Developing interpretable machine learning models to predict length of stay and disposition decision for adult patients in emergency departments by Abhishek Sharma, Timothy N Fazio, Long Song, Samantha Plumb, Uwe Aickelin, Mojgan Kouhounestani, Mark John Putland

“…Our objective was to develop interpretable ML models to predict LOS and DD at specific time points, all while establishing a transparent data analysis framework. …”
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A DSP–FPGA Heterogeneous Accelerator for On-Board Pose Estimation of Non-Cooperative Targets by Qiuyu Song, Kai Liu, Shangrong Li, Mengyuan Wang, Junyi Wang

“…Instruction-level control supports model generalization, while a weight concatenation strategy improves resource utilization during convolution. …”
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Polygenic risk score for acute rejection based on donor-recipient non-HLA genotype mismatch. by Rui Cao, David P Schladt, Casey Dorr, Arthur J Matas, William S Oetting, Pamala A Jacobson, Ajay Israni, Jinbo Chen, Weihua Guan

“…To reduce the risk of post-transplant AR, determination of kidney transplant donor-recipient mismatching focuses on blood type and human leukocyte antigens (HLA), while it remains unclear whether non-HLA genetic mismatching is related to post-transplant complications.…”
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A Novel AI-Based Integrated Cybersecurity Risk Assessment Framework and Resilience of National Critical Infrastructure by Sardar Muhammad Ali, Abdul Razzaque, Muhammad Yousaf, Sardar Sadaqat Ali

“…The highest accuracy at 99% was attained by the LSTM model, while the CNN demonstrated superior precision (98%), recall (97%), and F1 score (97%). …”
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Incidence, Pathogenesis, Risk Factors, and Treatment of Cystoid Macula Oedema Following Cataract Surgery: A Systematic Review by Lorenzo Ferro Desideri, Kirupakaran Arun, Enrico Bernardi, Nicola Sagurski, Rodrigo Anguita

“…Further research is needed to establish optimal treatment algorithms and improve outcomes for patients with post-operative CMO…”
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Leveraging Vision Foundation Model via PConv-Based Fine-Tuning with Automated Prompter for Defect Segmentation by Yifan Jiang, Jinshui Chen, Jiangang Lu

“…On two real-world defect segmentation datasets, PA-SAM achieves mean Intersections over Union of 73.87% and 68.30%, as well as mean Dice coefficients of 84.90% and 80.22%, outperforming other state-of-the-art algorithms, further demonstrating its robust generalization and application potential.…”
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Bridging the Gap: A Review of Machine Learning in Water Quality Control by Herlina Abdul Rahim, Nur Athirah Syafiqah Noramli, Indrabayu

“…However, persistent challenges include data scarcity in developing regions (only 12% of Sub-Saharan African monitoring stations provide real-time data), algorithmic bias (65% sensitivity loss in cross-regional models), and regulatory skepticism toward "black-box" systems. …”
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Inflow Prediction for Agricultural Reservoirs Using Disaster Prevention Measurement Data: A Comparison of TANK Model and Machine Learning by Bong-Kuk Lee, Joonyoung Choi, Kyoung Jae Lim, Jeongho Han

“…The results of this study demonstrate the potential of machine learning techniques for inflow prediction in agricultural reservoirs and suggest the need for further research on model improvement using various algorithms and input variables.…”
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Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study by Gyeongmin Kim, Hyungtai Kim, Yun-Hee Kim, Seung-Jong Kim, Mun-Taek Choi

“…Through this method, six optimal clusters were selected with a silhouette score of 0.2831, which is a relatively higher value compared to other clustering algorithms. To clarify the characteristics of the selected groups, in-depth statistics of spatiotemporal, kinematic, and clinical features are presented in the results. …”
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Optimisation of the adaptive neuro-fuzzy inference system for adjusting low-cost sensors PM concentrations by Martina Casari, Piotr A. Kowalski, Laura Po

“…Notably, incorporating only PM2.5, relative humidity and temperature as features yields optimal performance while mitigating overfitting issues. The paper also explores various ANFIS configurations, including two distinct optimization algorithms, and investigates the impact of the number and type of membership functions on the fuzzy system's performance. …”
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Development and validation of a machine learning-based prediction model for hepatorenal syndrome in liver cirrhosis patients using MIMIC-IV and eICU databases by Fengwei Yao, Ji Luo, Qian Zhou, Luhua Wang, Zhijun He

“…Patients from the eICU database served as a test set for external validation, while patients from the MIMIC database were divided into training and validation groups. …”
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Estimating Leaf Chlorophyll Fluorescence Parameters Using Partial Least Squares Regression with Fractional-Order Derivative Spectra and Effective Feature Selection by Jie Zhuang, Quan Wang

“…Among the feature selection algorithms, the least absolute shrinkage and selection operator (LASSO) and stepwise regression (Stepwise) methods outperformed others. …”
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Enhancing phase change thermal energy storage material properties prediction with digital technologies by Minghao Yu, Jing Liu, Cheng Chen, Mingyue Li

“…Traditional experimental approaches, while effective, are resource-intensive and time-consuming, often requiring extensive trial-and-error methods. …”
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Clinical application and immune infiltration landscape of stemness‐related genes in heart failure by Wenting Yan, Yanling Li, Gang Wang, Yuan Huang, Ping Xie

“…Feature selection was performed using two machine learning algorithms. Nomogram models were then constructed to predict HF risk based on the selected key genes. …”
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Genetic subtyping by Whole Exome Sequencing across Diffuse Large B Cell Lymphoma and Plasmablastic Lymphoma. by Aitana Avendaño Pomares, Laura Rodríguez Merino, Sonia González, Jordi Morata, Raúl Tonda, Patricia Arribas, José Revert, Estrella Carrillo, Carlos Grande, Josep Maria Roncero, Jaime Pérez de Oteyza, Concepción Nicolás, Norma Gutierrez, Pau Abrisqueta, Antonio Gutiérrez, Ángel Ramírez-Páyer, Alejandro Martin Garcia-Sancho, Eva González-Barca, Santiago Montes-Moreno, GELTAMO group (Grupo Español de Linfomas y Trasplante Autólogo de Medula Osea), Spain

“…Recently, genomic-based algorithms have been proposed for the classification of this disease. …”
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Intensive Care for Anaphylaxis in Children: Current Trends by Yu. V. Bykov, A. N. Obedin, V. V. Fischer, E. V. Volkov, O. V. Zinchenko

“…Bronchodilators reduce BOS and are an additional treatment, while infusion therapy eliminates hypovolemia. Knowledge and timely implementation of modern care algorithms for anaphylaxis in children and adolescents will improve the quality of emergency care and reduce the risk of fatal outcomes in this pathology.…”
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Panoramic radiographic features for machine learning based detection of mandibular third molar root and inferior alveolar canal contact by A. Canberk Ulusoy, Tuğçe Toprak, M. Alper Selver, Pelin Güneri, Betül İlhan

“…The ANN configuration surpassed both radiologists and DL models in specificity (82%), F1 score (92%), and accuracy (85%), while maintaining a comparable sensitivity (86%) to the DL models. …”
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Efficient Implementation of Mahalanobis Distance on Ferroelectric FinFET Crossbar for Outlier Detection by Musaib Rafiq, Yogesh Singh Chauhan, Shubham Sahay

“…Our implementation exhibits an accuracy of 94.1% which is comparable to the software implementations while consuming a significantly low energy (27.2 pJ).…”
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The Specific Features of the Pathogenesis and Correction of Critical Conditions in Obstetric Care by Yu. S. Podolsky

“…The comparison group comprised 44 nonobstetric patients while examining multiple organ dysfunction (MOD) in the purperas. …”
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Enhancing Air Quality Forecasting Using Machine Learning Techniques by Zeinab Shahbazi, Zahra Shahbazi, Slawomir Nowaczyk

“…Urbanization is rapidly shaping our world, with more people than ever residing in cities. While cities offer numerous opportunities and conveniences, they also face critical challenges, including air pollution. …”
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