A clinical study exploring the prediction of microvascular invasion in hepatocellular carcinoma through the use of combined enhanced CT and MRI radiomics. by Jiangfa Li, Wenxiang Song, Jixue Li, Lv Cai, Zhao Jiang, Mengxiao Wei, Boming Nong, Meiyu Lai, Yiyi Jiang, Erbo Zhao, Liping Lei

“…The optimal radiomics features of CT and MRI were selected to establish the prediction model. The predictive performance of the model was evaluated using the receiver operator characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).…”
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Early Response after Catheter Ablation of the Epicardial Substrate in a Patient with Brugada Syndrome Can Be Predicted by High Precordial Leads by Yae Min Park, Mi Sook Cha, Hanul Choi, Woong Chol Kang, Seung Hwan Han, In Suck Choi, Eak Kyun Shin, Young-Hoon Kim

“…We suggest that this novel ablation strategy is effective in Brugada syndrome patients with ICD, and early response after catheter ablation can be predicted by high precordial leads.…”
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Can Attention Deficits Predict a Genotype? Isolate Attention Difficulties in a Boy with Klinefelter Syndrome Effectively Treated with Methylphenidate by Antonella Gagliano, Eva Germanò, Loredana Benedetto, Gabriele Masi

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Prediction of biochemical prostate cancer recurrence from any Gleason score using robust tissue structure and clinically available information by Laura E. Marin, Daniel I. Zavaleta-Guzman, Jessyca I. Gutierrez-Garcia, Daniel Racoceanu, Fanny L. Casado

“…Our results provide a robust, cost-efficient approach using already available information to predict the risk of BCR.…”
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A mathematical model that predicts human biological age from physiological traits identifies environmental and genetic factors that influence aging by Sergiy Libert, Alex Chekholko, Cynthia Kenyon

“…The model predicted a person’s age with best accuracy when it heavily weighted traits that together query multiple organ systems, arguing that most or all physiological systems (lung, heart, brain, etc.) contribute to the global phenotype of chronological age. …”
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Identification of clinically-useful cut scores of the Traumatic Injuries Distress Scale (TIDS) for predicting rate of recovery following musculoskeletal trauma. by David M Walton, James M Elliott, Joshua Lee, Mohamad Fakhereddin, Wonjin Seo

“…<h4>Objective</h4>The Traumatic Injuries Distress Scale (TIDS) is a 12-item self-report tool intended for prognostic risk phenotyping in people with acute musculoskeletal (MSK) trauma. …”
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Endotype-driven prediction of acute exacerbations in chronic obstructive pulmonary disease (EndAECOPD): protocol for a prospective cohort study by Wei Xiao, Long-yi Du, Bing Mao, Ti-wei Miao, Juan-juan Fu

“…The effect of biomarkers representing genetic variants, airway inflammation and respiratory microbiome on predicting the frequent exacerbator phenotype and exacerbation frequency will be analysed with multivariable modelling, and time to first exacerbation with a Cox regression model.Ethics and dissemination The study has been approved by the Clinical Trial and Biomedical Ethics Committee of West China Hospital of Sichuan University (No. 2018–298). …”
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Prediction of Mature Body Weight of Indigenous Camel (<i>Camelus dromedarius</i>) Breeds of Pakistan Using Data Mining Methods by Daniel Zaborski, Wilhelm Grzesiak, Abdul Fatih, Asim Faraz, Mohammad Masood Tariq, Irfan Shahzad Sheikh, Abdul Waheed, Asad Ullah, Illahi Bakhsh Marghazani, Muhammad Zahid Mustafa, Cem Tırınk, Senol Celik, Olha Stadnytska, Oleh Klym

“…Six data mining methods [classification and regression trees (CARTs), chi-square automatic interaction detector (CHAID), exhaustive CHAID (EXCHAID), multivariate adaptive regression splines (MARSs), MLP, and RBF] were applied for ABW prediction. Additionally, hierarchical cluster analysis with Euclidean distance was performed for the phenotypic characterization of the camel breeds. …”
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Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer by Junyi Li, Shixin Li, Dongpo Zhang, Yibing Zhu, Yue Wang, Xiaoxiao Xing, Juefei Mo, Yong Zhang, Daixiang Liao, Jun Li

“…The IRGS demonstrated outstanding predictive performance across multiple datasets and surpassed 10 previously published signatures. …”
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Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder by Yilu Zhao, Zhao Fu, Eric J. Barnett, Ning Wang, Kangfuxi Zhang, Xuping Gao, Xiangyu Zheng, Junbin Tian, Hui Zhang, XueTong Ding, Shaoxian Li, Shuyu Li, Qingjiu Cao, Suhua Chang, Yufeng Wang, Stephen V. Faraone, Li Yang

“…Based on genotype data of medication-naïve patients with ADHD who received pharmacological treatments for 12 weeks, the current study performed GWAS using the percentage changes in ADHD-RS score as phenotype. Then, DL models were constructed to predict percentage changes in symptom scores using genetic variants selected based on four different genome-wide P thresholds (E-02, E-03, E-04, E-05) as inputs. …”
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The simpler modified fried frailty scale predicts 2-year mortality in older adults with heart failure: a pilot study by Celalettin Küçük, Serdar Özkök, Gülistan Bahat, Ekrem Bilal Karaayvaz, Mustafa Altınkaynak, Alpay Medetalibeyoğlu, Mehmet Akif Karan

“…SMFFS was used to assess frailty phenotype and presence of ≥ 3 items was accepted as frailty. …”
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Development and Validation of a TNF Family-Based Signature for Predicting Prognosis, Tumor Immune Characteristics, and Immunotherapy Response in Colorectal Cancer Patients by Zheng Xiao, Kechao Nie, Tong Han, Lin Cheng, Zheyu Zhang, Weijun Peng, Dazun Shi

“…Conversely, a low TFS risk score was related to high infiltration of resting CD4 memory T cells and resting dendritic cells, few immune escape phenotypes, and high sensitivity to immunotherapy. Thus, the eight gene-based TFS is a promising index to predict the prognosis, immune characteristics, and immunotherapy response in CRC, and our results also provide new understanding of the role of the TNF family members in the prognosis and treatment of CRC.…”
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Decoding Quantitative Traits in Yaks: Genomic Insights for Improved Breeding Strategies by Yujiao Fu, Yuanyuan Yu, Xinjia Yan, Daoliang Lan, Jiabo Wang

“…This review explores the application and potential of molecular marker-assisted selection (MAS) and genomic prediction (GP) in yak genetic improvement. We systematically evaluate critical components of genomic breeding pipelines, including: (1) phenotypic trait assessment, (2) sample collection strategies, (3) reference population design, (4) high-throughput genotyping (via genome sequencing and SNP arrays), (5) predictive model development, and (6) heritability estimation. …”
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Multiple machine learning algorithms identify 13 types of cell death-critical genes in large and multiple non-alcoholic steatohepatitis cohorts by Renao Jiang, Longfei Dai, Xinjian Xu, Zhen Zhang

“…Results A NASH prediction model, developed using the random forest (RF) algorithm, demonstrated high diagnostic accuracy across multiple cohorts. …”
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Abnormal phosphorylation of human LRH1 at Ser510 predicts poor prognosis and promotes cell viability in lung squamous cell carcinoma by Hayato Mine, Kotaro Sugimoto, Makoto Kobayashi, Hironori Takagi, Naoyuki Okabe, Satoshi Muto, Yasuyuki Kobayashi, Yuko Hashimoto, Hiroyuki Suzuki, Hideki Chiba

“…Thus, hLRH1pS510 is attractive not only as the predictive biomarker for LUSC but also as the potential therapeutic target.…”
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CD161+CD127+CD8+ T cell subsets can predict the efficacy of anti-PD-1 immunotherapy in non-small cell lung cancer with diabetes mellitus by Jingjing Qu, Yuekang Li, Binggen Wu, Qian Shen, Lijun Chen, Wenjia Sun, Bo Wang, Lixiong Ying, Li Wu, Hong Zhou, Jianya Zhou, Jianying Zhou

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Mendelian randomization analysis reveals the potential of the IKZF1 gene as a therapeutic target in colorectal cancer by Junzuo Lin, Qian Xu, Zhengfei Zhao

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Non-invasive liver fibrosis markers are increased in obese individuals with non-alcoholic fatty liver disease and the metabolic syndrome by Anders Askeland, Rikke Wehner Rasmussen, Mimoza Gjela, Jens Brøndum Frøkjær, Kurt Højlund, Maiken Mellergaard, Aase Handberg

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Genome-wide association study and genomic prediction of root system architecture traits in Sorghum (Sorghum bicolor (L.) Moench) at the seedling stage by Muluken Enyew, Mulatu Geleta, Kassahun Tesfaye, Amare Seyoum, Tileye Feyissa, Admas Alemu, Cecilia Hammenhag, Anders S. Carlsson

“…For GP, ridge-regression best linear unbiased prediction (RR-BLUP) and five different Bayesian models were applied. …”
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Using Blood Group Genotyping to Predict Hemolysis in Patients With β-Thalassemia Major With Frequent Transfusions: Protocol for a Cross-Sectional Study by Vitasari Indriani, Teguh Triyono, Budi Mulyono

“…In Indonesia, the role of blood group genotyping in predicting hemolysis has not been thoroughly studied. …”
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