI can be used for end-to-end analysis of large AD and CVD datasets, which can lower acquisition costs, simplify clinical translation, and reduce measurement error associated with multi-modal approaches.…”
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The Effect of Digital Addiction Training on University Students’ Digital Addiction, Sleep Quality, and Orexin-A Levels: Randomized Controlled Trial by Zehra İncedal Sonkaya, Burak Yazgan

“…In all statistical analyses, Type I error margin was set as p <.05. Results Intervention group students showed significant changes in the Pittsburgh Sleep Quality Index (t (19) = 6.28, p <.001, d = 1.40), Digital Addiction total (t (19) = 8.11, p <.001, d = 1.81) and its sub-subscales of Overuse (t (19) = 6.35, p <.001, d = 1.42), Non-restraint (t (19) = 5.07, p <.001, d = 1.13), Emotional State (t (19) = 4.17, p <.001, d = 0.93), and Dependence (t (19) = 3.85, p <.01, d = 0.86) scores. …”
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Pig Aggression Tracking and Analysis Application Based on A RPMeMOTR Method by Shuqin Tu, Haoxuan Ou, Aqing Yang, Yun Liang, Jiaying Du, Yuefei Cao, Ruilin He, Fang Yuan

“…Due to rapid pig movement and frequent occlusions during aggression activities, the key challenges for pig tracking and aggression analysis using multi-object tracking (MOT) are low tracking accuracy and error identity-switching (IDs) problems. To address the above challenges, this study proposes an RPMeMOTR approach by combining the RKNet model and the P-ids algorithm based on MeMOTR for pig aggression tracking and analysis. …”
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Automatic Weight-Bearing Foot Series Measurements Using Deep Learning by Jordan Tanzilli, Alexandre Parpaleix, Fabien de Oliveira, Mohamed Ali Chaouch, Maxime Tardieu, Malo Huard, Aymeric Guibal

“…Methods: A retrospective, non-interventional study at Perpignan Hospital analyzed the weight-bearing foot radiographs of 105 adult patients (August 2017–August 2022). …”
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Assessing dengue forecasting methods: a comparative study of statistical models and machine learning techniques in Rio de Janeiro, Brazil by Xiang Chen, Paula Moraga

“…Employing a dynamic window approach, various statistical methods and machine learning techniques were used to generate weekly forecasts at several time horizons. Error measures, uncertainty intervals, and computational efficiency obtained with each method were compared. …”
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Predicting depression and unravelling its heterogeneous influences in middle-aged and older people populations: a machine learning approach by Ling Zhang, Ruigang Wei, Jingwen Zhou, Lin Tan, Xiaolong Che, Minqinag Zhang, Xiaoyue Ning, Zhiliang Zhong

“…Results The LSTM model effectively predicted depression-related variables (mean square error = 0.067). The average AUC of the five ML models ranged from 0.78 to 0.82. …”
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