Miniaturized Near-Infrared Analyzer for Quantitative Detection of Trace Water in Ethylene Glycol by Qunling Luo, Zhiqiang Guo, Danping Lin, Boxue Chang, Yinlan Ruan

“…To address the limitations of a traditional Fourier-transform infrared (FTIR) spectrometer, including its bulky size, high cost, and unsuitability for on-site industrial detection, this study developed a Fourier-transform near-infrared (FT-NIR) absorption testing system utilizing Micro-Electro-Mechanical System (MEMS) technology for detecting trace water content in ethylene glycol. The modeling performances of three algorithms including Support Vector Machine Regression (SVMR), Principal Component Regression (PCR), and Partial Least Squares Regression (PLSR) were systematically evaluated, with PLSR identified as the optimal algorithm. …”
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The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea by Rafael Rodrigues dos Santos, Matheo Bellini Marumo, Alan Luiz Eckeli, Helio Cesar Salgado, Luiz Eduardo Virgílio Silva, Renato Tinós, Rubens Fazan

“…Minimum oxygen saturation value during sleep (SatMin), the percentage of total sleep time the patient spent with oxygen saturation below 90% (T90), and patient anthropometric data were also considered as inputs to the models. The Apnea-Hypopnea Index (AHI) was used to categorize into severity classes of OSA (normal, mild, moderate, severe) to train multiclass or binary (normal-to-mild and moderate-to-severe) classification models, using the Random Forest (RF) algorithm. …”
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Adaptive Feature Selection of Unbalanced Data for Skiing Teaching by Tao Feng

“…If the features are not selected, the model may overly rely on the features of common actions and ignore the features of difficult actions. …”
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RAD-Seq-derived SSR markers: a new paradigm for genetic analysis and construction of genetically improved production populations in Pinus koraiensis by Pingyu Yan, Wanying Zhang, Junfei Hao, Xiaotian Miao, Jun Wu, Zixiong Xie, Zhixin Li, Lei Zhang, Hanguo Zhang

“…A production population of 20 individuals was constructed via the simulated annealing algorithm, which exhibited a more reasonable mating system (F=−0.028) and demonstrated superior cone production compared with that of the plus tree population, with an increase of 79.6%. …”
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YOLO-RGDD: A Novel Method for the Online Detection of Tomato Surface Defects by Ziheng Liang, Tingting Zhu, Guang Teng, Yajun Zhang, Zhe Gu

“…Finally, dynamic convolution was used to replace the conventional convolution in the detection head in order to reduce the model parameter count. The experimental results show that the average precision, recall, and F1-score of the proposed YOLO-RGDD model for tomato defect detection reach 88.5%, 85.7%, and 87.0%, respectively, surpassing advanced object recognition detection algorithms. …”
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Remote clinical decision support tool for Parkinson’s disease assessment using a novel approach that combines AI and clinical knowledge by Harel Rom, Ori Peleg, Yovel Rom, Anat Mirelman, Gaddi Blumrosen, Inbal Maidan

“…Conclusions Our results demonstrate the feasibility of using advanced AI in a clinical decision support tool for PD diagnosis, suggesting a novel approach for home-based screening to identify PD patients. This method represents a significant innovation, transforming clinical knowledge into practical algorithms that can serve as effective screening tools. …”
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Prediction of clinical stages of cervical cancer via machine learning integrated with clinical features and ultrasound-based radiomics by Maochun Zhang, Qing Zhang, Xueying Wang, Xiaoli Peng, Jiao Chen, Hanfeng Yang

“…Prediction models were developed utilizing several ML algorithms by Python based on an integrated dataset of clinical features and ultrasound radiomics. …”
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Automated Vertebral Bone Quality Determination from T1-Weighted Lumbar Spine MRI Data Using a Hybrid Convolutional Neural Network–Transformer Neural Network by Kristian Stojšić, Dina Miletić Rigo, Slaven Jurković

“…The trained model performed similarly to state-of-the-art lumbar spine segmentation models, with an average DSC value of 0.914 ± 0.007 for the vertebrae and 0.902 for the spinal canal. …”
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Biochemical disturbances in schizophrenia — a «window of opportunity» by T. V. Zhilyaeva, A. S. Piatoikina, E. D. Kasyanov, G. V. Rukavishnikov, I. V. Semennov, O. V. Kostina, A. S. Blagonravova, G. E. Mazo

“…At the same time, there are no studies with an assessment of a wide range of correctable biochemical abnormalities in one sample of patients. Moreover, screening algorithms for the detection and personalized correction of controlled biomarkers have not been introduced into clinical practice yet.   …”
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Thyroid nodule classification in ultrasound imaging using deep transfer learning by Yan Xu, Mingmin Xu, Zhe Geng, Jie Liu, Bin Meng

“…In this study, we investigate the predictive efficacy of distinguishing between benign and malignant thyroid nodules by employing traditional machine learning algorithms and a deep transfer learning model, aiming to advance the diagnostic paradigm in this field. …”
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Artificial intelligence technology in ophthalmology public health: current applications and future directions by ShuYuan Chen, Wen Bai, Wen Bai

“…Key issues include interoperability with electronic health records (EHR), data security and privacy, data quality and bias, algorithm transparency, and ethical and regulatory frameworks. …”
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Different strokes: differences in the characteristics and outcomes of BCVI and non-BCVI strokes in trauma patients by Lillian S Kao, Charles E Wade, Xu Zhang, Bryan A Cotton, Sean I Savitz, Michelle K McNutt, Cedar Slovacek, David Rosenbaum, Hari Kishan Reddy Indupuru, John Harvin

“…Blunt cerebrovascular injury (BCVI)–related strokes and mortality have decreased, likely due to refined screening and treatment algorithms in trauma literature; however, there is a paucity of research addressing non-BCVI strokes in trauma. …”
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A low-cost platform for automated cervical cytology: addressing health and socioeconomic challenges in low-resource settings by José Ocampo-López-Escalera, Héctor Ochoa-Díaz-López, Xariss M. Sánchez-Chino, César A. Irecta-Nájera, Saúl D. Tobar-Alas, Martha Rosete-Aguilar

“…This disease is preventable and curable if detected in early stages, making regular screening critically important. Cervical cytology, the most widely used screening method, has proven highly effective in reducing cervical cancer incidence and mortality in high income countries. …”
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Serum Lipid Biomarkers for the Diagnosis and Monitoring of Neuromyelitis Optica Spectrum Disorder: Towards Improved Clinical Management by Li R, Wang J, Wang J, Xie W, Song P, Zhang J, Xu Y, Tian D, Wu L, Wang C

“…Subsequently, we validated the candidate biomarkers in the retrospective cohort and developed diagnostic models using a random forest algorithm. The association between these lipid biomarkers and disease activity was further evaluated in longitudinal analysis.Results: Our analysis identified a panel of serum lipid-related biomarkers that demonstrated significant differences between NMOSD patients and controls. …”
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Study on classification of aluminum plastic packaging tablets for drugs based on SOM-FDA using XRF spectroscopy(基于SOM-FDA利用XRF对药品铝塑包装片的分类) by 姜红(JIANG Hong), 康瑞雪(KANG Ruixue), 郝小辉(HAO Xiaohui)

“…The established classification model is scientifically accurate and can provide assistance for public security organs in large-scale screening, determining investigation directions, and shortening investigation time.…”
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Tool wear prediction based on XGBoost feature selection combined with PSO-BP network by Zhangwen Lin, Yankun Fan, Jinling Tan, Zhen Li, Peng Yang, Hua Wang, Weiwei Duan

“…Experimental results show that PSO outperforms other algorithms in training the tool wear prediction model, with XGBoost feature selection reducing model construction time by 57.4% and increasing accuracy by 63.57%, demonstrating superior feature selection capabilities over Decision Tree, Random Fores, Adaboost and Extra Trees. …”
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Optimizing deep learning for accurate blood cell classification: A study on stain normalization and fine-tuning techniques by Mohammed Tareq Mutar, Jaffar Nouri Alalsaidissa, Mustafa Majid Hameed, Ali Almothaffar

“…BACKGROUND: Deep learning’s role in blood film screening is expanding, with recent advancements including algorithms for the automated detection of sickle cell anemia, malaria, and leukemia using smartphone images. …”
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Efficient secure federated learning aggregation framework based on homomorphic encryption by Shengxing YU, Zhong CHEN

“…In order to solve the problems of data security and communication overhead in federated learning, an efficient and secure federated aggregation framework based on homomorphic encryption was proposed.In the process of federated learning, the privacy and security issues of user data need to be solved urgently.However, the computational cost and communication overhead caused by the encryption scheme would affect the training efficiency.Firstly, in the case of protecting data security and ensuring training efficiency, the Top-K gradient selection method was used to screen model gradients, reducing the number of gradients that need to be uploaded.A candidate quantization protocol suitable for multi-edge terminals and a secure candidate index merging algorithm were proposed to further reduce communication overhead and accelerate homomorphic encryption calculations.Secondly, since model parameters of each layer of neural networks had characteristics of the Gaussian distribution, the selected model gradients were clipped and quantized, and the gradient unsigned quantization protocol was adopted to speed up the homomorphic encryption calculation.Finally, the experimental results show that in the federated learning scenario, the proposed framework can protect data privacy, and has high accuracy and efficient performance.…”
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Advancements in Machine Learning (ML): Transforming the Future of Blood Cancer Detection and Outcome Prediction by Wiebke Rösler, Michael Roiss, Corinne Widmer

“…The diagnosis and treatment of hematologic malignancies are becoming more and more complex. Growing knowledge of pathophysiology, diagnostic methods and, last but not least, treatment options offer many opportunities for patients, but integrating the growing amount of knowledge into daily practice can be challenging. …”
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Load identification method based on one class classification combined with fuzzy broad learning by Wang Yi, Wang Xiaoyang, Li Songnong, Chen Tao, Hou Xingzhe, Fu Xiuyuan

“…Considering the recognition rate and model complexity, the fuzzy broad learning system is used to classify and recognize the screened samples. …”
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