Shared gene signatures and molecular mechanisms link ankylosing spondylitis and rheumatoid arthritis by Boli Qin, Xiaopeng Qin, Jie Ma, Chenxing Zhou, Tianyou Chen, Jichong Zhu, Chengqian Huang, Shaofeng Wu, Rongqing He, Songze Wu, Sitan Feng, Jiarui Chen, Jiang Xue, Wendi Wei, Tengxiang Long, Quan Pan, Kechang He, Zhendong Qin, Tiejun Zhou, Jiayan Jiang, Xinli Zhan, Chong Liu

“…The CBC data of 23,289 patients were collected, and six machine learning algorithms were applied to develop disease prediction models for AS and RA. …”
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Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI by Insu Jeon, Minjoong Kim, Dayeong So, Eun Young Kim, Yunyoung Nam, Seungsoo Kim, Sehoon Shim, Joungmin Kim, Jihoon Moon

“…Using <i>R</i> and the <i>caret</i> package (version 6.0.94), we developed and compared several ML algorithms, validated using 10-fold cross-validation and optimized by grid search hyperparameter tuning. …”
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SPA-Net: An Offset-Free Proposal Network for Individual Tree Segmentation from TLS Data by Yunjie Zhu, Zhihao Wang, Qiaolin Ye, Lifeng Pang, Qian Wang, Xiaolong Zheng, Chunhua Hu

“…Individual tree segmentation (ITS) from terrestrial laser scanning (TLS) point clouds is foundational for deriving detailed forest structural parameters, crucial for precision forestry, biomass calculation, and carbon accounting. Conventional ITS algorithms often struggle in complex forest stands due to reliance on heuristic rules and manual feature engineering. …”
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Local adaptation and validation of a transdiagnostic risk calculator for first episode psychosis using mental health patient records by Elizabeth Ford, James Stone, James Stone, James Stone, Dominic Oliver, Dominic Oliver, Dominic Oliver, Benjamin Fell, Gloria Roque, Sam Robertson, Paolo Fusar-Poli, Paolo Fusar-Poli, Paolo Fusar-Poli, Paolo Fusar-Poli, Kathryn Greenwood, Kathryn Greenwood

“…We developed new machine-learning NLP algorithms for diagnosis, symptom and substance use concepts by fine-tuning existing open-source transformer models. …”
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Analysis of human brain RNA-seq data reveals combined effects of 4 types of RNA modifications and 18 types of programmed cell death on Alzheimer’s disease by Ke Ye, Xinyu Han, Mengjie Tian, Lulu Liu, Xu Gao, Qing Xia, Dayong Wang

“…Finally, by combining unsupervised consensus clustering, gene co-expression networks, and machine learning algorithms, an RNA modification-related programmed cell death network was constructed, and the pivotal roles of programmed cell death genes in key modules were identified. …”
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Proteomic analysis of blood plasma as a tool for personalized diagnosis of lung adenocarcinoma by D. N. Korobkov, A. S. Kononikhin, S. D. Semenov, H. L. Kordzaya, A. G. Brzhozovskiy, A. E. Bugrova, E. Yu. Vasilieva, D. Yu. Kanner, E. N. Nikolaev, A. A. Komissarov

“…Additionally, we identified three proteins that predict the presence of distant metastases among patients with LAC. …”
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NeuroRF FarmSense: IoT-fueled precision agriculture transformed for superior crop care by Tarun Vats, Shrey Mehra, Uday Madan, Amit Chhabra, Akashdeep Sharma, Kunal Chhabra, Sarabjeet Singh, Utkarsh Chauhan

“…By merging IoT technology with machine learning algorithms, smart farming is poised to enter a transformative phase, providing a scalable response to the pressing issues of global food security. …”
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Construction and interpretation of tobacco leaf position discrimination model based on interpretable machine learning by Ranran Kou, Cong Wang, Jinxia Liu, Ran Wan, Zhe Jin, Le Zhao, Youjie Liu, Junwei Guo, Feng Li, Hongbo Wang, Song Yang, Cong Nie

“…In recent years, near-infrared (NIR) spectroscopy combined with algorithmic models has emerged as a popular method for identifying the tobacco leaf position. …”
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A multicenter pragmatic implementation study of AI-ECG-based clinical decision support software to identify low LVEF: Clinical trial design and methods by Francisco Lopez-Jimenez, Heather M. Alger, Zachi I. Attia, Barbara Barry, Ranee Chatterjee, Rowena Dolor, Paul A. Friedman, Stephen J. Greene, Jason Greenwood, Vinay Gundurao, Sarah Hackett, Prerak Jain, Anja Kinaszczuk, Ketan Mehta, Jason O'Grady, Ambarish Pandey, Christopher Pullins, Arjun R. Puranik, Mohan Krishna Ranganathan, David Rushlow, Mark Stampehl, Vinayak Subramanian, Kitzner Vassor, Xuan Zhu, Samir Awasthi

“…Background: Artificial intelligence (AI) enabled algorithms can detect or predict cardiovascular conditions using electrocardiogram (ECG) data. …”
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Regulatory Framework of the Conduct of Forensic Construction Examination by A. A. Revunov

“…In order to improve the current situation concerning the regulation of forensic construction and technical examinations, the following measures have been proposed: revision and improvement of their methodological, theoretical, and legal foundations, in-depth analysis of the content of urban planning legislation from the point of view of requirements mandatory for application by a forensic expertbuilder, specifying the limits of an expert’s competence, the formation of unified algorithms and forms of presenting research, the development of sub-theories on the legal and organizational support of the nonstate forensic activity, the active involvement of research institutions and higher educational institutions in the conduct of expert examinations.…”
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How does artificial intelligence shape the productivity and quality of research in business studies? A systematic literature review and future research framework by Sugandha Agarwal, Qian Long Kweh, Dima Jamali, Walton Wider, Syed Far Abid Hossain, Muhammad Ashraf Fauzi

“…Moreover, policymakers and managers should educate themselves and their teams about AI to maximize its benefits while minimizing associated risks. …”
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Microcontroller-Based Platform for Lithium-Ion Battery Charging and Experimental Evaluation of Charging Strategies by Laurentiu Marius Baicu, Mihaela Andrei, Bogdan Dumitrascu

“…Future enhancements may include the integration of adaptive algorithms based on internal resistance and temperature, enabling smarter and more efficient charging.…”
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Comparing Blind Image Quality Metrics for Reliable Image Assessment by Cristian George Fieraru, Maria Biserica, Ioana Cristina Plajer, Mihai Ivanovici

“…Reliable image quality assessment is essential not only in digital photography but also as a key metric for evaluating the performance of algorithms and models designed for image quality enhancement or generation. …”
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Linear and Nonlinear Multivariate Classification of Iranian Bottled Mineral Waters According to Their Elemental Content Determined by ICP-OES by J.B. Ghasemi, E. Zolfonoun, R. Khosrokhavar

“…The combinations of inductively coupled plasma-optical emission spectrometry (ICP-OES) and three classification algorithms, i.e., partial least squares discriminant analysis (PLS-DA), least squares support vector machine (LS-SVM) and soft independent modeling of class analogies (SIMCA), for discriminating different brands of Iranian bottled mineral waters, were explored. …”
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Network intrusion detection model using wrapper based feature selection and multi head attention transformers by Muhammad Umer, Muhammad Tahir, Muhammad Sardaraz, Muhammad Sharif, Hela Elmannai, Abeer D. Algarni

“…The model uses a wrapper-based feature selection technique using machine learning algorithms to select the best features, which are then combined and fed into a Multi-Head Attention-based transformer for getting the predictions. …”
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Honeybee Colony Growth Period Recognition Based on Multivariate Temperature Feature Extraction and Machine Learning by Chuanqi Lu, Lin Li, Denghua Li, Qiuying Huang, Wei Hong

“…Finally, six machine learning algorithms, including both supervised and unsupervised learning, were utilized to identify the growth period of bee colonies. …”
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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

“…The purpose of this study is to explore the possibilities of using advanced bio-signals for monitoring patient vital signs during daily life activities and predicting favorable and more accurate health-related solutions based on current body health-related real-time measurements.ResultsWith the help of machine learning algorithms, we have observed classification accuracy of up to 94.67% using the mHealth dataset and 95.12% on the ScientISST MOVE dataset. …”
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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

“…The proposed approach employs Decision Tree (DT) algorithms to uncover patterns linked to service failures. …”
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LoRa Technology Enhanced with a Custom-Designed High-Gain Yagi-Uda Antenna for Data Transmission from Misti Volcano Monitoring to Arequipa City by Flor de Milagro Yesit Arana Medina, Jorge Rendulich

“…In response, this project integrates Internet of Things (IoT) technology, the LoRa (Long Range) network, and an optimized seven-element Yagi-Uda antenna, developed using advanced optimization algorithms to enhance transmission efficiency. The primary objective is to facilitate the reliable collection and transmission of critical sensor data for subsequent analysis by volcanological experts, thereby supporting improved prediction and mitigation of potential volcanic hazards. …”
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From Genomics to AI: Revolutionizing Precision Medicine in Oncology by Giulia Calvino, Juliette Farro, Stefania Zampatti, Cristina Peconi, Domenica Megalizzi, Giulia Trastulli, Sarah Andreucci, Raffaella Cascella, Claudia Strafella, Carlo Caltagirone, Federico Grifalchi, Emiliano Giardina

“…It examines their roles in identifying genetic variants, assessing cancer risk, guiding targeted therapies and immunotherapy, predicting treatment response, and enabling early detection through liquid biopsies. …”
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