Artificial Intelligence Applications in Pediatric Craniofacial Surgery by Lucas M. Harrison, Ragan L. Edison, Rami R. Hallac

“…Machine learning and deep learning models are increasingly used to analyze complex craniofacial imaging, enabling early detection of congenital anomalies such as craniosynostosis, and cleft lip and palate. AI-driven algorithms assist in preoperative planning by identifying anatomical abnormalities, predicting surgical outcomes, and guiding personalized treatment strategies. …”
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Anomaly Detection Method for Hydropower Units Based on KSQDC-ADEAD Under Complex Operating Conditions by Tongqiang Yi, Xiaowu Zhao, Yongjie Shi, Xiangnan Jing, Wenyang Lei, Jiang Guo, Yang Meng, Zhengyu Zhang

“…This paper proposes a hydropower unit anomaly detection method based on K-means seeded quadratic discriminant clustering and an adaptive density-aware ensemble anomaly detection algorithm (KSQDC-ADEAD). The method first employs the KSQDC algorithm to identify different operating conditions of hydropower units. …”
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Trends in management of odontoid fractures 2010–2021 by Michael J. Gouzoulis, BS, Anthony E. Seddio, BS, Albert Rancu, BS, Sahir S. Jabbouri, MD, Jay Moran, MD, Arya Varthi, MD, Daniel R. Rubio, MD, Jonathan N. Grauer, MD

“…While these decisions were predicted by some clinical factors, both also correlated with nonclinical factors suggesting room for more consistent algorithms.…”
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Air pollution and prostate cancer: Unraveling the connection through network toxicology and machine learning by Yuqi Li, Tao Zhou, Zhiyu Liu, Xinyao Zhu, Qilong Wu, Chunyang Meng, Qingfu Deng

“…Subsequently, the best predictive model was selected through a combination of 108 machine learning algorithms. …”
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StrideHD: A Binary Hyperdimensional Computing System Utilizing Window Striding for Image Classification by Dehua Liang, Jun Shiomi, Noriyuki Miura, Hiromitsu Awano

“…Our evaluation also shows that compared with two popular HD algorithms, the singlepass StrideHD model achieves a 27.6<inline-formula> <tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> and 8.2<inline-formula> <tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> reduction in inference memory cost without hurting the classification accuracy, while the iterative mode further provides 8.7<inline-formula> <tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> memory efficiency. …”
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Characterization of Moisture Diffusion in Cured Concrete Slabs at Early Ages by Xiao Zhang, Hongduo Zhao

“…Lower w/c ratio tends to result in larger RH reduction. RH reduction considering both effect of diffusion and self-desiccation in early-age concrete is not sensitive to w/c ratio, but to curing method. …”
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Comparison of nonlinear Kalman filtering schemes for sensorless control of permanent magnet-assisted synchronous reluctance machines by M.A. González-Cagigal, Cristina Martín, Mario Bermúdez, Pedro Cruz-Romero

“…Speed-sensorless control methods can provide additional competitive advantages to these machines, such as cost and size reduction, and reliability enhancement. In this sense, Kalman filter theory (KF) constitutes a well-established solution for sensorless control of electrical drives that can be easily combined with model predictive control schemes (MPC). …”
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Reaching machine learning leverage to advance performance of electrocatalytic CO2 conversion in non-aqueous deep eutectic electrolytes by Ahmed Halilu, Mohamed Kamel Hadj-Kali, Hanee Farzana Hizaddin, Mohd Ali Hashim, Emad M. Ali, Suresh Bhargava

“…This study utilizes machine learning algorithms to analyse the carbon dioxide reduction reaction (CO2RR) in DEEs with a buffer capacity of approximately 10.21 mol/pH. …”
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Prediksi Kesiapan Sekolah Menggunakan Machine Learning Berbasis Kombinasi Adam dan Nesterov Momentum by Indah Mustika Rahayu, Ahmad Yusuf, Mujib Ridwan

“…Machine learning is a technique that uses algorithms to find useful patterns in data. Based on previous NST data, it can be designed as a school readiness prediction model that will facilitate teachers and parents in knowing the readiness of children to enter elementary school. …”
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Charactering Neural Spiking Activity Evoked by Acupuncture Through Coupling Generalized Linear Model by Qing Qin, Kaiyue Zhang, Yanqiu Che, Chunxiao Han, Yingmei Qin, Shanshan Li

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Secure K-Means Clustering Scheme for Confidential Data Based on Paillier Cryptosystem by Zhengqi Zhang, Zixin Xiong, Jun Ye

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Advances in optical biosensors as alternative diagnostics for clinical determination of ESKAPE bacteria by Maargavi Singh, Sreelakshmi C․S․, Chiranjay Mukhopadhyay, Sajan D. George, Pooja Nag, Kapil Sadani

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A Golden Jackal based optimal operation and optimization of a virtual power plant involving renewable resources by Anubhav Kumar Pandey, Chaima Mansour, Nandini K. K., Vinay Kumar Jadoun, Jayalakshmi N. S.

“…In particular, there is a reduction in cost by 2.1% and 0.62% when compared with the salp swarm algorithm and beluga whale algorithm followed by 2.12% and 1.18% in emission. …”
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T2 <italic>Candida</italic> Panel: A Game Changer in Diagnosis of Fungal Infections by Devesh N Joshi, Bhaskar Shenoy

“…In low-prevalence settings, the positive predictive value of T2MR might not be enough to justify the initiation of antifungal treatment in itself.…”
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Constructing a Classification Model for Cervical Cancer Tumor Tissue and Normal Tissue Based on CT Radiomics by Jinghong Pei BD, Jing Yu BD, Ping Ge BD, Liman Bao BD, Haowen Pang MS, Huaiwen Zhang MS

“…To bolster model's predictive capability, the data was stratified into train data (70%) and validation data (30%). …”
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Serum peptide biomarkers by MALDI-TOF MS coupled with machine learning for diagnosis and classification of hepato-pancreato-biliary cancers by Piya Prajumwongs, Attapol Titapun, Vasin Thanasukarn, Apiwat Jareanrat, Natcha Khuntikeo, Krit Rattanarak, Nisana Namwat, Poramate Klanrit, Arporn Wangwiwatsin, Jarin Chindaprasirt, Supinda Koonmee, Prakasit Sa-Ngiamwibool, Nattha Muangritdech, Sawanya Charoenlappanit, Janthima Jaresitthikunchai, Sittiruk Roytrakul, Watcharin Loilome

“…Feature selection on the training set identified 71 informative peptide mass fingerprints, which were then used to construct predictive models using SVM and RF algorithms. Visualization using heatmap, PLS-DA, and multiclass RF analysis showed clear separation between healthy individuals and HPB cancer patients, as well as among different HPB cancer subtypes. …”
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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

“…This narrative review synthesizes the evolving applications of AI in PBTs, focusing on early tumor detection, imaging analysis, therapy response prediction, and histological classification. AI-driven radiomics and predictive models have yielded promising results in assessing chemotherapy efficacy, optimizing preoperative imaging, and predicting treatment outcomes, thereby advancing the field of precision medicine. …”
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Beef Traceability Between China and Argentina Based on Various Machine Learning Models by Xiaomeng Xiang, Chaomin Zhao, Runhe Zhang, Jing Zeng, Liangzi Wang, Shuran Zhang, Diego Cristos, Bing Liu, Siyan Xu, Xionghai Yi

“…The classification accuracy of the PLS-DA model built on these results was 98.8%, while the prediction accuracy was 94.12% for the convolutional neural network (CNN) and 82.35% for the Random Forest algorithm. …”
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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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Integration of AI with artificial sensory systems for multidimensional intelligent augmentation by Changyu Tian, Youngwook Cho, Youngho Song, Seongcheol Park, Inho Kim, Soo-Yeon Cho

“…We introduce specialized AI algorithms and raw data processing methods for each function, designed to enhance and optimize sensing performance. …”
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