Artificial intelligence and machine learning techniques for power quality event classification: a focused review and future insights by Indu Sekhar Samanta, Sarthak Mohanty, Shubhranshu Mohan Parida, Pravat Kumar Rout, Subhasis Panda, Mohit Bajaj, Vojtech Blazek, Lukas Prokop, Stanislav Misak

“…This paper explores the challenges associated with AI-based PQ analysis, including the need for large datasets, overfitting issues, and the lack of interpretability in complex models. Future research directions are outlined, emphasizing the development of hybrid models, explainable AI systems, and real-time adaptability to dynamic grid conditions. …”
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Advancing precision medicine: the transformative role of artificial intelligence in immunogenomics, radiomics, and pathomics for biomarker discovery and immunotherapy optimization by Luchen Chang, Jiamei Liu, Jialin Zhu, Shuyue Guo, Yao Wang, Zhiwei Zhou, Xi Wei

“…Despite challenges such as data quality, model interpretability, integration of multi-modal data, and privacy protection, the ongoing advancements in AI, coupled with interdisciplinary collaboration, are poised to further enhance AI’s roles in biomarker discovery and immunotherapy response prediction. …”
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Topically Applied Connective Tissue Growth Factor/CCN2 Improves Diabetic Preclinical Cutaneous Wound Healing: Potential Role for CTGF in Human Diabetic Foot Ulcer Healing by F. R. Henshaw, P. Boughton, L. Lo, S. V. McLennan, S. M. Twigg

“…Endogenous wound fluid CTGF protein rate of increase in human diabetic foot ulcers correlated positively with foot ulcer healing rate (r=0.406; P<0.001). Conclusions/Interpretation. These data collectively increasingly substantiate a functional role for CTGF in human diabetic foot ulcers.…”
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Differential diagnosis of iron deficiency anemia from aplastic anemia using machine learning and explainable Artificial Intelligence utilizing blood attributes by B. S. Dhruva Darshan, Niranjana Sampathila, G. Muralidhar Bairy, Srikanth Prabhu, Sushma Belurkar, Krishnaraj Chadaga, S. Nandish

“…As of today, there are no studies which use Interpretable Artificial Intelligence to perform the above differential diagnosis. …”
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Entropy-extreme concept of data gaps filling in a small-sized collection by Viacheslav Kovtun, Krzysztof Grochla, Mohammed Al-Maitah, Saad Aldosary, Oleksii Kozachko

“…In the case of addressing missing values in input data, these are interpreted as results of transforming a sequence of independent stochastic vectors introduced into a model structurally identical to that formalized for filling gaps in output data. …”
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LSN-GTDA: Learning Symmetrical Network via Global Thermal Diffusion Analysis for Pedestrian Trajectory Prediction in Unmanned Aerial Vehicle Scenarios by Ling Mei, Mingyu Fu, Bingjie Wang, Lvxiang Jia, Mingyu Yu, Yu Zhang, Lijun Zhang

“…Additionally, we propose a novel thermal diffusion process, based on signal and system theory, which manages uncertainty by utilizing the full response and providing interpretability to the network. Experimental results demonstrate that the LSN-GTDA method outperforms state-of-the-art approaches on benchmark datasets such as SDD and ETH-UCY, validating its effectiveness in addressing the multimodal uncertainty of pedestrian trajectory prediction.…”
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Healthcare assessment tools—a valid source of data for pre-hospital care? Usability for ensuring medical care in the event of a disaster by Robert Konrad, Robert Konrad, Denise Schuster, HJ Heppner, HJ Heppner

“…Without adaptation they cannot be used at all or only after concerted efforts to interpret the needs for the care of vulnerable groups in a non-clinical context.DiscussionAn improved use of individual medical data in disaster and civil protection offers many advantages in prevention, diagnostics, therapy and care in the context of disaster medicine, and not only from an ethical point of view. …”
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Nonparametric analysis of inter‐individual relations using an attention‐based neural network by Takashi Morita, Aru Toyoda, Seitaro Aisu, Akihisa Kaneko, Naoko Suda‐Hashimoto, Ikuma Adachi, Ikki Matsuda, Hiroki Koda

“…In this study, researchers explored a nonparametric analysis of inter‐individual relations using a neural network with the attention mechanism, which plays a central role in natural language processing. The high interpretability of the attention mechanism and flexibility of the entire neural network allow for automatic detection of inter‐individual relations included in the raw data, without requiring prior knowledge/assumptions about what modes/types of relations are included in the data. …”
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Permafrost Dynamics Observatory: 3. Remote Sensing Big Data for the Active Layer, Soil Moisture, and Greening and Browning by Elizabeth Wig, Kevin Schaefer, Roger Michaelides, Richard Chen, Leah K. Clayton, Brittany Fager, Lingcao Huang, Andrew D. Parsekian, Howard Zebker, Yingtong Zhang, Yuhuan Zhao

“…We analyze the distributions of these variables and use a space‐for‐time substitution to enable interpretation of the effects of climate trends. Higher soil volumetric water content (VWC) is associated with lower ALT and subsidence, suggesting that Arctic soil may become drier as the climate warms. …”
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Seismic Imaging of Halokinetic Sequences and Structures With High‐Resolution, Dual‐Element Acquisition, and Processing: Applications to the Gassum Structure in Eastern Jutland, Den... by M. Westgate, K. Kucinskaite, E. Konstantinidis, A. Malehmir, M. Papadopoulou, U. Gregersen, M. Keiding, M. Bjerager

“…High‐resolution seismic data processing and interpretation reveals a skewed dome structure with steeper flanks on the western and northern sides, characterized by faults and stratigraphic thinning. …”
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Hyperoxia shows duration-dependent effects on the lengths of cell cycle phases in fetal cortical neural stem cells by Jennifer Lanto, Monika Maria Nicole Vehlken, Valeriia Abramenko, Alexander Storch, Alexander Storch, Franz Markert

“…These altered oxygen conditions lead to adaptive changes in NSCs which complicate the interpretation of in vitro data. However, the underlying adaption dynamics remain largely enigmatic. …”
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Integrating Explainable Artificial Intelligence With Advanced Deep Learning Model for Crowd Density Estimation in Real-World Surveillance Systems by Sultan Refa Alotaibi, Hanan Abdullah Mengash, Mohammed Maray, Faiz Abdullah Alotaibi, Abdulwhab Alkharashi, Ahmad A. Alzahrani, Moneerah Alotaibi, Mrim M. Alnfiai

“…Explainable Artificial Intelligence (XAI) improves the interpretability and transparency of crowd management methods. …”
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Quantifying observer variance in expansive monitoring program indicator data with heterogeneous-variance mixed-effects models by Leah T. Dreesmann, Timothy R. Johnson, Jason W. Karl

“…Reliable metadata about observers and the program history is also required to build the model and interpret the results. The model could also be expanded to answer additional questions about the influence of observers on monitoring data.…”
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Study of Shale Gas Source Rock S-Wave Structure Characteristics via Dense Array Ambient Noise Tomography in Zhangjiakou, China by Si Chen, Zhanwu Lu, Haiyan Wang, Qingyu Wu, Wei Cai, Guowei Wu, Guangwen Wang

“…Integration of the velocity model with regional geological data facilitated a comprehensive interpretation and structural analysis of the prospective shale gas zone. …”
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Forest Fire Clustering: A Novel Tool for Identifying Star Members of Clusters by Xingyin Wei, Jing Chen, Su Zhang, Feilong He, Yunbo Zhao, Xuran He, Yongjie Fang, Xinhao Chen, Hao Yang

“…In the era of a data-driven landscape, the development of an efficient and interpretable method has become a pivotal tool for robustly identifying memberships of clusters. …”
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Olfaction-based learned preference assessment without the use of motivational fear or motivational weight loss by Sara E. Moss, Ekaterina S. McCurdy, Natalya N. Thomas, Danielle Gulick, Angela M. Poff, Dominic P. D'Agostino

“…The C57BL/6 J mouse, a widely used laboratory strain, sporadically develops auditory and visual impairments that complicate interpretation. In this study, we establish an olfaction-based learned preference protocol designed to evaluate learning ability independent of fear responses, motivational weight loss, or visual cues in C57BL/6 J mice.Methods and resultsLeveraging the species’ natural preference for sweet flavors, we tested different sweeteners and confirmed their passive preference for sucrose was more robust than for saccharin or sucralose. …”
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Liposarcoma in the Inguinal Canal: Challenges in Preoperative Diagnosis and Importance of Routine Pathological Examination of “Hernia Sacs” by Christopher A. Febres-Aldana, Jin Min, Marc Rafols, Irvin Willis, John Alexis

“…A follow-up CT scan exposed a fatty tumor in the retroperitoneum of the second patient. Careful interpretation of imaging studies in patients with fatty inguinal masses is mandatory to rule out a retroperitoneal or intraperitoneal component. …”
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Quantitative Representation of Autonomous Driving Scenario Difficulty Based on Adversarial Policy Search by Shuo Yang, Caojun Wang, Yuanjian Zhang, Yuming Yin, Yanjun Huang, Shengbo Eben Li, Hong Chen

“…The result analysis shows that the proposed algorithm can generate reasonable and interpretable scenarios with high discrimination and can provide quantifiable difficulty representation without any expert logic rule design. …”
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Diagnostic efficiency of exome-based sequencing in pediatric patients with epilepsy by Huafang Zou, Huafang Zou, Qian Zhang, Jianxiang Liao, Jianxiang Liao, Dongfang Zou, Zhanqi Hu, Bing Li, Li Chen, Jialun Wen, Xia Zhao, Victor Wei Zhang, Dezhi Cao, Dezhi Cao

“…Single-nucleotide variants (SNVs) and copy number variants (CNVs) were interpreted based on each patient’s phenotypic presentation. …”
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Influenza A virus hemagglutinin: from classical fusion inhibitors to proteolysis targeting chimera-based strategies in antiviral drug discovery by Francisco Javier Hermoso-Pinilla, Aitor Valdivia, María-José Camarasa, Tiziana Ginex, Francisco Javier Luque

“…Furthermore, this study also aims to highlight the efforts made in exploiting the structural information in conjunction with molecular modeling techniques to discern the mechanism of action of the fusion inhibitors and to assist the design and interpretation of structure-activity relationships of novel lead compounds will be highlighted. …”
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