The Role of [18F]FDG PET Imaging for the Assessment of Pulmonary Lymphangitic Carcinomatosis: A Comprehensive Narrative Literature Review by Francesco Dondi, Pietro Bellini, Michela Cossandi, Luca Camoni, Roberto Rinaldi, Gian Luca Viganò, Francesco Bertagna

“…Future research should explore novel tracers (e.g., PSMA for prostate cancer-related PLC) and machine learning approaches to refine diagnostic and prognostic accuracy. …”
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Strategy to improve the confidence level of qualitative screening by high resolution mass spectrometry: A case study of mycotoxins in maize by Yan Gao, Mengyu Feng, Xiuqin Li, Yan Zhang, Jinglei Hu, Kangcong Li, Jianhua Duan, Qinghe Zhang

“…A quantitative structure-retention relationships (QSRR) model was developed for retention time prediction and projection using machine learning, providing supplementary evidence for molecule annotation. …”
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Toxicological evaluation of mycotoxins in tetra-pack milk samples using advanced analytical techniques by Ruby Khan, Sumbal Khan, Hailah M. Almohaimeed, Bakht Pari

“…Methods:: We employed LC–MS/MS (LOD: 0.05μg/L) with confirmatory TLC analysis on 126 milk samples, coupled with IoT sensors tracking temperature (±0.5°C), relative humidity (±3%), and pH (±0.2) at critical control points. A machine learning model incorporating Arrhenius kinetics was developed to predict contamination patterns. …”
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Impact of short-term soil disturbance on cadmium remobilization and associated risk in vulnerable regions by Zhong Zhuang, Hao Qi, Siyu Huang, Qiqi Wang, Yanan Wan, Huafen Li

“…The model predicted that the probabilities of grain exceeding Cd thresholds ranged from 021.6 % for rice, 13.8 %100 % for wheat, and 084.2 % for maize in the absence of fertilizer use. …”
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From Policy to Prices: How Carbon Markets Transmit Shocks Across Energy and Labor Systems by Cristiana Tudor, Aura Girlovan, Robert Sova, Javier Sierra, Georgiana Roxana Stancu

“…XGBoost models ascertain that policy uncertainty and Brent oil prices are the most significant predictors of one-month-ahead ETSs, whereas ESG factors are relevant only beyond certain thresholds and in conditions of low policy uncertainty. …”
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Review of advancements and challenges in delayed irrigation: Enhancing crop water productivity and sustainable crop production by Run Xue, Yue Jiang, Hong Li, Bin Shi

“…Future research should focus on identifying crop-specific water thresholds under diverse environmental conditions, developing multi-objective optimization models (water conservation, emission reduction, and yield enhancement), and integrating interdisciplinary technologies (e.g., IoT and deep learning) to enable precise DI implementation in global agricultural systems, fostering coordinated progress in water resource management and climate action.…”
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In-Season Automated Mapping of Xinjiang Cotton Based on Cumulative Spectral and Phenological Characteristics by Yongsheng Huang, Yaozhong Pan, Yu Zhu, Xiufang Zhu, Xingsheng Xia, Qiong Chen, Jufang Hu, Hongyan Che, Xuechang Zheng, Lingang Wang

“…Methods based on machine learning, and deep learning, rely on a large number of training samples, which is time-consuming and laborious. …”
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Soft graph clustering for single-cell RNA sequencing data by Ping Xu, Pengfei Wang, Zhiyuan Ning, Meng Xiao, Min Wu, Yuanchun Zhou

“…These constructions introduce difficulties when applied to scRNA-seq data due to: (i) The simplification of intercellular relationships into binary edges (0 or 1) by applying thresholds, which restricts the capture of continuous similarity features among cells and leads to significant information loss. …”
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Plasma proteomics for biomarker discovery in childhood tuberculosis by Andrea Fossati, Peter Wambi, Devan Jaganath, Roger Calderon, Robert Castro, Alexander Mohapatra, Justin McKetney, Juaneta Luiz, Rutuja Nerurkar, Esin Nkereuwem, Molly F. Franke, Zaynab Mousavian, Jeffrey M. Collins, George B. Sigal, Mark R. Segal, Beate Kampman, Eric Wobudeya, Adithya Cattamanchi, Joel D. Ernst, Heather J. Zar, Danielle L. Swaney, On behalf of the COMBO Study Consortium

“…By employing a machine learning approach, we derive four parsimonious biosignatures encompassing 3 to 6 proteins that achieve AUCs of 0.87–0.88 and which all reach the minimum WHO target product profile accuracy thresholds for a TB screening test. …”
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A longitudinal cohort study uncovers plasma protein biomarkers predating clinical onset and treatment response of rheumatoid arthritis by Siyu He, Chenxi Zhu, Yi Liu, Zhiqiang Xu, Rui Sun, Bin Yang, Xin Guo, Martin Herrmann i, Luis E. Muñoz, Inger Gjertsson, Rikard Holmdahl, Lunzhi Dai, Yi Zhao

“…A machine-learning model is trained for predicting responses, and achieves average receiver operating characteristic (ROC) scores of 0.88 (MTX + LEF) and 0.82 (MTX + HCQ) in the testing sets. …”
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Application of X-bar R Control Charts for Process Efficiency Monitoring: A Data-Driven Approach in Quality Management by Aleksy Kwilinski, Maciej Kardas, Nataliia Trushkina

“…The methodology involves constructing X-bar R control charts to monitor variability patterns, establish stability thresholds, and pinpoint critical sources of process deviations. …”
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Deciphering Socio-Spatial Integration Governance of Community Regeneration: A Multi-Dimensional Evaluation Using GBDT and MGWR to Address Non-Linear Dynamics and Spatial Heterogene... by Hong Ni, Jiana Liu, Haoran Li, Jinliu Chen, Pengcheng Li, Nan Li

“…Our findings reveal critical intersections where residential density thresholds interact with commercial accessibility patterns and transport network configurations. …”
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Statistical inference and effect measures in abstracts of major HIV and AIDS journals, 1987–2022: A systematic review by Andreas Stang, Henning Schäfer, Ahmad Idrissi-Yaghir, Christoph M. Friedrich, Matthew P. Fox

“…We applied rule-based text mining and machine learning methodology to detect the presence of confidence intervals, numerical p-values or comparisons of p-values with thresholds, language describing statistical significance, and effect measures for dichotomous outcomes Results: Among 41,730 PubMed entries from the major HIV/AIDS journals, 31,665 contained an abstract. …”
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Automatic adventitious respiratory sound analysis: A systematic review. by Renard Xaviero Adhi Pramono, Stuart Bowyer, Esther Rodriguez-Villegas

“…Detection or classification methods used varied from empirically determined thresholds to more complex machine learning techniques. …”
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Designing a cultivation model for top-notch students in basic medicine: a Delphi method by Geng Ni, Yutong Qin, Fangfang Wang, Jianjun Huang

“…Adjustments were made based on statistical thresholds (e.g., arithmetic mean < 4, full score ratio < 0.5, or variation coefficient > 0.25) and expert consensus. …”
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Automatic Correction of Labeling Errors Applied to Tomato Detection by Ángel Eduardo Zamora Suárez, Gerardo Antonio Alvarez Hernandez, Juan Irving Vasquez, Hind Taud, Abril Valeria Uriarte-Arcia, Erik Zamora

“…Experimental results show substantial improvements: the mean Average Precision at an IoU threshold of 0.50 (mAP-50) increased from 0.8 to 0.86, the mean Average Precision across IoU thresholds from 0.50 to 0.95 (mAP-50:95) increased from 0.46 to 0.63, and Recall improved from 0.68 to 0.82. …”
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Responsiveness of the mini-balance evaluation systems test, dynamic gait index, Berg balance scale, and performance-oriented mobility assessment in parkinson’s disease by Maryam Mehdizadeh, Seyed-Mohammad Fereshtehnejad, Merrill R. Landers, Parvaneh Taghavi Azar Sharabiani, Mohsen Shati, Seyede Salehe Mortazavi, Sayed Amir Hasan Habibi, Korosh Mansoori, Mahsa Meimandi, Zahra Nodehi, Zakieh Sadat Saberi, Ghorban Taghizadeh

“…Predictive modeling (MIDpred) yielded higher thresholds (e.g., 4.0 for Mini-BESTest), likely reflecting baseline variability. …”
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Slope deformation prediction based on GA–BP neural networks by Wenhui TAN, Kai LI, Huimin LIU, Meifeng CAI, Qifeng GUO

“…However, with advancements in artificial intelligence, machine learning has emerged as an important method for predicting slope deformation in open-pit mines. …”
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Optimizing Automated Hematoma Expansion Classification from Baseline and Follow-Up Head Computed Tomography by Anh T. Tran, Dmitriy Desser, Tal Zeevi, Gaby Abou Karam, Julia Zietz, Andrea Dell’Orco, Min-Chiun Chen, Ajay Malhotra, Adnan I. Qureshi, Santosh B. Murthy, Shahram Majidi, Guido J. Falcone, Kevin N. Sheth, Jawed Nawabi, Seyedmehdi Payabvash

“…In this study, we combined a tandem deep-learning classification model with automated segmentation to generate probability measures for false HE classifications. …”
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Attention Mechanism and Weighted Trend Loss for Wind Speed Correction by Liu Xu, Yang Hao, Liang Xiaoyun, Chen Jing, Li Qiaoping, Li Ruqing, Chen Min

“…To address the systematic bias in simulating 10-m wind speed using MIROC6 model within CMIP6 framework, a novel approach based on deep learning is proposed. A non-stationary Informer model (Ns-Informer) is integrated with an adaptive-length attention mechanism and a multilayer perceptron (MLP) dynamic adjustment module to enhance the model's correction performance, particularly in high wind speed conditions. …”
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