HMCFormer (hierarchical multi-scale convolutional transformer): a hybrid CNN+Transformer network for intelligent VIA screening by Bo Feng, Chao Xu, Zhengping Li, Chuanyi Zhang

“…This will attract more low-income women to volunteer for regular cervical cancer screening. …”
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Predicting immune status and gene mutations in stomach adenocarcinoma patients based on inflammatory response-related prognostic features by Huanjun Li, Jingtang Chen, Zhiliang Chen, Jingsheng Liao

“…Genes associated with STAD prognosis were obtained from the intersection of inflammation-related genes and DEGs. The key genes screened by last absolute shrinkage and selection operator (LASSO) Cox and stepwise regression analyses were used to construct prognostic models and nomograms. …”
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Assessment of prognosis and responsiveness to immunotherapy in colorectal cancer patients based on the level of immune cell infiltration by Kaili Liao, Minqi Zhu, Lei Guo, Zijun Gao, Jinting Cheng, Bing Sun, Yihui Qian, Bingying Lin, Jingyan Zhang, Tingyi Qian, Yixin Jiang, Yanmei Xu, Qionghui Zhong, Xiaozhong Wang

“…Prognosis-related genes were screened and models were constructed using LASSO-Cox analysis. …”
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Screening and Validation of Potential Biomarkers of Immune Cells in Childhood Asthma Patients via Mendelian Randomization and Machine Learning by Zhang Y, Hai Y, Song B, Xu J, Cao L, Yasen R, Xu W, Zhang J, Hu J

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Artificial intelligence in the service of entrepreneurial finance: knowledge structure and the foundational algorithmic paradigm by Robert Kudelić, Tamara Šmaguc, Sherry Robinson

“…A rigorous search and screening of the web of science core collection identified 1,890 journal articles for analysis. …”
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Association of sarcopenia with all-cause and cause-specific mortality in cancer patients: development and validation of a 3-year and 5-year survival prediction model by Feng Cui, Xiangji Dang, Daiyun Peng, Yuanhua She, Yubin Wang, Ruifeng Yang, Zhiyao Han, Yan Liu, Hanteng Yang

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Diagnostic accuracy of artificial intelligence for the screening of prostate cancer in biparametric magnetic resonance imaging: a systematic review by Oksana V. Kryuchkova, Elena V. Schepkina, Natalia A. Rubtsova, Boris Y. Alekseev, Anton I. Kuznetsov, Svetlana V. Epifanova, Elena V. Zarya, Ali E. Talyshinskii

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Interpretable machine learning model for identification and risk factor of premature rupture of membranes (PROM) and its association with nutritional inflammatory index: a retrospe... by Meng Zheng, Xiaowei Zhang, Haihong Wang, Ping Yuan, Qiulan Yu

“…Based on the variables screened out by ridge regression and Boruta algorithm, univariate and multivariate logistic regression analyses were further adopted. …”
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Light scattering-based screening method for rapid evaluating antibiotic effects on bacteria using laser speckle imaging by Donghyeok Kim, Seongjoon Moon, Jongseo Lee, Kyoungman Cho, Changhan Lee, Jonghee Yoon

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Validation of an Eye-Tracking Algorithm Based on Smartphone Videos: A Pilot Study by Wanzi Su, Damon Hoad, Leandro Pecchia, Davide Piaggio

“…<b>Methods:</b> The investigation primarily focused on comparing two algorithms, which were named CHT_TM and CHT_ACM, abbreviated from the core functions: Circular Hough Transform (CHT), Active Contour Models (ACMs), and Template Matching (TM). …”
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Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks by Udayaraju Pamula, Venkateswararao Pulipati, G. Vijaya Suresh, M. V. Jagannatha Reddy, Anil Kumar Bondala, Srihari Varma Mantena, Ramesh Vatambeti

“…Abstract Diabetic Retinopathy (DR) is a leading cause of vision impairment globally, necessitating regular screenings to prevent its progression to severe stages. …”
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Radiomics model building from multiparametric MRI to predict Ki-67 expression in patients with primary central nervous system lymphomas: a multicenter study by Yelong Shen, Siyu Wu, Yanan Wu, Chao Cui, Haiou Li, Shuang Yang, Xuejun Liu, Xingzhi Chen, Chencui Huang, Ximing Wang

“…The radiomics features were extracted respectively, and the features were screened by machine learning algorithm and statistical method. …”
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Applications of digital health technologies and artificial intelligence algorithms in COPD: systematic review by Zhenli Chen, Jie Hao, Haixia Sun, Min Li, Yuan Zhang, Qing Qian

“…Future research should focus on enhancing global collaboration to explore the cost-effectiveness and data-sharing capabilities of DHTs, enhancing the interpretability of AI models, and validating these algorithms through clinical trials to facilitate their safe integration into the routine COPD management.…”
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Construction of a circadian rhythm-related gene signature for predicting the prognosis and immune infiltration of breast cancer by Lin Ni, Lin Ni, He Li, Yanqi Cui, Wanqiu Xiong, Shuming Chen, Hancong Huang, Zhiwei Wang, Hu Zhao, Hu Zhao, Hu Zhao, Bing Wang, Bing Wang, Bing Wang

“…Three different machine learning algorithms were used to screen out the characteristic circadian genes associated with BC prognosis. …”
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Host Circulating Immunometabolism-Associated Biomarkers for Early Diagnosis of Active Tuberculosis: Multi-Omics Screening with Experimental Validation by Yang Z, Dong Y, Shang Y, Li H, Ren W, Li S, Pang Y

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Screening colorectal cancer associated autoantigens through multi-omics analysis and diagnostic performance evaluation of corresponding autoantibodies by Zan Qiu, Yifan Cheng, Haiyan Liu, Tiandong Li, Yinan Jiang, Yin Lu, Donglin Jiang, Xiaoyue Zhang, Xinwei Wang, Zirui Kang, Lei Peng, Keyan Wang, Liping Dai, Hua Ye, Peng Wang, Jianxiang Shi

“…Ten machine learning algorithms were utilized to develop diagnostic models, with the optimal one selected and integrated into an R Shiny-based GUI to enhance usability and accessibility. …”
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Artificial intelligence-enabled non-invasive ubiquitous anemia screening: The HEMO-AI pilot study on pediatric population by Daniel Gordon, Jason Hoffman, Keren Gamrasni, Yotam Barlev, Alex Levine, Tamar Landau, Ronen Shpiegel, Avishai Lahad, Ariel Koren, Carina Levin, Osnat Naor, Hannah Lee, Xin Liu, Shwetak Patel, Gilad Chayen, Michael Brandwein

“…Results 823 samples, 531 from a 12.2 megapixel camera and 256 from a 12.2 megapixel camera, were collected. 26 samples were excluded by the study coordinator for irregularities. 97% of fingernails and 68% of skin samples were successfully identified by a post-trained machine learning model. Separate models built to detect anemia using images taken from the Pixel 3 had an average precision of 0.64 and an average recall of 0.4, whereas models built using the Pixel 6 had an average precision of 0.8 and an average recall of 0.84. …”
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Cervical cancer screening uptake and its associated factor in Sub-Sharan Africa: a machine learning approach by Fetlework Gubena Arage, Zinabu Bekele Tadese, Eliyas Addisu Taye, Tigist Kifle Tsegaw, Tsegasilassie Gebremariam Abate, Eyob Akalewold Alemu

“…These algorithms were employed to predict cervical cancer screening uptake. …”
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An improved algorithm of segmented orthogonal matching pursuit based on wireless sensor networks by Xinmiao Lu, Yanwen Su, Qiong Wu, Yuhan Wei, Jiaxu Wang

“…It can be seen that the sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm has better adaptive characteristics to the sparsity of the signal, which is beneficial for users to receive more accurate original signals.…”
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Development and validation of a machine learning-based prediction model for hepatorenal syndrome in liver cirrhosis patients using MIMIC-IV and eICU databases by Fengwei Yao, Ji Luo, Qian Zhou, Luhua Wang, Zhijun He

“…By integrating the MIMIC-IV database and machine learning algorithms, we developed an effective predictive model for HRS in liver cirrhosis patients, providing a robust tool for early clinical intervention.…”
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