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

“…Introduction Race-specific equations for spirometry reference values are one example of race-specific algorithms traditionally used in medicine. The American Thoracic Society now recommends use of race-neutral reference equations instead of race-specific equations. …”
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Artificial intelligence and chordoma: A scoping review of the current landscape and future directions by Eddie Guo, Rafael D. Sanguinetti, Lyndon Boone, Jiawen Deng, Husain Shakil, Mehul Gupta

“…Limitations identified across studies included small sample sizes, single-center data, reliance on single data modalities, and issues with model interpretability. Discussion and conclusion: AI applications in chordoma management show potential in improving diagnostic accuracy, surgical planning, and prognostication. …”
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Real-time monitoring of water quality dynamics using low-cost sensor networks in Lagos lagoon by Idowu Ayisat Aneyo, Mumin Olatunji Oladipo, Funmilayo Victoria Doherty, Julius Osato Ehigie, Adebayo Fasasi Adebari, Abdulwakeel Oluwatobi Atoyebi, Peter Ozomata Balogun, Ambrose Obinna Ikpele

“…Future research should focus on enhancing wireless communication, refining species detection algorithms and improving sensor resilience in harsh aquatic conditions.…”
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Label semantics and image features aware remote sensing sample retrieval from multi-source datasets for AI-enabled remote sensing monitoring by XingTao Ren, XingTao Ren, Yan Ma, YiXin Zhou, YiXin Zhou

“…Accordingly, the remote sensing imagery sample datasets have become crucial in ensuring robust training models with satisfactory performance across various AI (Artificial Intelligence)-enabled remote sensing applications. …”
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Emerging Diagnostic Approaches for Musculoskeletal Disorders: Advances in Imaging, Biomarkers, and Clinical Assessment by Rahul Kumar, Kiran Marla, Kyle Sporn, Phani Paladugu, Akshay Khanna, Chirag Gowda, Alex Ngo, Ethan Waisberg, Ram Jagadeesan, Alireza Tavakkoli

“…Furthermore, reimbursement models have not caught up with many of these innovations, limiting access in resource-constrained healthcare settings. …”
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AI Dermatochroma Analytica (AIDA): Smart Technology for Robust Skin Color Classification and Segmentation by Abderrachid Hamrani, Daniela Leizaola, Nikhil Kumar Reddy Vedere, Robert S. Kirsner, Kacie Kaile, Alexander Lee Trinidad, Anuradha Godavarty

“…AIDA applies clustering techniques to classify skin tones without relying on labeled data, evaluating over twelve models, including K-means, density-based, hierarchical, and fuzzy logic algorithms. …”
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Research on Civil Aviation Airport Site Selection Considering Group Consensus Level Under Large-Scale Uncertain Information by Rui Wang, Jing-Han Zeng, Jing-Yang Huang, Rui Kang, Jiang Yuan, Qing-Wei Zhong

“…The method comprises five key processes: (1) Evaluation process: Based on the constructed multicriteria evaluation system for airport site selection, the q-Rung Orthopair Fuzzy (q-ROF) information is employed to represent evaluations from large-scale decision makers, which effectively characterizes the uncertainty of information and broadens the evaluative scope. (2) Clustering process: A clustering procedure is designed for large-scale q-ROF evaluation data and weight information of criteria, identifying and removing outliers. (3) Consensus reaching process: Considering the characteristics of q-ROF evaluations and multiplicative preference relations, two adaptive consensus reaching algorithms are developed to enhance group consensus levels, thereby improving the rationality of decision-making results. (4) Weight determination process: Criteria and subcriteria weights are calculated using multiplicative preference weighting approach and a deviation maximization model, respectively, derived from aggregated group evaluations. (5) Ranking process: The q-ROF Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is applied, in conjunction with the induced q-ROF information integration paradigm, to comprehensively rank the alternative sites. …”
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Comparative Analysis of Machine Learning Techniques for Fault Diagnosis of Rolling Element Bearing with Wear Defects by Devendra Sahu, Ritesh Kumar Dewangan, Surendra Pal Singh Matharu

“…This optimization of the signal enhancement methodology significantly improved the fault diagnosis accuracy. As per the result obtained, Random Forest method consistently outperforms when applied to the feature-enhanced SNR dataset. …”
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A novel infrared thermography image analysis for transformer condition monitoring by Rupali Balabantaraya, Ashwin Kumar Sahoo, Prabodh Kumar Sahoo, Chayan Mondal Abir, Manoj Kumar Panda

“…To find the best performing machine learning model, different techniques are compared here in terms of their accuracy and stability. …”
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White Blood Cell Detection Based on FBDM-YOLOv8s by Borui Sun, Xiangsuo Fan, Jie Meng, Jinfeng Wang, Huajin Chen, Lei Liu

“…This article proposes a white blood cell detection method based on an improved YOLOv8s to enhance the accurate detection of different categories of normal white blood cells. …”
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Integrative analysis of RNA-Seq data and machine learning approaches to identify Biomarkers for Rhizoctonia solani resistance in sugar beet by Bahman Panahi, Mahdi Hassani, Nahid Hosseinzaeh Gharajeh

“…We ranked differentially expressed genes (DEGs) using feature-weighting algorithms, such as Relief and kernel-based methods, to model expression patterns between sensitive and tolerant cultivars. …”
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Volcano activity classification from synergy of EO data and machine learning: an application to Mount Etna volcano (Italy) by C. Petrucci, G. Romoli, A. Pignatelli, E. Trasatti, F. Zuccarello, F. Greco, M. Dozzo, G. Bilotta, F. Spina, G. Ganci

“…A k-fold cross-validation approach was used to evaluate model performance systematically. The results underline the potential of ML techniques combined with EO data for volcanic hazard monitoring, with implications for improving risk assessment and early-warning systems. …”
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A Spatiotemporal Fusion Network for Remote Sensing Based on Global Context Attention Mechanism by Weisheng Li, Yusha Liu, Yidong Peng, Fengyan Wu

“…Spatial-temporal fusion algorithms commonly encounter difficulties in effectively striking a balance between the extraction of intricate spatial details and changes over time. …”
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Impact of tertiary lymphoid structure-associated biomarkers on pancreatic cancer via a dual-disease analysis of psoriasis and pancreatic cancer by Hao Yu, Quan Yuan, Liu-Xing Feng, Jia-Huan Xu, Shen-Yuan Zhan, Zhi-min Li, Shuang-Jia Wang

“…These results offer valuable insights into PC progression, providing a foundation for improved clinical management and future research.…”
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Classification of the Condition of Cancer Patients Receiving Home Health Care with Machine Learning Methods by Mürsel Kahveci

“…The machine learning model allows determining the type of cancer using the feature space based on VAS, Karnofsky performance scale, ECOG, Katz and Bartel scores. …”
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Anatomical Parameter-driven Volumetric Modulated Arc Therapy Optimization in Left-sided Breast Cancer: A Machine Learning Framework for Lung Dose Prediction by Mukesh Kumar Zope, Deepali Patil, Rishi Raj, Seema Devi, Richa Madhawi

“…In addition, we established predictive models for lung doses utilizing the Least Absolute Shrinkage and Selection Operator, ridge, and linear regression algorithms while also evaluating dosimetric parameters for both the PTV and the organs at risk (OARs). …”
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From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications by Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou, Constantinos Halkiopoulos

“…Methods: Following PRISMA, 64 studies were reviewed that outlined the latest feature extraction and classification developments using deep learning models such as CNNs and RNNs. Results: Indeed, the findings showed that the multimodal approaches were practical, especially the combinations involving EEG with physiological signals, thus improving the accuracy of classification, even surpassing 90% in some studies. …”
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The Analytical System for Determining the Attitude of Students to the University by Violeta Tretynyk, Mariia Pinda

“…Existing software solutions use methods for processing and analyzing text tone based on machine learning methods and algorithms (naive Bayesian classifier, support vector machine, logistic regression), as well as deep learning (recurrent neural networks). …”
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Integrating Metaheuristics and Machine Learning for Enhanced Vehicle Routing: A Comparative Study of Hyperheuristic and VAE-Based Approaches by Kassem Danach, Louai Saker, Hassan Harb

“…In contrast, the VAE-based approach leverages deep learning to model historical routing patterns and autonomously generate new heuristics tailored to problem-specific characteristics. …”
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Coordinating environmental genomics and geochemistry reveals metabolic transitions in a hot spring ecosystem. by Wesley D Swingley, D'Arcy R Meyer-Dombard, Everett L Shock, Eric B Alsop, Heinz D Falenski, Jeff R Havig, Jason Raymond

“…We have also assigned environmental genome sequences to individual microbial community members by complementing traditional homology-based assignment with nucleotide word-usage algorithms, allowing more than 70% of all reads to be assigned to source organisms. …”
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