A nicotinamide metabolism-related gene signature for predicting immunotherapy response and prognosis in lung adenocarcinoma patients by Meng Wang, Wei Li, Fang Zhou, Zheng Wang, Xiaoteng Jia, Xingpeng Han

“…Next, the MCP-counter, TIMER and ESTIMATE algorithms were utilized to comprehensively assess the immune microenvironmental profile of LUAD patients in different risk groups. …”
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Identification and validation of cellular senescence-related genes and immune cell infiltration characteristics in intervertebral disc degeneration by Hao Li, Lei Miao, Jiayuan Wu, Ye Wang, Jiyuan Xia, Da He

“…A protein–protein interaction (PPI) network was also drawn, and the hub SRDEGs were obtained using 11 different algorithms. Immune infiltration analysis was then performed. …”
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AI for rapid identification of major butyrate-producing bacteria in rhesus macaques (Macaca mulatta) by Annemiek Maaskant, Donghyeok Lee, Huy Ngo, Roy C. Montijn, Jaco Bakker, Jan A. M. Langermans, Evgeni Levin

“…However, the lack of transparency in these technologies limits the ability of clinicians to incorporate AI-driven diagnostic tools into their healthcare systems. The aim of this study was to investigate an AI approach that rapidly predicts different bacterial genera and bacterial groups, specifically butyrate producers, from digital images of fecal smears of rhesus macaques (Macaca mulatta). …”
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ERBB3-related gene PBX1 is associated with prognosis in patients with HER2-positive breast cancer by Shufen Mo, Haiming Zhong, Weiping Dai, Yuanyuan Li, Bin Qi, Taidong Li, Yongguang Cai

“…Utilizing three distinct machine learning algorithms, we identified three signature genes-PBX1, IGHM, and CXCL13-that exhibited significant diagnostic value within the diagnostic model. …”
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Presentation matters: Impact of association of amphiphilic LPS with serum carrier proteins on innate immune signaling. by Loreen R Stromberg, Heather M Mendez, Jessica Z Kubicek-Sutherland, Steven W Graves, Nicolas W Hengartner, Harshini Mukundan

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The State of Artificial Intelligence and its Prospects in Pakistan's Medical Sector by Rohail Akhtar Habib, Yumna Sattar Khan

“…In Pakistan, AI has significantly improved diagnostic imaging. AI algorithms are used by radiologists and other healthcare professionals to interpret medical pictures, resulting in more accurate and timely diagnosis. …”
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Effectiveness of AI for Enhancing Computed Tomography Image Quality and Radiation Protection in Radiology: Systematic Review and Meta-Analysis by Subo Zhang, Zhitao Zhu, Zhenfei Yu, Haifeng Sun, Yi Sun, Hai Huang, Lei Xu, Jinxin Wan

“…ConclusionsThe findings suggest that AI-based interventions can significantly enhance CT imaging practices by improving image quality and potentially reducing radiation doses, which may lead to better diagnostic accuracy and patient safety. However, these results should be interpreted with caution due to the limited number of studies and the variability in AI algorithms. …”
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Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome by Yaxuan He, Zekai Chen, Zhaohui Tang, Yuexiang Qin, Fang Wang

“…Objective To develop a non-invasive prediction model for MetS by integrating body roundness index (BRI), gender, age, height, and waist circumference with machine learning algorithms, and to validate its generalizability across different ethnic groups. …”
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Machine learning for the prediction of mortality in patients with sepsis-associated acute kidney injury: a systematic review and meta-analysis by Xiangui Lv, Daiqiang Liu, Xinwei Chen, Lvlin Chen, Xiaohui Wang, Xiaomei Xu, Lin Chen, Chao Huang

“…It is also eagerly anticipated that future research efforts will incorporate larger sample sizes and multi-centre studies to more intensively examine the external validation of these models in different patient populations, allowing for a more in-depth exploration of sepsis-associated acute kidney injury in terms of accurate diagnostic efficacy across a diverse range of model and predictor types. …”
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Machine learning-based prediction of antimicrobial resistance and identification of AMR-related SNPs in Mycobacterium tuberculosis by Yi Xu, Ying Mao, Xiaoting Hua, Yan Jiang, Yi Zou, Zhichao Wang, Zubi Liu, Hongrui Zhang, Lingling Lu, Yunsong Yu

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Subtypes detection of papillary thyroid cancer from methylation assay via Deep Neural Network by Andrea Colacino, Andrea Soricelli, Michele Ceccarelli, Ornella Affinito, Monica Franzese

“…Background and Objective: In recent years, DNA methylation-tumor classification based on artificial intelligence algorithms has led to a notable improvement in diagnostic accuracy compared to traditional machine learning methods. …”
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New Insights into the Role of the Immune Microenvironment in Breast Carcinoma by Luis de la Cruz-Merino, Antonio Barco-Sánchez, Fernando Henao Carrasco, Esteban Nogales Fernández, Ana Vallejo Benítez, Javier Brugal Molina, Antonio Martínez Peinado, Ana Grueso López, Manuel Ruiz Borrego, Manuel Codes Manuel de Villena, Víctor Sánchez-Margalet, Adoración Nieto-García, Emilio Alba Conejo, Noelia Casares Lagar, José Ibáñez Martínez

“…Infiltration by tumor infiltrating lymphocytes (TIL) and their subtypes, tumor-associated macrophages (TAM) and myeloid-derived suppressive cells (MDSC) seem bona fide prognostic and even predictive biomarkers, that will eventually be incorporated into diagnostic and therapeutic algorithms of breast cancer. …”
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Predicting phage-host interaction via hyperbolic Poincaré graph embedding and large-scale protein language technique by Jie Pan, Rui Wang, Wenjing Liu, Li Wang, Zhuhong You, Yuechao Li, Zhemeng Duan, Qinghua Huang, Jie Feng, Yanmei Sun, Shiwei Wang

“…Existing computational tools often fail to accurately identify phages across different bacterial species. In this study, we present GE-PHI, a machine-learning-based model for predicting phage-host interactions (PHIs) by integrating knowledge graph embedding algorithm with a large-scale protein language model. …”
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Integrated Analysis of Ferroptosis- and Cellular Senescence-Related Biomarkers in Atherosclerosis Based on Machine Learning and Single-Cell Sequencing Data by Qi X, Cao S, Chen J, Yin X

“…Eight machine learning algorithms were applied to identify hub genes and construct a diagnostic model. …”
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Artificial Intelligence-Based Prediction of Bloodstream Infections Using Standard Hematological and Biochemical Markers by Ferhat DEMİRCİ, Murat AKŞİT, Aylin DEMİRCİ

“…Basophil count, while ranked highest by SHAP, showed low sensitivity, highlighting the difference between algorithmic weight and bedside utility. …”
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Breast thermography: a systematic review and meta-analysis by Ane Goñi-Arana, Jorge Pérez-Martín, Francisco Javier Díez

“…However, advances in infrared technology and image processing algorithms in the twenty-first century led to a renewed interest in thermography. …”
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Metabolism and Microstructure of the Small Intestine Wall in Patients With Colorectal Cancer by M. V. Bagryantsev, M. G. Ryabkov, E. L. Bederina, M. M. Loginova, A. V. Bazayev, A. I. Abelevich, I. L. Dezortsev, S. S. Bunova, M. V. Shirmanova, V. I. Shcheslavskiy, E. B. Kiseleva

“…RELEVANCE In patients with colorectal cancer (CRC), the normal small intestine, located outside the pathological focus, undergoes changes that may be the cause of digestive dysfunction after radical surgery to remove the tumor.The assessment of metabolic and microstructural changes in the ileum mucosa in patients with colorectal cancer is necessary to correct the algorithms of postoperative therapy and enteral nutrition. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…After handling missing values, balancing the dataset, and analyzing the classifier’s performance, it is found that tree-based algorithms, particularly RF, perform better for all the datasets. …”
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Causes of embryo implantation failure: A systematic review and metaanalysis of procedures to increase embryo implantation potential by Francesco M. Bulletti, Romualdo Sciorio, Alessandro Conforti, Roberto De Luca, Carlo Bulletti, Antonio Palagiano, Marco Berrettini, Giulia Scaravelli, Roger A. Pierson

“…This review highlights the need to focus on PGT-A, diagnostic hysteroscopy, and endometrial receptivity for improving implantation rates.ConclusionImplantation success in ARTs largely depends on embryo euploidy. …”
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Serum and plasma as a good candidates of body fluids for detection lung cancer by FTIR liquid biopsy by Jolanta Smok-Kalwat, Stanisław Góźdź, Paweł Macek, Zuzanna Kalwat, Maryna Khalavka, Wioletta Rzad, Andrzej Stepulak, Joanna Depciuch

“…However, using these methods differences between serum and plasma were not existed. …”
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