An artificial intelligence approach to palaeogeographic studies: a case study of the Late Ordovician brachiopods of Laurentia by Akbar Sohrabi

“…Based on the training algorithm and after 146 periods, the training error decreased, but the validation error increased (Fig. 7). …”
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Integration of graph neural networks and transcriptomics analysis identify key pathways and gene signature for immunotherapy response and prognosis of skin melanoma by Maodong Ye, Shuai Ren, Huanjuan Luo, Xiumin Wu, Hongwei Lian, Xiangna Cai, Yingchang Ji

“…Graph neural networks (GNNs), alongside other deep learning algorithms and bioinformatics approaches, have demonstrated substantial promise in advancing cancer diagnosis and treatment strategies. …”
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The Persistent Threat of Chronic Inflammation on the Mortality Among Cervical Cancer Survivors: A Mendelian Randomization and Machine Learning Analysis Using UK Biobank and Chinese... by Wang J, Chen Z, Guan M, Ma Z, Peng L, Chen J, Fiori PL, Carru C, Capobianco G, Coradduzza D, Zhou L

“…We aimed to comprehensively evaluate the genetic association between inflammation and cervical cancer, and construct an accurate prognosis model based on circulating inflammatory parameters and indexes with machine learning (ML) algorithms.Patients and Methods: We tested the genome-wide association of circulating inflammatory molecules (CIMs) (91 circulating inflammatory cytokines and 10 inflammatory cells) and summary data retrieved from the UK biobank (cases = 1659 and controls =381,902) with two-sample Mendelian randomization (MR) and colocalization analyses. …”
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Prognostic prediction for inflammatory breast cancer patients using random survival forest modeling by Yiwei Jia, Chaofan Li, Cong Feng, Shiyu Sun, Yifan Cai, Peizhuo Yao, Xinyu Wei, Zeyao Feng, Yanbin Liu, Wei Lv, Huizi Wu, Fei Wu, Lu Zhang, Shuqun Zhang, Xingcong Ma

“…Random survival forest (RSF) algorithm was adopted to construct an accurate prognostic prediction model for IBC patients. …”
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Merging Various Types of Remote Sensing Data and Social Participation GIS with AI to Map the Objects Affected by Light Occlusion by Yen-Chun Lin, Teng-To Yu, Yu-En Yang, Jo-Chi Lin, Guang-Wen Lien, Shyh-Chin Lan

“…The dataset comprised 20,889 images, with 98% being used for training and validation and 2% being used for independent testing. …”
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Predicting Kinematic Viscosity and Cetane Number of Diesel- Biodiesel Blend Using Neural Network and Empirical Models by M. yari, Gh. Moradi, M. Abdolmaleki, Sh. Bashiri

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Prediction of additional hospital days in patients undergoing cervical spine surgery with machine learning methods by Bin Zhang, Shengsheng Huang, Chenxing Zhou, Jichong Zhu, Tianyou Chen, Sitan Feng, Chengqian Huang, Zequn Wang, Shaofeng Wu, Chong Liu, Xinli Zhan

“…Background Machine learning (ML), a subset of artificial intelligence (AI), uses algorithms to analyze data and predict outcomes without extensive human intervention. …”
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An integrated machine learning framework for developing and validating diagnostic models and drug predictions based on ulcerative colitis genes by Na An, Zhongwen Lu, Yang Li, Bing Yang, Shaozhen Ji, Xu Dong, Zhaoliang Ding

“…Next, we identified differentially expressed genes (DEGs) that are associated with UC. Using the WGCNA algorithm, we screened key module genes in UC and retrieved immune-related genes (IRGs) from the ImmPort database. …”
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The signature based on interleukin family and receptors identified IL19 and IL20RA in promoting nephroblastoma progression through STAT3 pathway by Chen Ding, Hongjie Gao, Liting Zhang, Zhiyi Lu, Bowen Zhang, Ding Li, Fengyin Sun

“…Our analysis ultimately identified five genes associated with prognosis: IL20RA, IL19, IL24, IL11 and IL17RD. …”
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Mining hypertension predictors using decision tree: Baseline data of Kharameh cohort study by abbas Rezaianzadeh, Samane Nematolahi, maryam jalali, Shayan Rezaeianzadeh, Masoumeh Ghoddusi Johari, Seyed Vahid Hosseini

“… Background: Hypertension is a serious chronic disease and an important risk factor for many health problems. this study aimed to investigate the factors associated with hypertension using a decision-tree algorithm. …”
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Immune Microenvironment Characterization and Machine Learning-Guided Identification of Diagnostic Biomarkers for Ulcerative Colitis by Zheng Q, Wang L, Zhang Y, Peng J, Hou J, Wang H, Ma Y, Tang P, Li Y, Li H, Chen Y, Li J, Chen Y

“…It employs machine learning algorithms to construct diagnostic models, including an optimal 8-gene model (GATA2, IL8, LAT, NOLC1, SMARCA5, SMC3, STX10, ZMIZ1), which demonstrates high predictive performance (AUC of 0.964 in training datasets and 0.884 in testing datasets). …”
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A Machine Vision Perspective on Droplet‐Based Microfluidics by Ji‐Xiang Wang, Hongmei Wang, Huang Lai, Frank X. Liu, Binbin Cui, Wei Yu, Yufeng Mao, Mo Yang, Shuhuai Yao

“…To address the long‐standing challenges associated with the accurate and efficient identification, sorting, and analysis of the morphology and generation rate of single and double emulsion droplets, a novel machine vision approach utilizing the deformable detection transformer (DETR) algorithm is proposed. …”
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Early prediction of colorectal adenoma risk: leveraging large-language model for clinical electronic medical record data by Xiaoyu Yang, Jinjian Xu, Hong Ji, Jun Li, Bingqing Yang, Liye Wang

“…Several classical machine learning algorithms were applied in combination with the BGE-M3 large-language model (LLM) for enhanced semantic feature extraction. …”
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Machine learning model to predicting synergy of ultrasonication and solvation impacts on crude oil viscosity by Nasir Khan, Mehdi Razavifar, Qazi Adnan Ahmad, Muhammad Siyar, Masoud Riazi, Waqar Khan, Jafar Qajar

“…In this study, we develop a machine learning-based algorithm to rigorously predict the synergistic effects of ultrasonication and solvation on crude oil viscosity. …”
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Exploring the Role of Peritumoral Edema in Predicting Lung Cancer Subtypes Through T2-FLAIR Digital Subtraction Imaging of Metastatic Brain Tumors by Okan Dilek, Emin Demırel, Zeynel Abidin Tas, Emre Bılgın

“…The maximum relevance–minimum redundancy (mRMR) method was then used for dimensionality reduction. The Naive Bayes algorithm was used for model development, and the interpretability of the model was explored using SHapley Additive exPlanations (SHAP). …”
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Construction and validation of a readmission risk prediction model for elderly patients with coronary heart disease by Hanyu Luo, Benlong Wang, Rui Cao, Jun Feng

“…XGBoost, LR, RF, KNN and DT algorithms were used to build prediction models for readmission risk. …”
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Identification of a novel ferroptosis-induced immunogenic cell death related signature based on a machine learning framework in colorectal cancer by Feng Zhu, Xin Liu, Huiyuan Li, Jianfeng Li, Hongzhang Liu, Yusheng Wang

“…The RSF algorithm was chosen for further analysis due to its strong predictive performance, making it a robust tool for our study. …”
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Automatic Detect Incorrect Lifting Posture with the Pose Estimation Model by Gee-Sern Jison Hsu, Jie Syuan Wu, Yin-Kai Dean Huang, Chun-Chieh Chiu, Jiunn-Horng Kang

“…We used the OpenPose algorithm to detect and extract key body points to calculate relevant biomechanical features. …”
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Optimized CNN-Bi-LSTM–Based BCI System for Imagined Speech Recognition Using FOA-DWT by Meenakshi Bisla, Radhey Shyam Anand

“…EEG signal is enhanced using firefly optimization algorithm (FOA)–based optimized soft thresholding of high-frequency detail components obtained by DWT decomposition. …”
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Effect of Molarity of Sodium Hydroxide on the Strength Behavior of Fiber-Reinforced Geopolymer Concrete Exposed to Elevated Temperature by Abbasali Saffar, Mohammad Ehsanifar, Seyed Mohammad Mirhoseini, Mohammad Javad Taheri Amiri

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