Implementation of automation tools for test analysis in the Radiotherapy Quality Assurance Programs by João Guilherme Rivera Santiago, Laura Furnari, Marcus Vinicius Saad de Paula Rodrigues, Victor Augusto Bertotti Ribeiro

“…To implement such tools, it is essential to assess factors such as accuracy, error detection sensitivity, adaptability to institution needs, and ease of access and use for those involved in quality control processes. …”
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Classification of melanoma skin Cancer based on Image Data Set using different neural networks by Rukhsar Sabir, Tahir Mehmood

“…Across these metrics, EfficientNet-B0 consistently outperformed ResNet-18 and basic CNN. The findings from this research suggest that neural network models, particularly EfficientNet-B0, hold significant promise for precise and efficient melanoma skin cancer detection.…”
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A brief review of Lynch syndrome: understanding the dual cancer risk between endometrial and colorectal cancer by Sneha Pallatt, Sibin Nambidi, Subhamay Adhikary, Antara Banerjee, Surajit Pathak, Asim K. Duttaroy

“…These mutations result in frameshift alterations, leading to the accumulation of errors within microsatellites. Individuals with LS have an elevated risk of developing colorectal and distant malignancies, including endometrial cancer (EC), which is one of the most common cancer associated with LS. …”
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Coexistence of a Leaky SCID Phenotype With Hyperphenylalaninemia in an Adult Case by Ugur Musabak, Tuba Erdogan, Muserref Sule Akcay, Serdar Ceylaner

“…For this reason, cases where diseases related to inborn errors of immunity (IEI) and metabolism errors are detected in the same patient are encountered more frequently. …”
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Benchmarking Large Language Models in Evaluating Workforce Risk of Robotization: Insights from Agriculture by Lefteris Benos, Vasso Marinoudi, Patrizia Busato, Dimitrios Kateris, Simon Pearson, Dionysis Bochtis

“…Using ChatGPT, Copilot, and Gemini, the LLMs followed a three-step evaluation process focusing on (a) task importance, (b) potential for task robotization, and (c) task attribute indexing of 15 agricultural occupations, mirroring the methodology used by human assessors. The findings indicate a significant tendency for LLMs to overestimate robotization potential, with most of the errors falling within the range of 0.229 ± 0.174. …”
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Artificial intelligence-enhanced diagnosis of degenerative joint disease using temporomandibular joint panoramic radiography and joint noise data by Eunhye Choi, Seokwon Shin, Kijin Lee, Taejin An, Richard K. Lee, Sunmin Kim, Youngdoo Son, Seong Teak Kim

“…A total of 2631 TMJ panoramic images were collected, resulting in a final dataset of 3908 images (2127 normal (N) and 1781 DJD (D)) after excluding indeterminate cases and errors. AI models using GoogleNet were evaluated with six different combinations of image data, clinician-detected crepitus, and patient-reported joint noise. …”
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Three-dimensional surface deformation field monitoring and influencing factors analysis in mountainous areas based on SBAS-INSAR technology (Tianjin, China) by Jun Shang, Mingyang Wang, Xin Wang, Mengyao Yang, Yifan Wu, Wangze Du

“…The comprehensive analysis of land subsidence in northern Tianjin’s mountainous region revealed multi-directional surface deformation characteristics, with validation against GNSS Kriging interpolation data demonstrating root mean square errors of 5.74 mm and 5.09 mm in vertical and east–west directions, respectively. …”
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Bayesian deep learning applied to diabetic retinopathy with uncertainty quantification by Masoud Muhammed Hassan, Halbast Rashid Ismail

“…In the case of Diabetic Retinopathy (DR), DL models have shown high efficacy in tasks such as classification, segmentation, detection, and prediction. However, DL model's opacity and complexity lead to errors in decision-making, particularly in complex cases, making it necessary to estimate the model's uncertainty in predictions. …”
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‘I can’t understand why others don’t screen more’: a qualitative study exploring why Australian general practitioners screen for primary aldosteronism by Sanne Peters, Jun Yang, Grant Russell, Abhir Krishan Nainani

“…Knowledge of the screening process, cost and convenience of performing the aldosterone–renin ratio, conceptualisation of risk related to PA, and a desire to improve clinical care were influencing factors that modified the GPs’ screening experience.Conclusion Our findings suggest that knowledge gaps, practical limitations of the aldosterone–renin ratio, and errors in diagnostic reasoning were challenges of routine PA screening. …”
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Relating Atlantic meridional deep-water transport to ocean bottom pressure variations as a target for satellite gravimetry missions by L. Shihora, T. Martin, A. C. Hans, R. Hummels, M. Schindelegger, H. Dobslaw

“…Here, we use the output of a fine-resolution (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><mo>/</mo><mn mathvariant="normal">20</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="27pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="eb44dc7215fab272447585860bb94269"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="os-21-1533-2025-ie00001.svg" width="27pt" height="14pt" src="os-21-1533-2025-ie00001.png"/></svg:svg></span></span>°) regional ocean model to assess the connection between OBP signals at the western boundary of the North and South Atlantic to changes in the zonally integrated meridional deep-water transport. We find that transport anomalies in the <span class="inline-formula">∼</span> 1–3 km depth range can be reconstructed using OBP variations spatially averaged over the continental slope, with correlations of 0.75 (0.72) for the North (South) Atlantic and root-mean-square errors of <span class="inline-formula">∼</span> 1 Sv (sverdrup; <span class="inline-formula">10⁶</span> <span class="inline-formula">m³ s⁻¹</span>), on monthly to inter-annual timescales. …”
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Ocular Manifestations Among Thalassemia Patients Presenting to Tertiary Care Hospital in Jammu Region by Sonika Syal, Rukhsana Kousar, Riya Gupta, Hans Raj Sharma, Manpreet Kaur

“…Aims: This study aims to find out the ocular manifestations in thalassemia patients at a tertiary care hospital in Jammu region. …”
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Utility and usability of a dengue NS1 rapid diagnostic as a self-test by Nurfatihah Zulkifli, Naim Che-Kamaruddin, Atiqah Hazan, Tan Kim-Kee, Sivalingam Rajagopal, Sazaly AbuBakar

“…Seventy percent (70%) of the participants, most of whom with monthly income of less than USD417, were willing to pay less than USD2 for the test kit. Conclusion Findings from the study suggested that a self-test diagnostic for dengue fever is highly acceptable and, hence, could be a viable approach for the early detection of the infection. …”
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Global and local magnitude and spatial pattern of uncertainty from geographically adaptive empirical and machine learning satellite-derived bathymetry models by Kim Lowell, Yuri Rzhanov

“…This lack of spatial autocorrelation among errors is potentially problematic for the use of SDB maps for navigation since error at any location is generally inferred from known uncertainties at neighboring locations. …”
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Advancing Nutritional Status Classification With Hybrid Artificial Intelligence: A Novel Methodological Approach by Md. Moddassir Alam, Asif Irshad Khan, Aasim Zafar, Mohammad Sohail, Mohammad Tauheed Ahmad, Rezaul Azim

“…The EGBF model is employed to classify nutritional states, including stunting, wasting, severe wasting, overweight, and underweight, providing a robust framework for predictive analysis. Findings The proposed FHO‐K‐Means and EGBF model demonstrated superior performance, achieving 99.84% accuracy, 99.5% precision, 99.8% specificity, and 100% sensitivity, with an F1 measure of 98.6% and a mean squared error (MSE) of 0.01%, outperforming existing classification techniques. …”
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An Improved Size and Direction Adaptive Filtering Method for Bathymetry Using ATLAS ATL03 Data by Lei Kuang, Mingquan Liu, Dongfang Zhang, Chengjun Li, Lihe Wu

“…Airborne LiDAR bathymetry (ALB) data were also used to validate the bathymetric accuracy and reliability. The experimental findings show that the ISDAF consistently exhibits effectiveness in detecting and retrieving signal photons, regardless of whether the seafloor terrain is stable or dynamic. …”
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A New Breast Cancer Discovery Strategy: A Combined Outlier Rejection Technique and an Ensemble Classification Method by Shereen H. Ali, Mohamed Shehata

“…It achieves 0.987 accuracy, 0.013 error, 0.98 recall, 0.984 precision, and a run time of 3 s, outperforming all other methods from the literature.…”
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Evaluating the relative predictive validity of measures of self-referential processing for depressive symptom severity by Ethel Siew Ee Tan, Hong Ming Tan, Kah Vui Fong, Sheryl Yu Xuan Tey, Nikita Rane, Chong Wei Ho, Zhao Yuan Tan, Rachel Jing Min Ong, Chloe Teo, Jerall Yu, Maxine Lee, An Rae Teo, Sin Kee Ong, Xin Ying Lim, Jin Lin Kee, Jussi Keppo, Geoffrey Chern-Yee Tan

“…DiscussionThese findings imply that task modifications such as utilising Likert-response options and the use of longer word lists may enhance the effectiveness of screening methods in both clinical and research settings, potentially improving early detection and intervention for depression.…”
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Noisy neuronal populations effectively encode sound localization in the dorsal inferior colliculus of awake mice by Juan Carlos Boffi, Brice Bathellier, Hiroki Asari, Robert Prevedel

“…The detected noise correlations contributed to minimize the error of the DCIC population code of sound azimuth. …”
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Real-Time, Risk-Based Clinical Trial Quality Management in China: Development of a Digital Monitoring Platform by Min Jiang, Shuhua Zhao, Yun Mei, Zhiying Fu, Yannan Yuan, Jie Ai, Yuan Sheng, Ying Gong, Jingjing Chen

“…ObjectiveThe objective of this study was to develop a digital monitoring platform that allows for the real-time monitoring and detection of risk points and provides warnings about risk points throughout the entire life cycle of clinical trials, on the basis of historical clinical trial quality control (QC) findings. …”
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Performance evaluation and improvement of ICESat-2 and GEDI forest canopy height retrievals in Northeast China by Cancan Yang, Daoli Peng, Nan Zhang, Mingjie Chen, Weisheng Zeng, Xiangnan Sun, Longwei Li, Weitao Li

“…Moreover, the proposed method increased the coefficient of determination (R2) for ICESat-2 canopy height accuracy from 0.53 to 0.82, and reduced the root mean square error (RMSE) from 3.98 m to 2.00 m. Similarly, the R2 for GEDI improved from 0.52 to 0.80, while RMSE decreased from 4.45 m to 2.41 m. …”
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