Harnessing AI forward and backward chaining with telemetry data for enhanced diagnostics and prognostics of smart devices by Muhammad Shoaib Farooq, Rizwan Pervez Mir, Atif Alvi, Kilian Tutusaus, Eduardo Garcia Villena, Fadwa Alrowais, Hanen Karamti, Imran Ashraf

“…Accurate early diagnosis and prediction of potential failures have the capability to greatly improve maintenance efficiency, minimize downtime, and optimize cost.…”
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Feasibility of Implementing Motion-Compensated Magnetic Resonance Imaging Reconstruction on Graphics Processing Units Using Compute Unified Device Architecture by Mohamed Aziz Zeroual, Natalia Dudysheva, Vincent Gras, Franck Mauconduit, Karyna Isaieva, Pierre-André Vuissoz, Freddy Odille

“…Motion correction in magnetic resonance imaging (MRI) has become increasingly complex due to the high computational demands of iterative reconstruction algorithms and the heterogeneity of emerging computing platforms. …”
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Predictive Modeling of Acute Respiratory Distress Syndrome Using Machine Learning: Systematic Review and Meta-Analysis by Jinxi Yang, Siyao Zeng, Shanpeng Cui, Junbo Zheng, Hongliang Wang

“…Early detection and accurate prediction of ARDS can significantly improve patient outcomes. While machine learning (ML) models are increasingly being used for ARDS prediction, there is a lack of consensus on the most effective model or methodology. …”
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Impact of a massive earthquake on adherence to antiretroviral therapy, mental health, and treatment failure among people living with HIV in Nepal. by Bharat Singh Negi, Sunil Kumar Joshi, Minato Nakazawa, Tomohiro Kotaki, Anup Bastola, Masanori Kameoka

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Breaks in the Arctic ice cover: from observations to predictions by A. A. Ershova, L. N. Dyment, T. A. Alekseeva

“…Breaks (ruptures) and cracks is the distinguishing feature of any ice cover in the Arctic seas during the cold season and in the whole Arctic Basin throughout a year. The formation of them is a consequence of macro-deformation of the ice thickness. …”
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Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach by Lingyu Xu, Siqi Jiang, Chenyu Li, Xue Gao, Chen Guan, Tianyang Li, Ningxin Zhang, Shuang Gao, Xinyuan Wang, Yanfei Wang, Lin Che, Yan Xu

“…Predictive models were constructed using eight machine learning algorithms and two ensemble algorithms, with the optimal model identified through AUROC. …”
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Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting. by Nicole A Doria-Rose, Han R Altae-Tran, Ryan S Roark, Stephen D Schmidt, Matthew S Sutton, Mark K Louder, Gwo-Yu Chuang, Robert T Bailer, Valerie Cortez, Rui Kong, Krisha McKee, Sijy O'Dell, Felicia Wang, Salim S Abdool Karim, James M Binley, Mark Connors, Barton F Haynes, Malcolm A Martin, David C Montefiori, Lynn Morris, Julie Overbaugh, Peter D Kwong, John R Mascola, Ivelin S Georgiev

“…Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and enable serologic analysis for entire cohorts. …”
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The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review by Norah Hamad Alhumaidi, Doni Dermawan, Hanin Farhana Kamaruzaman, Nasser Alotaiq

“…A substantial portion of studies (n=38, 67%) focused on improving clinical decision-making, patient stratification, and treatment optimization. …”
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Automated Quality Control of Cleaning Processes in Automotive Components Using Blob Analysis by Simone Mari, Giovanni Bucci, Fabrizio Ciancetta, Edoardo Fiorucci, Andrea Fioravanti

“…The LoG and DoG methods were more prone to spurious detections, while DoH demonstrated intermediate performance but struggled with reflective surfaces. …”
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A novel hybrid deep learning approach for super-resolution and objects detection in remote sensing by Muhammad Asif, Mohammad Abrar, Faizan Ullah, Abdu Salam, Farhan Amin, Isabel de la Torre, Mónica Gracia Villar, Helena Garay, Gyu Sang Choi

“…Advanced StyleGAN enhances image resolution, facilitating the detection of small and occluded objects, while Swin Transformer employs hierarchical attention mechanisms for effective feature extraction. …”
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Treatment Strategies and Prognostic Outcomes in Acute Limb Ischemia: A Systematic Review and Meta-Analysis Comparing Thrombolytic Therapy and Open Surgical Interventions by Mircea Cătălin Coșarcă, Nicolae Alexandru Lazăr, Suzana Vasilica Șincaru, Bogdan Corneliu Bandici, Eduard Costin Argatu, Cosmin Carașca, Ráduly Gergő, Dorin Constantin Dorobanțu, Cristian Trâmbițaș, Adrian Vasile Mureșan

“…Future research should focus on refining treatment algorithms, investigating novel thrombolytic agents, and expanding the role of minimally invasive techniques to improve long-term outcomes while mitigating complications such as bleeding and reperfusion injuries.…”
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Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer by Junyi Li, Shixin Li, Dongpo Zhang, Yibing Zhu, Yue Wang, Xiaoxiao Xing, Juefei Mo, Yong Zhang, Daixiang Liao, Jun Li

“…To address these limitations, this study systematically analyzed RNA-seq high-throughput data and combined 10 machine learning algorithms to construct 117 models. The optimal algorithm combination, StepCox[both] and ridge regression, was identified, and an immune-related gene signature (IRGS) composed of 12 genes was developed. …”
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Frailty in older adults patients: a prospective observational cohort study on subtype identification by Zhikai Yang, Chen Ji, Ting Wang, Wei He, Yuhao Wan, Min Zeng, Di Guo, Lingling Cui, Hua Wang

“…This study applied the K-means clustering algorithm to analyze 27 variables, determining the optimal cluster number using the Elbow method and Silhouette coefficient. …”
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Hierarchical Sensing Framework for Polymer Degradation Monitoring: A Physics-Constrained Reinforcement Learning Framework for Programmable Material Discovery by Xiaoyu Hu, Xiuyuan Zhao, Wenhe Liu

“…Our method combines three key innovations: (1) a dual-channel sensing architecture that fuses spectroscopic signatures from Graph Isomorphism Networks with temporal degradation patterns captured by transformer-based models, enabling comprehensive molecular state detection across multiple scales; (2) a physics-constrained policy network that ensures sensor measurements adhere to thermodynamic principles while optimizing the exploration of degradation pathways; and (3) a hierarchical signal processing system that balances multiple sensing modalities through adaptive weighting schemes learned from experimental feedback. …”
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Thematic Analysis of Clinician Documentation Surrounding Treatment Discussions and Decision‐Making in Patients With Desmoid Tumors by Victoria Wytiaz, Tianyi Wang, Scott Schuetze, Nina J. Francis‐Levin, Rashmi Chugh

“…The emergent themes provide novel guidance and support for optimizing treatment discussions and decisions. More robust community peer support groups specific to patients with desmoid tumors and clinician “support groups” may provide a way for both patients and clinicians practicing in a disease state with uncertainty to share experiences and improve resilience. …”
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IoT Based Health Monitoring with Diet, Exercise and Calories recommendation Using Machine Learning by Muhammad Hassaan Naveed, Omar Bin Samin, Muhammad Bilal, Mustehsum Waseem

“…Additionally, machine learning algorithms recommend tailored exercise, diet type, Basal Metabolic Rate (BMR), and daily caloric intake based on individual member data. …”
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Robust zero-watermarking for color images using hybrid deep learning models and encryption by Hager A. Gharib, Noha M. M. Abdelnapi, Khalid M. Hosny

“…Traditional zero-watermarking techniques often struggle to maintain resilience against geometric and signal processing attacks while ensuring high security and imperceptibility. …”
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Lightweight Brain Tumor Segmentation Through Wavelet-Guided Iterative Axial Factorization Attention by Yueyang Zhong, Shuyi Wang, Yuqing Miao, Tao Zhang, Haoliang Li

“…Conclusions: This study underscores the advantages of integrating frequency-domain analysis with optimized attention mechanisms, paving the way for scalable, high-performance medical image segmentation algorithms with broader clinical diagnostic applications.…”
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Artificial Intelligence and Smart Technologies in Safety Management: A Comprehensive Analysis Across Multiple Industries by Jiyoung Park, Dongheon Kang

“…AI-driven solutions, such as predictive analytics, machine learning algorithms, IoT sensor integration, and digital twin models, are shown to proactively identify and mitigate potential hazards, optimize energy consumption, and enhance operational efficiency. …”
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Radiology AI and sustainability paradox: environmental, economic, and social dimensions by Burak Kocak, Andrea Ponsiglione, Valeria Romeo, Lorenzo Ugga, Merel Huisman, Renato Cuocolo

“…Socially, AI risks perpetuating healthcare disparities through biases in algorithms and unequal access to technology. On the other hand, AI has the potential to improve sustainability in healthcare by reducing low-value imaging, optimizing resource allocation, and improving energy efficiency in radiology departments. …”
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