A deep learning model for predicting systemic lupus erythematosus-associated epitopes by Jiale He, Zixia Liu, Xiaopo Tang

“…Results The hybrid model outperformed both baseline machine learning algorithms and ablated versions of itself. It achieved a ROCAUC of 0.9506 and an F1-score of 0.8333 on the SLE epitope prediction task. …”
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Statistical modeling and application of machine learning for antibiotic degradation using UV/persulfate-peroxide based advanced oxidation process by Musfekur Rahman Dihan, Md. Ashraful Alam, Surya Akter, Md. Abdul Gafur, Md. Shahinoor Islam

“…Pearson correlation and statistical multivariate linear regression (MLR) were applied to model the removal% and pHfinal of both antibiotics, along with the three machine learning algorithms, Artificial neural network (ANN), support vector machine (SVM), and Random Forest (RF), to make the same predictions. …”
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Nutritional markers of undiagnosed type 2 diabetes in adults: Findings of a machine learning analysis with external validation and benchmarking. by Kushan De Silva, Siew Lim, Aya Mousa, Helena Teede, Andrew Forbes, Ryan T Demmer, Daniel Jönsson, Joanne Enticott

“…We tested three machine learning algorithms on original and resampled training datasets built using three resampling methods. …”
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Goal-oriented autonomous decision-making for social robots via collaborative interactive inverse reinforcement learning approach by Mingyue Luo, Hui Li, Wanbo Luo, Hewei Li, Jianan Li

“…Furthermore, reduplicate experiments demonstrate that GO-ADM achieves higher success rate with other social navigation and decision-making algorithms. Under severe interference conditions, with maximum noise 0.5 m, the success rate of GO-ADM exceeding 75%, demonstrating strong robustness against unknown interferences.…”
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Resilience evaluation of memristor based PUF against machine learning attacks by Hebatallah M. Ibrahim, Heorhii Skovorodnikov, Hoda Alkhzaimi

“…However, most existing CMOS PUFs are found to be vulnerable to modeling attacks based on machine learning (ML) algorithms. Memristors leveraging nanotechnology fabrication processes and highly nonlinear behavior became an interesting alternative to the existing CMOS-based PUF technology, introducing cryptographic and resilient random outputs. …”
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A novel hexagonal PtPS monolayer for high anisotropic carrier mobility and potential for photocatalytic water splitting with pronounced optical absorption by Chunying Pu, Pan Zhang, Linxuan Chen, Xindong Pan, Dawei Zhou

“…Motivated by the attractive properties and potential applications of MPX materials, we identified a novel stable hexagonal structure of PtPS monolayer with the space group $$P\bar {3}m1$$ using particle swarm optimization algorithms in conjunction with first-principles calculations. …”
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The impact of a dedicated checklist on the quality of onsite management of critically buried avalanche victims in cardiac arrest in a Swiss helicopter emergency medical service by Maxime Trolliet, Mathieu Pasquier, Marc Blancher, Roland Albrecht, Alban Lovis, Hermann Brugger, Alexandre Kottmann

“…Despite existing specific management algorithms, previous studies have reported poor compliance with international guidelines and incomplete documentation and transmission of the information required for patient management. …”
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Development and evaluation of a machine learning model for post-surgical acute kidney injury in active infective endocarditis by XinPei Liu, SanXi Ai, RuiMing Yu, ChaoJi Zhang, Qi Miao

“…LASSO regression identified 25 significant features for the models. Among the six algorithms tested, the radial basis function support vector machine (RBF-SVM) had the highest AUC at 0.771. …”
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Assessing marine ecosystem risks through unsupervised methods by Laura Pavirani, Pasquale Bove, Gianpaolo Coro

“…This study evaluates six unsupervised methods — four clustering algorithms (Multi K-means, Fuzzy C-means, X-means, and DBSCAN) and two machine-learning models (an Artificial Neural Network, ANN, and a Variational Autoencoder, VAE) — to assess marine ecosystem risk in the Mediterranean Sea automatically, using open-access data from 2017 to 2021. …”
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Grid Search Based Hyperparameter-Tuned Deep Learning Model for Osteoporosis Diagnosis with Bi-Cubic Interpolation of X-Ray Images by Ruhul Amin, Md.Shamim Reza, Dewan Ahmed Muhtasim, Jungpil Shin, Md. Maniruzzaman, Md.Mahfujul Hasan

“…Even with the widespread use of deep learning (DL) and machine learning (ML) algorithms, the early diagnosis of osteoporosis patients can still be improved. …”
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Are Artificial Intelligence Models Listening Like Cardiologists? Bridging the Gap Between Artificial Intelligence and Clinical Reasoning in Heart-Sound Classification Using Explain... by Sami Alrabie, Ahmed Barnawi

“…First, we observed that automatic heart-sound segmentation algorithms—commonly used for data augmentation—produce varying outcomes, raising concerns about the accuracy of both the segmentation process and the resulting classification performance. …”
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Lightweight highland barley detection based on improved YOLOv5 by Minghui Cai, Hui Deng, Jianwei Cai, Weipeng Guo, Zhipeng Hu, Dongzheng Yu, Houxi Zhang

“…In addition,the proposed model outperformed mainstream object detection algorithms such as Faster R-CNN, Mask R-CNN, RetinaNet, YOLOv7, and YOLOv8, in terms of detection accuracy and computational efficiency. …”
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Cross-dimensional adaptivity research on a 3D earth observation data cube model by Yu Jinsongdi, Cui Zhanying, Baumann Peter, Tong Ruiju, Wei Dandan, Luo Yuan

“…This becomes feasible by applying suitable serialization algorithms. This study demonstrates that data cubes can be successfully mapped into the proposed 3D adaptive data cube, achieving interoperability under specific conditions. …”
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Performance and applicability of low-cost PM sensors to assess global pollution variability through machine learning techniques by Rajat Sharma, Andry Razakamanantsoa, Ashutosh Kumar, Thaseem Thajudeen, Agnès Jullien

“…Additionally, it was observed that advanced machine learning algorithms helped to improve performance parameters, particularly in middle and lower income group countries where pollution variability is higher. …”
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A Novel Approach for Maize Straw Type Recognition Based on UAV Imagery Integrating Height, Shape, and Spectral Information by Xin Liu, Huili Gong, Lin Guo, Xiaohe Gu, Jingping Zhou

“…An object-oriented classification method, utilizing a “two-step segmentation with multiple algorithms” strategy, was employed to integrate height, shape, and spectral features, enabling rapid and accurate mapping of maize straw types. …”
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Compensation of Speckle Noise in 2D Images from Triangulation Laser Profile Sensors Using Local Column Median Vectors with an Application in a Quality Control System by Paweł Rotter, Dawid Knapik, Maciej Klemiato, Maciej Rosół, Grzegorz Putynkowski

“…Consequently, conventional algorithms for removing fixed pattern noise yield unsatisfactory results when applied to profilometer images. …”
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Assessing the deep learning based image quality enhancements for the BGO based GE omni legend PET/CT by Meysam Dadgar, Amaryllis Verstraete, Jens Maebe, Yves D’Asseler, Stefaan Vandenberghe

“…Conclusion This study conducted a thorough evaluation of deep learning algorithms in the GE Omni Legend PET/CT scanner, demonstrating that these methods enhance image quality, with notable improvements in CRC and CNR, thereby optimizing lesion detectability and offering opportunities to reduce image acquisition time.…”
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Potential of diagnostic electron microscopy of calcification, pathological neovascularization and elastolysis in combination with phenotyping of cell populations in large arteries by R. A. Mukhamadiyarov, K. Yu. Klyshnikov, V. A. Koshelev, A. G. Kutikhin

“…Electronic contrast distribution signatures unique for each cell population indicate the possibility of their automated phenotyping using specialized neural network algorithms.…”
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Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach. by Hamidreza Moradi, H Timothy Bunnell, Bradley S Price, Maryam Khodaverdi, Michael T Vest, James Z Porterfield, Alfred J Anzalone, Susan L Santangelo, Wesley Kimble, Jeremy Harper, William B Hillegass, Sally L Hodder, National COVID Cohort Collaborative (N3C) Consortium

“…Then, the most accurate model is utilized by eXplainable Artificial Intelligence (XAI) algorithms to provide insights about the learned treatment combination impacts on the model's final outcome prediction.…”
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Prediction of Shield Tunneling Attitude Based on WM-CTA Method by GAO Su, CHEN Cheng

“…The preprocessing module, composed of Wavelet Transform (WT) and the Maximum Information Coefficient (MIC) algorithms, was used to perform noise reduction and parameter correlation analysis on the raw data, thereby generating enhanced inputs. …”
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