A hybrid parallel convolutional spiking neural network for enhanced skin cancer detection by K. Anup Kumar, C. Vanmathi

“…Furthermore, the system has a false positive rate (FPR) of 10.7% and a positive predictive value (PPV) of 90.8%, demonstrating its capacity to reduce wrong diagnosis while prioritizing true positive instances. PCSN-Net outperforms various complex algorithms, including EfficientNet, DenseNet, and Inception-ResNet-V2, despite preserving effective training and inference times. …”
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A framework of partial discharge detection for gas-insulated switchgear based on LSTM and multi-head attention by YANG Zhengsheng, LIU Fang

“…Secondly， the self-attention mechanism identified important information between input and output sequences， while the multi-head self-attention network captured high-order features of faulty PRPD. …”
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Deep reinforcement learning for conservation decisions by Marcus Lapeyrolerie, Melissa S. Chapman, Kari E. A. Norman, Carl Boettiger

“…Ecologists must establish a better understanding of how these algorithms work and fail if we are to realize this potential and avoid the pitfalls such a transition would bring. …”
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Review of Surface-Defect Detection Methods for Industrial Products Based on Machine Vision by Quan Wang, Mengnan Wang, Jiadong Sun, Deji Chen, Pei Shi

“…Machine learning methods are divided into point-distance-based, hyperplane-based, tree-based, and neural network-based classification algorithms. Deep learning models are classified into two types: accuracy-oriented and efficiency-oriented. …”
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Anatomical Parameter-driven Volumetric Modulated Arc Therapy Optimization in Left-sided Breast Cancer: A Machine Learning Framework for Lung Dose Prediction by Mukesh Kumar Zope, Deepali Patil, Rishi Raj, Seema Devi, Richa Madhawi

“…In addition, we established predictive models for lung doses utilizing the Least Absolute Shrinkage and Selection Operator, ridge, and linear regression algorithms while also evaluating dosimetric parameters for both the PTV and the organs at risk (OARs). …”
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Studies on in-flight aircraft rerouting by M. A. Kiselev, Yu. S. Kalyuzhny, A. V. Karpov, S. F. Borodkin

“…When determining alternatives to avoid an obstacle, as well as while implementing the selected route for avoiding action, the crew makes errors due to the increased psychophysiological load and lack of time. …”
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LSD-Det: A Lightweight Detector for Small Ship Targets in SAR Images by Zhen Wang, Bin Qin, Shang Gao

“…However, ship targets in SAR images are often small, have blurred edges, and suffer from strong background interference, making it difficult for traditional detection algorithms to balance accuracy and real-time performance. …”
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Application of artificial intelligence in triage in emergencies and disasters: a systematic review by Azadeh Tahernejad, Ali Sahebi, Ali Salehi Sahl Abadi, Mehdi Safari

“…Results The search identified 2,630 articles, narrowing down to 19 high-quality studies on AI in triage, which improved patient care through optimized resource management and real-time data transmission. AI algorithms like OpenPose and YOLO enhanced efficiency in mass casualty incidents, while e-triage systems allowed for continuous vital sign monitoring and faster triaging. …”
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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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Application of machine learning and temporal response function modeling of EEG data for differential diagnosis in primary progressive aphasia by Heather Dial, Lokesha S. Pugalenthi, G. Nike Gnanateja, Junyi Jessy Li, Maya L. Henry

“…The resulting TRFs for channel Cz were used as input to machine learning algorithms for classification of PPA vs. healthy controls, three-way classification by PPA subtype, classification of a single PPA subtype relative to the other two (e.g., semantic vs. logopenic/nonfluent variant), and pairwise classification by PPA subtype. …”
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Molecular biomarkers in salivary diagnostic materials: Point-of-Care solutions — PoC-Diagnostics and -Testing by Ziyad S. Haidar

“…Recent advancements in nanomaterials and fabrication techniques, coupled with emerging computational approaches such as artificial intelligence (AI), machine learning, and deep learning, have revolutionized high-throughput screening and laboratory automation. AI-driven algorithms now process and analyze salivary proteomic data with remarkable accuracy, identifying patterns and biomarkers associated with diseases such as oral cancer at an early stage. …”
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Exploring Migraine Pathogenesis: Transcriptomic Insights and Pathway Analysis in Nitroglycerin-Induced Rat Model by Qiao-Wen Chen, Run-Tian Meng, Chih-Yuan Ko

“…The control group received saline, while the migraine model group received nitroglycerin (NTG) to induce migraines over four weeks. …”
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Remote Monitoring of Sympathovagal Imbalance During Sleep and Its Implications in Cardiovascular Risk Assessment: A Systematic Review by Valerie A. A. van Es, Ignace L. J. de Lathauwer, Hareld M. C. Kemps, Giacomo Handjaras, Monica Betta

“…This review evaluates non-invasive technologies, metrics, and algorithms for tracking nocturnal autonomic nervous system (ANS) activity, assessing their CV relevance and feasibility for integration into RPM systems. …”
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Impact of Buses, Taxis, Passenger Cars, and Traffic Infrastructure on Average Travel Speed by José Gerardo Carrillo-González, Jorge López-Ortega, Jacobo Sandoval-Gutiérrez, Francisco Perez-Martinez

“…First, we developed a tool featuring algorithms that simulate ordinary overtaking and car-following behaviors, along with controls for setting vehicles’ actions, particularly buses’ and taxis’ stops. …”
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Opportunities and Challenges of Brain-on-a-Chip Interfaces by Wenwei Shao, Weiwei Meng, Jiachen Zuo, Xiaohong Li, Dong Ming

“…Addressing these limitations could offer insights into emergent intelligence while enabling next-generation biocomputing solutions.…”
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Determination of indications for the choice of the preparation method of the root canal system with rotation and reciprocation instruments by I. V. Pyatkova, L. Yu. Orekhova, T. V. Porkhun, A. V. Silin

“…Compliance with the algorithms of endodontic treatment in most cases ensures the quality of treatment. …”
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Capturing spatiotemporal variation in salt marsh belowground biomass, a key resilience metric, through geoinformatics by Kyle D. Runion, Deepak R. Mishra, Merryl Alber, Mark A. Lever, Jessica L. O'Connell

“…We used the BERM machine learning algorithms to evaluate how variables relating to biological, climatic, hydrologic, and physical attributes covaried with these BGB observations. …”
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Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction by Vitalii Kapitan, Michael Choi

“…By integrating simulated annealing into the LM approach, we propose LM SA, a variant designed to improve convergence stability while facilitating more efficient exploration of complex landscapes. …”
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Development and evaluation of deep neural networks for the classification of subtypes of renal cell carcinoma from kidney histopathology images by Amit Kumar Chanchal, Shyam Lal, Shilpa Suresh

“…Recently, deep learning algorithms have gained significant attention in histopathology image analysis. …”
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Using Machine Learning and Nationwide Population-Based Data to Unravel Predictors of Treated Depression in Farmers by Pascal Petit, Vincent Bonneterre, Nicolas Vuillerme

“…To complement these traditional studies, big data and machine learning (ML) can advantageously be harnessed. While ML algorithms have shown high accuracy in identifying depression predictors in mental health research, no study has yet applied ML in farmers. …”
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