Artificial Intelligence in Primary Malignant Bone Tumor Imaging: A Narrative Review by Platon S. Papageorgiou, Rafail Christodoulou, Panagiotis Korfiatis, Dimitra P. Papagelopoulos, Olympia Papakonstantinou, Nancy Pham, Amanda Woodward, Panayiotis J. Papagelopoulos

“…Ethical considerations, including data privacy and the interpretability of complex AI algorithms, also warrant careful attention. Future research should prioritize multicenter collaborations, external validation of AI models, and the integration of explainable AI systems into clinical practice. …”
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The PM_2.5-Bound Polycyclic Aromatic Hydrocarbon Behavior in Indoor and Outdoor Environments, Part III: Role of Environmental Settings in Elevating Indoor Concentrations... by Gordana Jovanović, Mirjana Perišić, Timea Bezdan, Svetlana Stanišić, Kristina Radusin, Aleksandar Popović, Andreja Stojić

“…We applied seven regression tree ensemble algorithms to interrelate the variables alongside six metaheuristic optimization algorithms to refine model accuracy and robustness. …”
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Integrative in Silico modeling for mTOR inhibition: From ridge classifiers to descriptor-free deep neural networks by Seyed Alireza Khanghahi, Hadi Kamkar, Seyedehsamaneh Shojaeilangari, Abdollah Allahverdi, Parviz Abdolmaleki

“…Unlike prior studies that focused on specific algorithms or limited descriptors, we benchmark a wide range of models, from traditional models like Random Forest, logistic regression, and SVM to modern algorithms like CNNs, GRUs, and LSTMs, on both descriptor-based features obtained by Dragon and descriptor-free inputs, including raw SMILES string, and Morgan fingerprints. …”
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Comprehensive protein datasets and benchmarking for liquid–liquid phase separation studies by Carlos Pintado-Grima, Oriol Bárcenas, Eva Arribas-Ruiz, Valentín Iglesias, Michał Burdukiewicz, Salvador Ventura

“…To validate our datasets, we investigate specific physicochemical traits related to LLPS across different subsets of protein sequences and benchmark them against 16 predictive algorithms. We observe significant differences not only between positive and negative instances but also among LLPS proteins themselves. …”
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Data-Driven Clustering of Plantar Thermal Patterns in Healthy Individuals: An Insole-Based Approach to Foot Health Monitoring by Mark Borg, Stephen Mizzi, Robert Farrugia, Tiziana Mifsud, Anabelle Mizzi, Josef Bajada, Owen Falzon

“…The data were analysed using clustering algorithms, including k-means, fuzzy c-means, OPTICS, and hierarchical clustering. …”
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A Novel RMS-Driven Deep Reinforcement Learning for Optimized Portfolio Management in Stock Trading by Asma Sattar, Amna Sarwar, Saira Gillani, Maryam Bukhari, Seungmin Rho, Muhammad Faseeh

“…Algorithmic stock trading has improved tremendously, with Reinforcement Learning (RL) algorithms being more adaptable than classic approaches like mean reversion and momentum. …”
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Comparative analysis of hybrid-SNP microarray and nanopore sequencing for detection of large-sized copy number variants in the human genome by Catarina Silva, José Ferrão, Bárbara Marques, Sónia Pedro, Hildeberto Correia, Ana Valente, António Sebastião Rodrigues, Luís Vieira

“…However, further improvements in variant calling algorithms are still needed for nanopore sequencing to become a highly robust and standardized approach for a comprehensive analysis of genomic structural variation.…”
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Obtaining the Highest Quality from a Low-Cost Mobile Scanner: A Comparison of Several Pipelines with a New Scanning Device by Marek Hrdina, Juan Alberto Molina-Valero, Karel Kuželka, Shinichi Tatsumi, Keiji Yamaguchi, Zlatica Melichová, Martin Mokroš, Peter Surový

“…Given the growing availability of 3D-based forest inventory algorithms, a selection of such processing pipelines was used to assess the practical potential of the scanning devices. …”
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synax: A Differentiable and GPU-accelerated Synchrotron Simulation Package by Kangning Diao, Zack Li, Richard D. P. Grumitt, Yi Mao

“…This facilitates powerful inference algorithms, such as Hamiltonian Monte Carlo (HMC) and gradient-based optimization, which enables inference over models that would otherwise be computationally prohibitive. …”
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An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

“…External validation of the eXGBM model also demonstrated a favorable prediction performance with an AUC value of 0.880 (95% CI: 0.830–0.929). …”
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Data transfers for nuclear reactor multiphysics studies using the MOOSE framework by Guillaume L. Giudicelli, Guillaume L. Giudicelli, Fande Kong, Roy Stogner, Logan Harbour, Derek Gaston, Alexander Lindsay, Zachary Prince, Lise Charlot, Stefano Terlizzi, Mahmoud Eltawila, April Novak

“…Advanced nuclear reactor cores are governed by multiple physical phenomena which should be all be resolved, and the coupling of these physics would also need to be resolved spatially in a high-fidelity approach, while lower fidelity may leverage integrated quantities for the coupling instead. …”
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Wearable sensors-based assistive technologies for patient health monitoring by Nouf Abdullah Almujally, Danyal Khan, Danyal Khan, Naif Al Mudawi, Mohammed Alonazi, Haifa F. Alhasson, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…Other performance indicators, such as recall, precision, and F1 score, also performed well.Discussion:Overall, integrating a machine learning model with bio-signals provides an enhanced ability to interpret complex real-time patient health monitoring for personalized care and overall smart healthcare.…”
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Comparison of artificial intelligence and logistic regression models for mortality prediction in acute respiratory distress syndrome: a systematic review and meta-analysis by Yang He, Ning Liu, Jie Yang, Yucai Hong, Hongying Ni, Zhongheng Zhang

“…Sensitivity analysis, meta-regression analysis, and tests for heterogeneity were also performed. Results Eight studies were included in the analysis. …”
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Identification of potential metabolic biomarkers and immune cell infiltration for metabolic associated steatohepatitis by bioinformatics analysis and machine learning by Haoran Xie, Junjun Wang, Qiuyan Zhao

“…The findings not only offer novel strategies for non-invasive diagnosis of MASH but also highlight the substantial role of immune cell infiltration in the progression of MASH.…”
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Enhanced MRI brain tumor detection using deep learning in conjunction with explainable AI SHAP based diverse and multi feature analysis by Asif Rahman, Maqsood Hayat, Nadeem Iqbal, Fawaz Khaled Alarfaj, Salem Alkhalaf, Fahad Alturise

“…In subsequent analysis, a large benchmark dataset is also utilized to evaluate the performance of learning algorithms in order to investigate the generalization power of the proposed model. …”
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Prediction of early postoperative complications and transfusion risk after lumbar spinal stenosis surgery in geriatric patients: machine learning approach based on comprehensive ge... by Wounsuk Rhee, Sam Yeol Chang, Bong-Soon Chang, Hyoungmin Kim

“…A set of Compact models incorporating a smaller number of features was also trained, and SHAP analysis was conducted to evaluate the models’ interpretability. …”
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RGB-to-Infrared Translation Using Ensemble Learning Applied to Driving Scenarios by Leonardo Ravaglia, Roberto Longo, Kaili Wang, David Van Hamme, Julie Moeyersoms, Ben Stoffelen, Tom De Schepper

“…However, the lack of IR data in many datasets and simulation tools limits the development and validation of sensor fusion algorithms that exploit this complementarity. To address this, we propose an augmentation method that synthesizes realistic IR data from RGB images using gradient-boosting decision trees. …”
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Quantum secured blockchain framework for enhancing post quantum data security by Nalavala Ramanjaneya Reddy, Supriya Suryadevara, K. Guru Raghavendra Reddy, Ramisetty Umamaheswari, Ramakrishna Guttula, Rajitha Kotoju

“…Popular schemes like RSA, ECDSA, and SHA-256 can be compromised by quantum algorithms (Shor’s and Grover’s), raising questions about the security and trustworthiness of blockchain-based applications in finance, healthcare, and supply chains. …”
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Deep Neural Network-Based Method for Detecting Central Retinal Vein Occlusion Using Ultrawide-Field Fundus Ophthalmoscopy by Daisuke Nagasato, Hitoshi Tabuchi, Hideharu Ohsugi, Hiroki Masumoto, Hiroki Enno, Naofumi Ishitobi, Tomoaki Sonobe, Masahiro Kameoka, Masanori Niki, Ken Hayashi, Yoshinori Mitamura

“…Training to construct the DL model using deep convolutional neural network algorithms was provided using ultrawide-field fundus images. …”
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Control of three-level quadratic DC-DC boost converters for energy systems using various technique-based MPPT methods by Souheyb Mohammed Belhadj, Bouziane Meliani, Habib Benbouhenni, Ilhami Colak, Z. M. S. Elbarbary, Saad F. Al-Gahtani

“…Abstract The conventional DC-DC architecture is often used in photovoltaic systems, with control based on incremental conductance-based maximum power point tracking (MPPT-IC) algorithms. Despite its simplicity and ability to ensure voltage balance across the output capacitors, this architecture suffers several drawbacks. …”
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