Non-Invasive Detection of Breast Cancer by Low-Coverage Whole-Genome Sequencing from Plasma by Li Peng, Ru Yao, Sihang Gao, Yang Qu, Li Qu, Jingbo Zhang, Yidong Zhou

“…Our approach adopted principal component analysis and a generalized linear model algorithm to distinguish between breast cancer and normal samples. …”
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Multimodal data integration with machine learning for predicting PARP inhibitor efficacy and prognosis in ovarian cancer by Xi’an Xiong, Li Cai, Li Cai, Zhen Yang, Zhongping Cao, Nayiyuan Wu, Nayiyuan Wu, Qianxi Ni

“…Patient-specific efficacy and prognosis prediction models were then constructed using various machine learning algorithms.ResultsTotal bile acids (TBAs) and CA-199 present as an independent risk factor in Cox multivariate analysis for primary and recurrent ovarian cancer patients respectively (P < 0.05). …”
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Adaptive Estimation Algorithm for Photoplethysmographic Heart Rate Based on Finite State Machine by Ting Lan, Yanan Bie, Dong Hai, Jun Zhong

“…The results of the experiment show that compared with other dominant algorithms, the proposed algorithm estimates heart rate with a smaller mean absolute error and can extract heart rate more effectively.…”
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Clinical efficacy of DSA-based features in predicting outcomes of acupuncture intervention on upper limb dysfunction following ischemic stroke by Yuqi Tang, Sixian Hu, Yipeng Xu, Linjia Wang, Yu Fang, Pei Yu, Yaning Liu, Jiangwei Shi, Junwen Guan, Ling Zhao

“…We applied three deep-learning algorithms (YOLOX, FasterRCNN, and TOOD) to develop the object detection model. …”
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Development of a PANoptosis-related LncRNAs for prognosis predicting and immune infiltration characterization of gastric Cancer by Yangjian Hong, Cong Luo, Yanyang Liu, Zeng Wang, Huize Shen, Wenyuan Niu, Jiaming Ge, Jie Xuan, Gaofeng Hu, Bowen Li, Qinglin Li, Huangjie Zhang

“…PANoptosis-related genes were obtained from molecular characteristic databases, and PANlncRNAs were screened through Pearson correlation analysis. Based on this, PANlncRNAs were subjected to univariate Cox regression analysis using the least absolute shrinkage and selection operator (LASSO) algorithm to obtain lncRNA associated with survival outcomes, which were subsequently used to calculate survival scores and to construct signatures. …”
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Regional Brain Aging Disparity Index: Region-Specific Brain Aging State Index for Neurodegenerative Diseases and Chronic Disease Specificity by Yutong Wu, Shen Sun, Chen Zhang, Xiangge Ma, Xinyu Zhu, Yanxue Li, Lan Lin, Zhenrong Fu

“…This study proposes a novel brain-region-level aging assessment paradigm based on Shapley value interpretation, aiming to overcome the interpretability limitations of traditional brain age prediction models. Although deep-learning-based brain age prediction models using neuroimaging data have become crucial tools for evaluating abnormal brain aging, their unidimensional brain age–chronological age discrepancy metric fails to characterize the regional heterogeneity of brain aging. …”
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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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An improved algorithm of segmented orthogonal matching pursuit based on wireless sensor networks by Xinmiao Lu, Yanwen Su, Qiong Wu, Yuhan Wei, Jiaxu Wang

“…Aiming at the problems of low data reconstruction accuracy in wireless sensor networks and users unable to receive accurate original signals, improvements are made on the basis of the stagewise orthogonal matching pursuit algorithm, combined with sparseness adaptation and the pre-selection strategy, which proposes a sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm. …”
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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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