Face Anti-Spoofing Based on Deep Learning: A Comprehensive Survey by Huifen Xing, Siok Yee Tan, Faizan Qamar, Yuqing Jiao

“…Finally, it summarizes the current research challenges and future directions for FAS, such as its limited generalization for unknown attacks, the insufficient multi-modal research, the spatiotemporal efficiency of algorithms, and unified detection for presentation attacks and deepfakes. …”
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RODA-OOD: Robust Domain Adaptation from Out-of-Distribution Data by Jaekyun Jeong, Mangyu Lee, Sunguk Yun, Keejun Han, Jungeun Kim

“…By dynamically adjusting the threshold for OOD detection, the proposed method effectively filters out OOD data, allowing the model to focus on relevant target data. …”
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Three-Band Spectral Camera Structure Design Based on the Topology Optimization Method by Kai Hu, Yuzhu Wan, Jialong Guo, Chunbo Zou, Xiangtao Zheng

“…Using a combination of density-based topology optimization and multi-objective genetic algorithms in parametric optimization, redundant structures were removed to achieve a lightweight design. …”
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Machine Learning Approaches for Real-Time Mineral Classification and Educational Applications by Paraskevas Tsangaratos, Ioanna Ilia, Nikolaos Spanoudakis, Georgios Karageorgiou, Maria Perraki

“…The main objective of the present study was to develop a real-time mineral classification system designed for multiple detection, which integrates classical computer vision techniques with advanced deep learning algorithms. …”
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A Practical Methodology for Accuracy and Quality Evaluation of Structured Light Systems in Automotive Inspection by Antonio Lagudi, Umberto Severino, Loris Barbieri, Fabio Bruno

“…It also demonstrated the ability to quantify improvements obtained through image enhancement algorithms. These results confirm the methodology’s capacity to expose critical performance trade-offs and guide optimization choices in practical inspection scenarios. …”
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Performance of Natural Language Processing versus International Classification of Diseases Codes in Building Registries for Patients With Fall Injury: Retrospective Analysis by Atta Taseh, Souri Sasanfar, Michelle Chan, Evan Sirls, Ara Nazarian, Kayhan Batmanghelich, Jonathan F Bean, Soheil Ashkani-Esfahani

“…The highest F1ICD ConclusionsOur findings showed promising performance with higher accuracy of NLP algorithms compared to the conventional method for detecting fall occurrence and mechanism in developing disease registries using clinical notes. …”
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Immune checkpoint inhibitor-associated autoimmune encephalitis and other neurological immune-mediated adverse events: a pharmacovigilance study using the FAERS and JADER by Xiaomeng Di, Xiaohong Shi, Feng Gai, Jiawei Wang

“…ICIs, including pembrolizumab, nivolumab, atezolizumab, ipilimumab, and durvalumab, were identified among the top 30 agents in both databases, demonstrating significant signals across all 4 algorithms. Except for noninfectious myelitis, acute disseminated encephalomyelitis, and multiple sclerosis, positive signals were detected in all other preferred terms (PTs). …”
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Machine learning–based feature prediction of convergence zones in ocean front environments by Weishuai Xu, Lei Zhang, Hua Wang

“…Out of 24 machine learning algorithms tested through K-fold cross-validation, the multilayer perceptron–random forest hybrid demonstrated the highest accuracy, showing its superiority in predicting the convergence zone within a complex ocean front environment. …”
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Clinical Utility of Bladder Cancer Biomarkers by Laura Maria Krabbe, Georgios Gakis, Yair Lotan

“…Prognostic and predictive biomarkers have the potential to fundamentally change bladder cancer treatment algorithms, which may result in improved patient comfort and oncological outcomes and may also decrease the socioeconomic burden of the disease. …”
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THE CURRENT STATE OF ARTIFICIAL INTELLIGENCE IN RADIOLOGY – A REVIEW OF THE BASIC CONCEPTS, APPLICATIONS, AND CHALLENGES by Mariana Yordanova

“…CNNs excel in tasks like lesion detection and disease classification, aiding radiologists in diagnosing conditions more accurately. …”
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Explainable Machine Learning Models for Colorectal Cancer Prediction Using Clinical Laboratory Data by Rui Li MS, Xiaoyan Hao MS, Yanjun Diao MD, Liu Yang MS, Jiayun Liu MD

“…Incorporating stool miR-92a detection into the model further improved diagnostic performance. …”
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AstroM3: A Self-supervised Multimodal Model for Astronomy by M. Rizhko, J. S. Bloom

“…In particular we show the efficacy of using the learned embeddings to identify misclassifications, for similarity search, and for anomaly detection. One surprising highlight is the “rediscovery” of Mira subtypes and two rotational variable subclasses using manifold learning and dimensionality reduction algorithms. …”
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Photodiagnosis and photodynamic recognition of cervical cancer with SEM and AFM images. by Sevcan Aytaç, Gürkan Özbey

“…Continuation of early detection research is important to reduce the number of deaths due to cancer. …”
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Prevalence of tuberculosis, HIV and respiratory symptoms in two Zambian communities: implications for tuberculosis control in the era of HIV. by Helen Ayles, Albertus Schaap, Amos Nota, Charalambos Sismanidis, Ruth Tembwe, Petra De Haas, Monde Muyoyeta, Nulda Beyers, Peter Godfrey-Faussett for the ZAMSTAR Study Team

“…Epidemiological studies can inform screening algorithms for both detection and prevention of active tuberculosis.…”
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Mutation Scanning in Wheat by Exon Capture and Next-Generation Sequencing. by Robert King, Nicholas Bird, Ricardo Ramirez-Gonzalez, Jane A Coghill, Archana Patil, Keywan Hassani-Pak, Cristobal Uauy, Andrew L Phillips

“…After testing different mapping algorithms and settings, candidate SNPs were identified by mapping to the IWGSC wheat Chromosome Survey Sequences. …”
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Artificial Intelligence and ECG: A New Frontier in Cardiac Diagnostics and Prevention by Dorota Bartusik-Aebisher, Kacper Rogóż, David Aebisher

“…<b>Conclusions</b>: Modern AI algorithms—especially deep neural networks—show promise in detecting arrhythmias, heart failure, prolonged QT syndrome, and other cardiovascular conditions. …”
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Brain computer interface based emotion recognition with error analysis and challenges: an interdisciplinary review by Niharika Gudikandula, Ravichander Janapati, Rakesh Sengupta, Sridhar Chintala

“…The review emphasizes the need to understand and address these error sources to develop robust BCI-based emotion recognition systems that can provide accurate and reliable emotion detection in various contexts.…”
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Artificial intelligence in pancreatic intraductal papillary mucinous neoplasm imaging: A systematic review. by Muhammad Ibtsaam Qadir, Jackson A Baril, Michele T Yip-Schneider, Duane Schonlau, Thi Thanh Thoa Tran, C Max Schmidt, Fiona R Kolbinger

“…Methodologically, convolutional neural network (CNN)-based algorithms were most commonly used. Thematically, most studies reported models augmenting differential diagnosis (n = 9,36%) or risk stratification (n = 10,40%) rather than IPMN detection (n = 5,20%) or IPMN segmentation (n = 2,8%). …”
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A deep learning framework for predicting disease-gene associations with functional modules and graph augmentation by Xianghu Jia, Weiwen Luo, Jiaqi Li, Jieqi Xing, Hongjie Sun, Shunyao Wu, Xiaoquan Su

“…ModulePred performs graph augmentation on the protein interaction network using L3 link prediction algorithms. It builds a heterogeneous module network by integrating disease-gene associations, protein complexes and augmented protein interactions, and develops a novel graph embedding for the heterogeneous module network. …”
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Microcephalic osteodysplastic primordial dwarfism type II in four Indian children with PCNT variants by Amit Singh, Mahak Garg, Mohammed Shariq, Preeti Khetarpal, Inusha Panigrahi

“…Data were analyzed using standard bioinformatic algorithms and possible causal variants identified. …”
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