Identification and validation of an explainable machine learning model for vascular depression diagnosis in the older adults: a multicenter cohort study by Ran Zhang, Tian Li, Fan Fan, Haoying He, Liuyi Lan, Dong Sun, Zhipeng Xu, Sisi Peng, Jing Cao, Juan Xu, Xiaoxiang Peng, Ming Lei, Hao Song, Junjian Zhang

“…The final model also achieved, and marginally exceeded, clinician-level diagnostic performance. …”
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Low-dimensional multiscale fast SAR image registration method by Jiamu Li, Wenbo Yu, Zijian Wang, Jiaxin Xie, Xiaojie Zhou, Yabo Liu, Zhongjun Yu, Meng Li, Yi Wang

“…Experiments on raw SAR images with neither prior information nor any pre-processing measure like terrain correction and de-speckling demonstrate the efficacy of the proposed method over other state-of-the-art SAR image registration algorithms. Some analyses concerning the factors affecting feature matching and invariance of PC map and MIM are also studied.…”
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A lightweight knowledge graph-driven question answering system for field-based mineral resource survey by Mingguo Wang, Chengbin Wang, Jianguo Chen, Bo Wang, Wei Wang, Xiaogang Ma, Jiangtao Ren, Zichen Li, Yicai Ye, Jiakai Zhang, Yue Wang

“…In this study, we proposed and built a workflow that employs knowledge graph techniques, deep learning, question templates, and matching algorithms to provide a lightweight question-answering service for field-based geologists involved in mineral resource surveys. …”
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Challenges and inequalities in the management of financing the tasks of local government units: a critical analysis by Arkadiusz Ciach

“…Do the currently used algorithms for the distribution of subsidies reflect the real needs of local government units, and, as a result, there is an optimal allocation of public funds? …”
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The impact of using advanced computer programs on the interior architectural design of the home أثر استخدام برامج الحاسوب المتقدمه في التصميم المعماري الداخلي للمسكن... by Mohamed Abdel Hamed

“…This study examines the evolution of advanced computer software in its various versions, stages, techniques, parametric design, algorithms, and BIM technologies, as well as their positive impacts, advantages, and the challenges they entail in enhancing interior design quality and, consequently, the quality of life within residential buildings. …”
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Optimal vaccination model of airborne infection under variable humidity and demographic heterogeneity for hybrid fractional operator technique by Saima Rashid, Ilyas Ali, Nida Fatima, Tehreem Fatima, Fekadu Tesgera Agam, Sayed K. Elagan

“…In order to lessen the infections, time-dependent control factors are also implemented. The optimality criteria are produced by applying Pontryagin’s maximal argument to prove the validity of the most effective control. …”
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Global overview of usable Landsat and Sentinel-2 data for 1982–2023Dryad by Katarzyna Ewa Lewińska, Stefan Ernst, David Frantz, Ulf Leser, Patrick Hostert

“…To facilitate data exploration the data availability records are accompanied by a growing season information, also sampled at the pixel-level in regular intervals with 0.18° spacing. …”
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Diagnosis methods for pancreatic cancer with the technique of deep learning: a review and a meta-analysis by Yuanbo Bi, Dongrui Li, Ruochen Pang, Chengxv Du, Da Li, Xiaoyv Zhao, Haitao Lv

“…Inclusion criteria were studies involving PDAC patients, using deep learning algorithms for diagnosis evaluation, using histopathological results as the reference standard, and having sufficient data. …”
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Trust in Artificial Intelligence–Based Clinical Decision Support Systems Among Health Care Workers: Systematic Review by Hein Minn Tun, Hanif Abdul Rahman, Lin Naing, Owais Ahmed Malik

“…Barriers to trust included algorithmic opacity, insufficient training, and ethical challenges, while enabling factors for health care workers’ trust in AI-CDSS tools were transparency, usability, and clinical reliability. …”
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AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector by Şenda Yıldırım, Ahmet Deniz Yücekaya, Mustafa Hekimoğlu, Meltem Ucal, Mehmet Nafiz Aydin, İrem Kalafat

“…The enhanced service appointment scheduling, combined with timely vehicle maintenance, also contributed to reducing potential accident risks. …”
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Low-cost phone-based LiDAR scanning technology provides sub-centimeter accuracy when measuring the main dimensions of motor-manual tree felling cuts by Stelian Alexandru Borz, Andrea Rosario Proto

“…The wood lost depends also on the tree size, but accurate quantifications and their dependencies are difficult to establish since there is a limited ability to manually measure key dimensions and assimilate the tree bottom to parametric geometric features. …”
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Equity in Digital Mental Health Interventions in the United States: Where to Next? by Athena Robinson, Megan Flom, Valerie L Forman-Hoffman, Trina Histon, Monique Levy, Alison Darcy, Toluwalase Ajayi, David C Mohr, Paul Wicks, Carolyn Greene, Robert M Montgomery

“…All these considerations should also extend into the context of an equity-informed commercial strategy for DMHI manufacturers and health care organizations alike. …”
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Deep learning-based novel ensemble method with best score transferred-adaptive neuro fuzzy inference system for energy consumption prediction by Birce Dağkurs, İsmail Atacak

“…The results of the 120-h periodic analyses also showed that the proposed method yielded a better prediction result than the other methods. …”
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Bioinformatics‑Based Analysis Reveals Diagnostic Biomarkers and Immune Landscape in Atopic Dermatitis by Yang M, Zhang X, Zhou C, Du Y, Zhou M, Zhang W

“…Least Absolute Shrinkage and Selection Operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms were used to screen hub genes. Immune cell infiltration was evaluated using CIBERSORT. …”
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Machine-learning-based reconstruction of long-term global terrestrial water storage anomalies from observed, satellite and land-surface model data by N. Mandal, P. Das, K. Chanda, K. Chanda

“…Globally, ETR performs best for most of the grid cells; this is also noticed at the river basin scale, particularly for the Ganga–Brahmaputra–Meghna, Godavari, Krishna, Limpopo and Nile river basins. …”
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Prediction of Rice Chlorophyll Index (CHI) Using Nighttime Multi-Source Spectral Data by Cong Liu, Lin Wang, Xuetong Fu, Junzhe Zhang, Ran Wang, Xiaofeng Wang, Nan Chai, Longfeng Guan, Qingshan Chen, Zhongchen Zhang

“…Subsequently, CHI prediction models were developed using four machine learning algorithms: support vector regression (SVR), random forest (RF), back-propagation neural network (BPNN), and k-nearest neighbors (KNNs). …”
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Recent advances in anion exchange membrane technology for water electrolysis: a review of progress and challenges by Abdul Qayoom, Muhammad Shakeel Ahmad, H. Fayaz, Atika Qazi, Jeyraj Selvaraj, Rahadian Zainul, Krismadinata, Nasrudin Abd Rahim, Farruh Atamurotov, Thien Khanh Tran, Basma Souayeh, Natei Ermias Benti

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Automated classification of stress and relaxation responses in major depressive disorder, panic disorder, and healthy participants via heart rate variability by Sangwon Byun, Ah Young Kim, Min-Sup Shin, Hong Jin Jeon, Hong Jin Jeon, Chul-Hyun Cho, Chul-Hyun Cho

“…The impact of personalized longitudinal scaling on classification accuracy was also assessed.ResultsRandom forest classification accuracies were 0.67 for MDD, 0.69 for PD, and 0.73 for HCs, indicating higher accuracy in the HC group. …”
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Transient Attracting Profiles in the Great Pacific Garbage Patch by L. Kunz, A. Griesel, C. Eden, R. Duran, R. Duran, B. Sainte-Rose

“…Prospective research could investigate this further by applying our algorithms to soon-available high-resolution observations of the flow. …”
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Transformer Models improve the acoustic recognition of buzz-pollinating bee species by Alef Iury Siqueira Ferreira, Nádia Felix Felipe da Silva, Fernanda Neiva Mesquita, Thierson Couto Rosa, Stephen L. Buchmann, José Neiva Mesquita-Neto

“…However, transformer approaches face challenges related to small dataset size and class imbalance, similar to CNNs and classical ML algorithms. Combining pre-training with data augmentation is crucial to increase the diversity and robustness of training data sets for the acoustic recognition of bee species. …”
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