The Chaotic Prediction for Aero-Engine Performance Parameters Based on Nonlinear PLS Regression by Chunxiao Zhang, Junjie Yue

“…At the same time, the forecast error is less than that of nonlinear PLS algorithm through bootstrap test screening.…”
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An Upper Partial Moment Framework for Pathfinding Problem Under Travel Time Uncertainty by Xu Zhang, Mei Chen

“…Theoretical analysis shows that the MUPM framework is consistent with the expected utility theory (EUT) and stochastic dominance theory (SDT), providing a behavioral foundation for the model. To efficiently solve the model, an SDT-based label-correcting algorithm is adapted, with a pre-screening step to reduce unnecessary pairwise path comparisons. …”
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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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Distinguishing novel coronavirus influenza A virus pneumonia with CT radiomics and clinical features by Lianyu Sui, Huan Meng, Jianing Wang, Wei Yang, Lulu Yang, Xudan Chen, Liyong Zhuo, Lihong Xing, Yu Zhang, Jingjing Cui, Xiaoping Yin

“…And then combining these features of the two to construct a combined model. Receiver operating characteristic curve (ROC), calibration curve, and decision curve were performed to evaluate the classification of the radiomics model, clinical model and combined model. …”
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Artificial Intelligence in Biomedical Sciences: A Scoping Review by Rasha Abu-El-Ruz, Ali Hasan, Dima Hijazi, Ovelia Masoud, Atiyeh M. Abdallah, Susu M. Zughaier, Maha Al-Asmakh, Maha Al-Asmakh

“…Scope (6): Opportunities and limitations of AI in biomedical sciences, where major reported opportunities include efficiency, accuracy, universal applicability, and real-world application. Limitations include; model complexity, limited applicability, and algorithm robustness.ConclusionAI has generally been under characterized in the biomedical sciences due to variability in AI models, disciplines, and perspectives of applicability.…”
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Identification method of roof rock interface based on response characteristics of drilling parameters by LI Dianshang, LIU Cancan, WANG Chuanbing, REN Bo, REN Shuai, KANG Zhipeng

“…Then, the accuracy of rock interface identification was analyzed using parameters such as penetration rate, revolution per minute, sound pressure level, and torque using the application of the change point detection algorithm, the strucchange model in RStudio software, and the decision tree algorithm. …”
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A phase separation-related gene signature for prognosis prediction and immunotherapy response evaluation in gastric cancer with targeted natural compound discovery by Yanjuan Jia, Yuanyuan Ma, Zhenhao Li, Wenze Zhang, Rukun Lu, Wanxia Wang, Chaojun Wei, Chunyan Wei, Yonghong Li, Xiaoling Gao, Tao Qu

“…Immune checkpoint inhibitor (ICI) response between PS-related high- and low-risk groups was evaluated using TIDE algorithm scores. Potential therapeutic agents targeting signature genes were screened via Connectivity Map and HERB database analyses, followed by molecular docking validation. …”
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Potential Metabolic Markers in the Tongue Coating of Chronic Gastritis Patients for Distinguishing Between Cold Dampness Pattern and Damp Heat Pattern in Traditional Chinese Medici... by Yuan S, Zhang R, Zhu Z, Zhou X, Zhang H, Li X, Hao Y

“…We applied metabolomics to identify differential metabolites distinguishing these patterns.Methods: In this study, the first principal component was analyzed by the OPLS-DA model. The model quality was evaluated by 7-fold cross-validation, and the model validity was evaluated based on R²Y (interpretability of categorical variable Y) and Q² (predictability of the model), and the permutation test was used for further verification. …”
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Development of a method for differential diagnosis of iron deficiency anemia and anemia of chronic disease based on demographic data and routine laboratory tests using machine lear... by N. V. Varekha, N. I. Stuklov, K. V. Gordienko, R. R. Gimadiev, O. B. Shchegolev, S. N. Kislaya, E. V. Gubina, A. A. Gurkina

“…A dataset of 9771 patients with micro‑normocytic anemia was used to create the model. On the basis of demographic data (gender and age), clinical blood count, C‑reactive protein level and known SF level, a regression model was developed to calculate the expected SF concentration in a particular patient and, using the same parameters, a classification model to determine the SF level group to which the patient belongs: I – < 15 μg / L; II – 15–100 μg / L; III – 100–300 μg / L; Iv – ≥ 300 μg / L.   …”
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Combinations of multimodal neuroimaging biomarkers and cognitive test scores to identify patients with cognitive impairment by Yuriko Nakaoku, Soshiro Ogata, Kiyotaka Nemoto, Chikage Kakuta, Eri Kiyoshige, Kanako Teramoto, Kiyomasa Nakatsuka, Gantsetseg Ganbaatar, Masafumi Ihara, Kunihiro Nishimura

“…Finally, MCI identification models were developed using a penalized logistic regression model with an elastic net algorithm.ResultsAmong the 148 participants (mean age, 78.6 ± 5.2 years), 44.6% were identified as having MCI. …”
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Machine learning prediction of metabolic dysfunction-associated fatty liver disease risk in American adults using body composition: explainable analysis based on SHapley Additive e... by Yan Hong, Xinrong Chen, Ling Wang, Fan Zhang, ZiYing Zeng, Weining Xie

“…The Boruta algorithm was used for feature selection, and model performance was evaluated using cross-validation and a validation set. …”
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Deep learning system for the auxiliary diagnosis of thyroid eye disease: evaluation of ocular inflammation, eyelid retraction, and eye movement disorder by Yu Han, Jun Xie, Xiaoyu Li, Xinying Xu, Bin Sun, Han Liu, Chunfang Yan

“…The designed quantitative algorithm provides greater interpretability than existing studies, thereby validating the effectiveness of the diagnostic system.ConclusionThe deep learning-based auxiliary diagnostic model for TED established in this study exhibits high accuracy and interpretability in the diagnosis of ocular inflammation related to CAS, eyelid retraction, and eye movement disorders. …”
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Enhancing semi‐supervised contrastive learning through saliency map for diabetic retinopathy grading by Jiacheng Zhang, Rong Jin, Wenqiang Liu

“…Hence, the development of efficient automated DR grading systems is crucial for early screening and treatment. Although progress has been made in DR detection using deep learning techniques, these methods still face challenges in handling the complexity of DR lesion characteristics and the nuances in grading criteria. …”
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Research on Feature Extraction of Performance Degradation for Flexible Material R2R Processing Roller Based on PCA by Yaohua Deng, Huiqiao Zhou, Kexing Yao, Zhiqi Huang, Chengwang Guo

“…The Jacobi iteration method was introduced to derive the algorithm for solving eigenvalue and eigenvector of the covariance matrix. …”
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Multi‐Omic Analysis Reveals a Lipid Metabolism Gene Signature and Predicts Prognosis and Chemotherapy Response in Thyroid Carcinoma by Yuqin Tu, Yanchen Chen, Linlong Mo, Guiling Yan, Jingling Xie, Xinyao Ji, Shu Chen, Changchun Niu, Pu Liao

“…The immune landscape was evaluated using the CIBERSORT algorithm, and chemotherapeutic response was predicted utilizing the “pRRophetic” R package. …”
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Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech by Julianna Olah, Win Lee Edwin Wong, Atta-ul Raheem Rana Chaudhry, Omar Mena, Sunny X. Tang

“…Linguistic and paralinguistic features were extracted and ensemble learning algorithms (e.g., XGBoost) were used to train models. …”
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An incremental data-driven approach for carbon emission prediction and optimization of heat treatment processes by Qian Yi, Xin Wu, Junkang Zhuo, Congbo Li, Chuanjiang Li, Huajun Cao

“…Using life cycle assessment (LCA) theory, carbon emission sources are accurately analyzed and quantified, and a full life cycle carbon emission model is established. The key process parameters affecting part performance and carbon emission were screened through mechanism analysis, and the incremental data were fused by the Elasticity Weight Consolidation (EWC) algorithm to establish an EWC-BPNN heat treatment carbon emission prediction model. …”
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Chinese AI tool ERNIE Bot Textual Exploration of False Information by Fu Yue

“…In order to improve the accuracy of detection, this paper proposes countermeasures to improve the AI detection algorithm, enhance data training and model optimisation, and human-machine collaboration. …”
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Machine learning, clinical-radiomics approach with HIM for hemorrhagic transformation prediction after thrombectomy and treatment by Sheng Hu, Junyu Liu, Jiayi Hong, Yuting Chen, Ziwen Wang, Jibo Hu, Shiying Gai, Xiaochao Yu, Jingjing Fu

“…An optimal machine learning (ML) algorithm was used for model development. Subsequently, models for clinical, radiomics, and clinical-radiomics were developed. …”
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Tuberculosis Lesion Segmentation Improvement in X-Ray Images Using Contextual Background Label by Sahasat Khumang, Supaporn Kansomkeat, Wiwatana Tanomkiat, Sathit Intajag

“…To detect PTB at an early stage by screening chest X-Ray (CXR) images for tuberculosis (TB) lesions, we propose a semantic segmentation scheme that uses a deep learning algorithm. …”
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