Impacts of Spatial Expansion of Urban and Rural Construction on Typhoon-Directed Economic Losses: Should Land Use Data Be Included in the Assessment? by Siyi Zhou, Zikai Zhao, Jiayue Hu, Fengbao Liu, Kunyuan Zheng

“…Results demonstrate three key findings: (1) By introducing prototype learning, a meta-learning approach, to guide model updates, we achieved precise assessments with small training samples, attaining an MAE of 1.02, representing 58.5–76.1% error reduction compared to conventional machine learning algorithms. This reveals that implicitly classifying typhoon disaster loss types through prototype learning can significantly improve assessment accuracy in data-scarce scenarios. (2) By designing a dual-path uncertainty quantification mechanism, we realized high-reliability risk assessment, with 95.45% of actual loss values falling within predicted confidence intervals (theoretical expectation: 95%). …”
Get full text

Energy-Accuracy Trade-Offs for Resistive In-Memory Computing Architectures by Saion K. Roy, Naresh R. Shanbhag

“…This result clearly implies the need for other approaches, e.g., algorithmic- and learning-based methods, to improve the inference accuracy of resistive IMC architectures.…”
Get full text

THEORETICAL AND METHODOLOGICAL ASPECTS OF USING INFORMATION ANDCOGNITIVE TECHNOLOGIES IN THE TRAINING OF TRANSPORT SPECIALISTS by Lavrentieva Olena, Krupskyi Oleksandr

“…The article addresses how to improve the professional training of specialists in the transport industry using information and cognitive technologies. …”
Get full text

Random Undersampled Digital Elevation Model Super-Resolution Based on Terrain Feature-Aware Deep Learning Network by Ziqiang Huo, Meng Xi, Jingyi He, Zhengjian Li, Jiabao Wen

“…The network integrates a deep residual module, a deformable convolution module, and an upsampling module, which are used to extract deep terrain features, extract adaptive terrain features, and improve the resolution of DEM data, respectively. …”
Get full text

Marine soundscape forecasting: A deep learning-based approach by Shashidhar Siddagangaiah

“…Despite the rapid development of anomaly detection algorithms and deep-learning models for forecasting, their application to marine soundscapes remains unexplored. …”
Get full text

Artificial Intelligence Performance in Cardiac Magnetic Resonance Strain Analysis for Aortic Stenosis: Validation with Echocardiography and Healthy Controls by Žygimantas Abramikas, Ieva Jasiukevičiūtė, Giedrė Balčiūnaitė, Sigita Glaveckaitė, Darius Palionis, Nomeda Valevičienė

“…However, the higher error rates in AS patients compared to controls underscore the need for more advanced AI algorithms to improve performance in cardiac pathology.…”
Get full text

Non-invasive urinary proteomic biomarkers for prognostic assessment in sepsis by Qingbo Zeng, Nianqing Zhang, Junjie Zeng, Lincui Zhong, Qingwei Lin, Longping He, Xiaomin Song, Jingchun Song

“…Abstract Early identification of the death risk of sepsis may improve short-term prognosis. The objective of this study was to identify urinary proteomic biomarkers and create a model to predict short-term outcomes in sepsis patients. …”
Get full text

Computed tomography-based radiomics model for predicting station 4 lymph node metastasis in non-small cell lung cancer by Yanru Kang, Mei Li, Xizi Xing, Kaixuan Qian, Hongxia Liu, Yafei Qi, Yanguo Liu, Yi Cui, Hua Zhang

“…This model serves as an effective auxiliary tool for clinical decision-making and has the potential to optimize treatment strategies and improve prognostic assessment for pN0-pN2 patients. …”
Get full text

IoT-driven smart agricultural technology for real-time soil and crop optimization by Hammad Shahab, Muhammad Naeem, Muhammad Iqbal, Muhammad Aqeel, Syed Sajid Ullah

“…It empowers farmers with data-driven insights to enhance productivity, optimize resource use, and improve sustainability. This scalable solution addresses modern agricultural challenges by reducing environmental impact and strengthening crop resilience. …”
Get full text

Machine Learning-Driven Prediction of One-Year Readmission in HFrEF Patients: The Key Role of Inflammation by Ma F, Hu Y, Han P, Qiu Y, Liu Y, Ren J

“…Integrating such models into clinical practice could improve risk stratification, reduce readmissions, and enhancing patient outcomes.Keywords: HFrEF, readmission, prediction model, machine learning…”
Get full text

Syn-MolOpt: a synthesis planning-driven molecular optimization method using data-derived functional reaction templates by Xiaodan Yin, Xiaorui Wang, Zhenxing Wu, Qin Li, Yu Kang, Yafeng Deng, Pei Luo, Huanxiang Liu, Guqin Shi, Zheng Wang, Xiaojun Yao, Chang-Yu Hsieh, Tingjun Hou

“…Abstract Molecular optimization is a crucial step in drug development, involving structural modifications to improve the desired properties of drug candidates. …”
Get full text

Poor Nutritional Status Increases Risk of Postoperative Adverse Events after Surgical Management of Traumatic Ankle Fracture by Sanket Mehta MD, Nicholas Danford MD

“…Patients missing baseline or comorbidity information, dead on arrival, or with a pilon fracture or stress fracture were excluded. Enhanced ICD-9 algorithms were used to identify patients with severe protein-calorie malnutrition and chronic deficiency. …”
Get full text

Machine Learning for the estimation of foliar nitrogen content in pineapple crops using multispectral images and Internet of Things (IoT) platforms by Jorge Enrique Chaparro, José Edinson Aedo, Felipe Lumbreras Ruiz

“…These results indicate that the integration of data from multiple sources and the use of machine learning models could greatly improve the precision of nitro-gen (N) diagnostics in pineapple crops, especially in real-time applications. …”
Get full text

Predictors of pathological complete response after total neoadjuvant treatment using short course radiotherapy for locally advanced rectal cancer by Haythem Yacoub, Yosr Zenzri, Dhouha Cherif, Hajer Ben Mansour, Najla Attia, Cyrine Mokrani, Khadija Ben Zid, Feryel Letaief, Nadia Maamouri, Amel Mezlini

“…Integrating these factors into personalized treatment algorithms may help optimize therapeutic strategies and improve outcomes for patients with LARC.…”
Get full text

Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach by Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi

“…Following hyperparameter tuning to improve the model's performance, the selected model was deployed in a real-world network environment to classify QoS into "Above Average," "Average," and "Below Average," categories. …”
Get full text

Fault diagnosis method of mine hoist main bearing with small sample based on VAE-WGAN by Fan JIANG, Hongyan SONG, Xi SHEN, Zhencai ZHU, Shuman CHENG

“…Furthermore, a fault diagnosis method based on CBAM-MobileNetV2 is proposed to achieve fault diagnosis of mine hoist main bearings under small sample data. At the algorithmic level, the Wasserstein distance metric is introduced to solve the problem of vanishing training gradients in generative adversarial networks. …”
Get full text

A machine learning-based depression risk prediction model for healthy middle-aged and older adult people based on data from the China health and aging tracking study by Fang Xia, Jie Ren, Linlin Liu, Yanyin Cui, Yufang He

“…BackgroundPredicting depression risk in adults is critical for timely interventions to improve quality of life. To develop a scientific basis for depression prevention, machine learning models based on longitudinal data that can assess depression risk are necessary.MethodsData from 2,331 healthy older adults who participated in the China Health and Retirement Longitudinal Study (CHARLS) from 2018 to 2020 were used to develop and validate the predictive model. …”
Get full text

Expectations and Requirements of Surgical Staff for an AI-Supported Clinical Decision Support System for Older Patients: Qualitative Study by Adriane Uihlein, Lisa Beissel, Anna Hanane Ajlani, Marcin Orzechowski, Christoph Leinert, Thomas Derya Kocar, Carlos Pankratz, Konrad Schuetze, Florian Gebhard, Florian Steger, Marina Liselotte Fotteler, Michael Denkinger

“… Abstract BackgroundGeriatric comanagement has been shown to improve outcomes of older surgical inpatients. Furthermore, the choice of discharge location, that is, continuity of care, can have a fundamental impact on convalescence. …”
Get full text

Development and Validation of Predictive Models for Non-Adherence to Antihypertensive Medication by Cristian Daniel Marineci, Andrei Valeanu, Cornel Chiriță, Simona Negreș, Claudiu Stoicescu, Valentin Chioncel

“…<i>Background and Objectives</i>: Investigating the adherence to antihypertensive medication and identifying patients with low adherence allows targeted interventions to improve therapeutic outcomes. Artificial intelligence (AI) offers advanced tools for analyzing medication adherence data. …”
Get full text

Breast lesion classification via colorized mammograms and transfer learning in a novel CAD framework by Abbas Ali Hussein, Morteza Valizadeh, Mehdi Chehel Amirani, Sedighe Mirbolouk

“…In a subsequent step, Machine Learning (ML) algorithms are employed to classify these tumors as malign or benign cases. …”
Get full text