Cosine Similarity Template Matching Networks for Optical and SAR Image Registration by Wenxuan Xiong, Mingyu Sun, Hua Du, Bangshu Xiong, Congxuan Zhang, Qiaofeng Ou, Zhibo Rao

“…These datasets serve as benchmarks for evaluating template matching algorithms in heterogeneous image scenarios, setting the stage for further advancements in template matching research.…”
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Listener Acoustic Personalization Challenge - LAP24: Head-Related Transfer Function Upsampling by Aidan O. T. Hogg, Roberto Barumerli, Rapolas Daugintis, Katarina C. Poole, Fabian Brinkmann, Lorenzo Picinali, Michele Geronazzo

“…The submissions to Task 2 employed both algorithmic and machine learning-based approaches, which were evaluated on three key spatial audio objective metrics, including the log-spectral distortion (LSD), interaural time difference (ITD), and the interaural level difference (ILD). …”
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Predicting the risk of depression in older adults with disability using machine learning: an analysis based on CHARLS data by Tongtong Jin, Ayitijiang· Halili

“…A three-stage serial consensus approach feature selection framework (LASSO, Elastic Net, and Boruta) was employed to identify 21 robust predictors from 74 candidate variables. Ten ML algorithms were evaluated: LR, HistGBM, MLP, XGBoost, bagging, DT, LightGBM, RF, SVM, and CatBoost. …”
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Investigating imperceptibility of adversarial attacks on tabular data: An empirical analysis by Zhipeng He, Chun Ouyang, Laith Alzubaidi, Alistair Barros, Catarina Moreira

“…The study also identifies limitations in current attack algorithms, offering insights that can guide future research in the area. …”
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Assessment of flight fatigue using heart rate variability and machine learning approaches by Dalong Guo, Cong Wang, Yufei Qin, Lamei Shang, Aijing Gao, Baosen Tan, Yubin Zhou, Guangyun Wang

“…First, we conducted statistical analyses to investigate whether HRV features and respiratory rate indicators significantly differed across various fatigue levels. A subset of HRV features and the respiratory metric were used as input variables for four machine learning algorithms: decision tree, support vector machine, K-nearest neighbor, and light gradient-boosting machine (LightGBM). …”
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Optimized Time-domain Feature Extraction for Early Onset Diagnosis of Parkinson Disease From EEG Signals by Delshad Ghavami, Moein Radman, Ali Chaibakhsh

“…Various window lengths were evaluated to determine the optimal time window for feature extraction, with 4 seconds identified as the optimal duration. …”
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A topic modeling approach for analyzing and categorizing electronic healthcare documents in Afaan Oromo without label information by Etana Fikadu Dinsa, Mrinal Das, Teklu Urgessa Abebe

“…The tools designed for English do not work efficiently for Afaan Oromo due to the linguistic differences and lack of well-structured resources. To address this challenge, this work proposes a topic modeling framework for unstructured health-related documents in Afaan Oromo using latent dirichlet allocation (LDA) algorithms. …”
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Predictive modelling employing machine learning, convolutional neural networks (CNNs), and smartphone RGB images for non-destructive biomass estimation of pearl millet (Pennisetum... by Faten Dhawi, Abdul Ghafoor, Norah Almousa, Sakinah Ali, Sara Alqanbar

“…Smartphone-based RGB imaging was used for data collection, and Shapley additive explanations (SHAP) methodology evaluated predictor importance. The SHAP analysis identified Normalized Green-Red Difference Index (NGRDI) and plant height as the most influential features for AGB estimation. …”
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Machine learning for synchronous bone metastasis risk prediction in high grade lung neuroendocrine carcinoma by Bo Lan, Zongyun He, Zhe Chen, Haibing Tao, Tao Liu, Jin Yang

“…This study aimed to use multiple machine learning algorithms to exploring the significant factors associated with synchronous BM in these patients. …”
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SEARCH FOR CLINICAL PREDICTORS OF PULMONARY HYPERTENSION IN PATIENTS WITH SYSTEMIC SCLEROSIS by N. A. Klyaus, M. A. Simakova, A. L. Maslyansky, O. M. Moiseeva

“…The scope of investigations necessary to detect PH, the complexity of its diagnostic algorithms for routine use, as well as the impossibility to apply the existing algorithms for all PH variants increase the relevance of searching for novel PH predictors in patients with SSc.Objective: to reveal the relationship of capillary structural changes to the clinical and immunological subtype of SSc, disease activity, and risk for PH.Subjects and methods. …”
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Teaching Internal Medicine Residents to Critically Appraise the Role of Race in Pulmonary Function Testing by Ananya Bhatia-Lin, Nirav Bhakta, Neha Deshpande, Laura Granados, Rosemary Adamson

“…We conducted pre- and posttest surveys; the posttest survey was designed using the Kirkpatrick model to assess reaction, learning, and anticipated behavioral change. Mean score differences were evaluated for level 2 questions using Cohen's d effect size. …”
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Advances in Light Field Spatial Super-Resolution: A Comprehensive Literature Survey by Wenqi Lyu, Hao Sheng, Wei Ke, Xiao Ma

“…We present a systematic review of 17 mainstream light field spatial super-resolution techniques, evaluating their performance across seven public datasets. …”
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Mapping Vegetation Dynamics in Wyoming: A Multi-Temporal Analysis using Landsat NDVI and Clustering by N. Kuppala, C. Navneet Krishna, V. V. Sajith Variyar, R. Sivanpillai

“…GMM assigns data points probabilistically, assuming data are generated from a mixture of Gaussian distributions, while AP identifies clusters by finding representative exemplars without needing a predefined number of clusters. To evaluate the performance of these clustering algorithms, we assigned the clusters into six classes based on vegetation growth patterns observed over the five-year period. …”
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A Machine Learning Approach for Predicting Maternal Health Risks in Lower-Middle-Income Countries Using Sparse Data and Vital Signs by Avnish Malde, Vishnunarayan Girishan Prabhu, Dishant Banga, Michael Hsieh, Chaithanya Renduchintala, Ronald Pirrallo

“…The models’ performance were evaluated using regular, random and stratified sampling techniques. …”
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Towards sustainable agriculture in Iran using a machine learning-driven crop mapping framework by Iman Khosravi

“…The Ministry of Agriculture-Jihad (MAJ) and the Iranian Space Agency (ISA) aim to accurately estimate the cultivated area of strategic crops and evaluate their annual yield through meticulous crop mapping. …”
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From Words to Ratings: Machine Learning and NLP for Wine Reviews by Iliana Ilieva, Margarita Terziyska, Teofana Dimitrova

“…The descriptions were transformed into numerical representations using a pre-trained language model (BERT), after which algorithms were used to predict style categories and ratings. …”
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Investigating Similarities Across Decentralized Finance (DeFi) Services by Junliang Luo, Stefan Kitzler, Pietro Saggese

“… We explore the adoption of graph representation learning (GRL) algorithms to investigate similarities across services offered by Decentralized Finance (DeFi) protocols. …”
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Cross-sectional and longitudinal Biomarker extraction and analysis for multicentre FLAIR brain MRI by J. DiGregorio, A. Gibicar, H. Khosravani, P. Jabehdar Maralani, J.-C. Tardif, P.N. Tyrrell, A.R. Moody, A. Khademi

“…Biomarkers were extracted from two dementia cohorts (4356 vol, 162 233 images) and one vascular disease cohort (869 vol, 42 850 images) using deep learning-based segmentation algorithms designed specifically for FLAIR. Biomarkers from all cohorts were summarized using descriptive statistics, correlation analysis, and ANCOVA to assess differences in diagnostic labels while accounting for demographic and acquisition factors. …”
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Lossy DICOM conversion may affect AI performance by Robin Sebastian Mayer, Fabian Fliedner, Ingvild Frøberg Mathisen, Anna Laib, Julia Bein, Marco Eichelberg, Peter J. Wild, Nadine Flinner

“…So, if DICOM images are intended for a diagnostic use, all processes and algorithms must be (re-)evaluated with the converted files, as images are not identical. …”
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Transbronchial lung cryobiopsy for diagnosing interstitial lung disease: a cross-sectional, comparative study by Min Yu, Xuefeng Xu, Xiaoyan Xin, Shangwen Yang, Yihua Wang, Yonglong Xiao, Shenyun Shi, Xuebing Feng

“…Conclusions This study indicated that the clinical applicability of TBLC in ILD diagnostic algorithms, with a diagnostic yield of 85.0% and an acceptable safety profile.…”
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