Integrating SEResNet101 and SE-VGG19 for advanced cervical lesion detection: a step forward in precision oncology by Yan Ye, Yuanyuan Chen, Jiajia Pan, Peipei Li, Feifei Ni, Haizhen He

“…Abstract Background Cervical cancer remains a significant global health issue, with accurate differentiation between low-grade (LSIL) and high-grade squamous intraepithelial lesions (HSIL) crucial for effective screening and management. …”
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Experimental validation of cuproptosis-associated molecular signatures and their immunological implications in pulmonary tuberculosis by Xiaofang Liu, Xiaofang Liu, Qianqian Ma, Zhiming Li, Yong Xue, Jie Mi, Yuxi Li, Chunfeng Bai, Donglin Guo, Yinping Liu, Yan Liang, Jianqin Liang, Xueqiong Wu

“…Hub CRGs were screened out via least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms. Diagnostic models were subsequently constructed and validated. …”
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Using the Nutri-Score to visualise food reformulation in Germany: the case of breakfast cereals by Corinna Gréa, Anna Dittmann, David Wolff, Hanna Haidar, Silvia Roser, Benedikt Merz, Stefan Storcksdieck genannt Bonsmann

“…Methods Using data from the German monitoring of packaged foods, changes in energy and nutrient content and the final nutritional score (FNS) of breakfast cereals, differentiated into children’s and non-children’s products, between 2019 (n = 888) and 2022 (n = 1473) were evaluated (Mann-Whitney test for two independent samples). …”
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The Machine Learning Models in Major Cardiovascular Adverse Events Prediction Based on Coronary Computed Tomography Angiography: Systematic Review by Yuchen Ma, Mohan Li, Huiqun Wu

“…However, its role in predicting MACEs remains highly debated. ObjectiveWe evaluated the diagnostic value of ML models constructed using radiomic features extracted from CCTA in predicting MACEs, and compared the performance of different learning algorithms and models, thereby providing clinical recommendations for the diagnosis, treatment, and prognosis of MACEs. …”
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Establishing a preoperative predictive model for gallbladder adenoma and cholesterol polyps based on machine learning: a multicentre retrospective study by Yubing Wang, Chao Qu, Jiange Zeng, Yumin Jiang, Ruitao Sun, Changlei Li, Jian Li, Chengzhi Xing, Bin Tan, Kui Liu, Qing Liu, Dianpeng Zhao, Jingyu Cao, Weiyu Hu

“…Conclusion This study employed the machine learning combination algorithms and preoperative ultrasound imaging data to construct an SVM + RF predictive model, enabling effective preoperative differentiation of gallbladder adenomas and cholesterol polyps. …”
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A novel stemness-related lncRNA signature predicts prognosis, immune infiltration and drug sensitivity of clear cell renal cell carcinoma by Jia Liu, Lin Yao, Yong Yang, Jinchao Ma, Ruijian You, Ziyi Yu, Peng Du

“…Multiple machine learning algorithms were employed to construct a prognostic signature. …”
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Identification and validation of immune and diagnostic biomarkers for interstitial cystitis/painful bladder syndrome by integrating bioinformatics and machine-learning by Tao Zhou, Can Zhu, Wei Zhang, Qiongfang Wu, Mingqiang Deng, Zhiwei Jiang, Longfei Peng, Hao Geng, Zhouting Tuo, Zhouting Tuo, Ci Zou

“…Hub genes in IC/BPS patients were identified through the application of three distinct machine-learning algorithms. Additionally, the inflammatory status and immune landscape of IC/BPS patients were evaluated using the ssGSEA algorithm. …”
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EXTREME NORMOBLASTOSIS IN A THALASSAEMIA INTERMEDIA PATIENT POST-SPLENECTOMY: THE ROLE OF FLOW CYTOMETRY IN DIAGNOSIS AND MANAGEMENT by İdil Yürekli, Gülçin Dağlıoğlu, Naciye Nur Tozluklu, Birol Güvenç

“…This case reinforces the need for a tailored flow cytometric testing algorithm for complex cases.…”
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ZBTB10 as a potential prognosis biomarker and correlates with the tumor immune microenvironment in stomach adenocarcinoma by Yingdi Jiang, Fuhua Han, Lu Dai, Shali Qiu, Yanjie Zhou, Ke Wang, Jiang Lin

“…UALCAN and TCGA databases were used to evaluate the association of ZBTB10 expression with clinicopathological characteristics. …”
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The value of a radiomics model in predicting ovarian malignancy: a retrospective multi-center comparison with O-RADS and radiologists by Junjie Jin, Xijia Deng, Ling Long, Meiling Liu, Meimei Cao, Hao Gong, Huan Liu, Xiaosong Lan, Lili Liu, Jiuquan Zhang

“…Features were selected using minimum redundancy, maximum relevance, and the least absolute shrinkage and selection operator algorithm. Diagnostic performance of the radiomics model, O-RADS, and independent assessments by junior and senior radiologists was evaluated via the area under the receiver operating characteristic curve (AUC) and compared using DeLong’s test. …”
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Immune regulatory genes impact the hot/cold tumor microenvironment, affecting cancer treatment and patient outcomes by Mengmeng Sang, Jia Ge, Juan Ge, Juan Ge, Gu Tang, Qiwen Wang, Jiarun Wu, Liming Mao, Liming Mao, Xiaoling Ding, Xiaorong Zhou

“…Kyoto Encyclopedia of Genes and Genomes and Hallmark pathway enrichment were evaluated through gene set variation analysis. Additionally, hub genes that regulate the tumor microenvironment were identified, and their expression patterns were analyzed using single-cell RNA sequencing. …”
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Automatic segmentation model and machine learning model grounded in ultrasound radiomics for distinguishing between low malignant risk and intermediate-high malignant risk of adnex... by Lu Liu, Wenjun Cai, Feibo Zheng, Hongyan Tian, Yanping Li, Ting Wang, Xiaonan Chen, Wenjing Zhu

“…The nomogram using the LightGBM algorithm reached the best AUC (0.966, 95% CI: 0.927–1.000). …”
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In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes. by Alireza Naghizadeh, Wei-Chung Tsao, Jong Hyun Cho, Hongye Xu, Mohab Mohamed, Dali Li, Wei Xiong, Dimitri Metaxas, Carlos A Ramos, Dongfang Liu

“…The ML-based automated algorithm quantified CAR-T IS data correlates with the clinical responder and non-responder treated with Kappa-CAR-T cells directly from patients. …”
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Comparative estimation of the effectiveness of the Khorana, Vienna CATS, and TiC-Onco scores and the vWF/ADAMTS13 ratio in identifying a high risk of thrombotic complications in pa... by A. V. Vorobеv, A. G. Solopova, V. O. Bitsadze, M. M. Baeva, M. E. Sosnyagova, V. N. Galkin, D. O. Utkin, A. D. Makatsariya

“…Objective: To compare the diagnostic accuracy of the Khorana, Vienna CATS, and TiC-Onco scores in assessing the risk of venous thromboembolism (VTE) in patients with malignant neoplasms of the female reproductive system and mammary gland and to evaluate the prognostic role of the vWF/ADAMTS13 ratio in identifying groups with a high risk of thrombosis.Material and methods. …”
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Screening biomarkers related to cholesterol metabolism in osteoarthritis based on transcriptomics by ChenDeng Lao, Wei Wei, JianWen Cheng, ShiJie Liao, XiaoLin Luo, Qian Huang, HengZhen Huang, JinMin Zhao

“…Three machine learning algorithms identified ATF3, CHKA, CLU, CTNNB1, and FASN as potential biomarkers. …”
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Machine learning-based identification of exosome-related biomarkers and drugs prediction in nasopharyngeal carcinoma by Zhengyu Wei, Guoli Wang, Yanghao Hu, Chongchang Zhou, Yuna Zhang, Yi Shen, Yaowen Wang

“…Results Through the application of three machine learning algorithms, five key genes (LTF, IDH1, ITGAV, CCL2, and LGALS3BP) were identified for the construction of a diagnostic model. …”
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Pain sensitisation and joint inflammation in patients with active rheumatoid arthritis by Sam Norton, Bruce W Kirkham, James Galloway, Khaldoun Chaabo, Toby Garrood, Zoe Rutter-Locher, Estee Chan, Alex Vincent

“…However clinical examination and PROMs did not reliably differentiate groups, emphasising PDUS remains an important tool.…”
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Unraveling volatile metabolites in pigmented onion (Allium cepa L.) bulbs through HS-SPME/GC–MS-based metabolomics and machine learning by Kaiqi Cheng, Kaiqi Cheng, Jingzhe Xiao, Jingyuan He, Rongguang Yang, Jinjin Pei, Jinjin Pei, Wengang Jin, Wengang Jin, A. M. Abd El-Aty, A. M. Abd El-Aty

“…The 38 features selected by LASSO enabled clear differentiation of onion types via PCA, UMAP, and k-means clustering. …”
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A High Resolution Melting Analysis (HRM) PCR assay for the detection and identification of Old World Leishmania species. by Yusr Saadi-Ben Aoun, Hejer Souguir, Hamed Chouaieb, Mongia Kraiem, Insaf Bel Hadj Ali, Ahmed S Chakroun, Florian Noguier, Akila Fathallah-Mili, David Piquemal, Ikram Guizani

“…Its integration into molecular diagnostic algorithms for CL or in eco-epidemiological studies holds promise for improving disease management and control.…”
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Intelligent diagnosis of thyroid nodules with AI ultrasound assistance and cytology classification by Xiaojuan Cai, Ya Zhou, Jie Ren, Jinrong Wei, Shiyu Lu, Hanbing Gu, Weizhe Xu, Xun Zhu

“…ObjectiveAccurate evaluation of thyroid nodules is crucial for effective management; however, methods such as ultrasonography and Fine Needle Aspiration Cytology (FNAC) can be subjective and operator-dependent. …”
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