AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis by Esther Ugo Alum

“…Existing gaps include data quality, algorithmic transparency, and ethical concerns around privacy, among others. …”
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Play, watch, share: the dissemination of the cultural presence of games on video-based social media by Qiaohe Zhang, Yixuan Shao, Xu Li

“…Finally, text proctyessing is performed via manual coding, screening, classification and summarization. We obtain the IR dissemination model of digital cultural presence. 1. …”
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Callback time preference for prescreening visits among Black residents in the Boston area: findings from two randomized controlled trials by Ruth Zeto, Oluwagbemisola Ibikunle, Jingyi Cao, Hannah Col, Dhrumil Patil, Ruth-Alma Turkson-Ocran, Mingyu Zhang, Timothy B. Plante, Stephen P. Juraschek

“…Staff call attempts and participant screening status were logged prospectively. Gender was estimated based on first name, using a published algorithm. …”
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Analysis of Facial Areas to Identify CHD Risks Based on Facial Textures by Budi Sunarko, Agung Adi Firdaus, Yudha Andriano Rismawan, Anan Nugroho

“…Early screening for coronary heart disease (CHD) remains insufficiently addressed, underscoring the need for a more effective screening tool. …”
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A hybrid super learner ensemble for phishing detection on mobile devices by Routhu Srinivasa Rao, Cheemaladinne Kondaiah, Alwyn Roshan Pais, Bumshik Lee

“…Abstract In today’s digital age, the rapid increase in online users and massive network traffic has made ensuring security more challenging. Among the various cyber threats, phishing remains one of the most significant. …”
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EDITORIAL: ARTIFICIAL INTELLIGENCE AND ITS TRANSFORMATIVE IMPACT ON SCIENTIFIC PUBLISHING by Abubakar Munir

“…Conventional software such as Turnitin and iThenticate have come a long way, using deep learning algorithms to identify more evolved instances of academic fraud, including paraphrasing plagiarism and AI-generated content. …”
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Cheetah optimized CNN: A bio-inspired neural network for automated diabetic retinopathy detection by V. K. U. Ahamed Gani, N. Shanmugasundaram

“…The proposed CO-CNN approach shows superior performance compared to that of state-of-the-art methods, offering potential applications in telemedicine, treatment planning, early detection, screening, and patient education. Integrating fuzzy logic enhances the model’s interpretability and robustness, paving the way for improved healthcare outcomes in diabetic retinopathy management.…”
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Chinese AI tool ERNIE Bot Textual Exploration of False Information by Fu Yue

“…In order to improve the accuracy of detection, this paper proposes countermeasures to improve the AI detection algorithm, enhance data training and model optimisation, and human-machine collaboration. …”
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Maternal factors associated with early-onset neonatal sepsis among caesarean-delivered babies at Mbarara Regional Referral Hospital, Uganda: a case-control study by James M. Maisaba, Richard Migisha, Asiphas Owaraganise, Leevan Tibaijuka, David Collins Agaba, Joy Muhumuza, Joseph Ngonzi, Stella Kyoyagala, Musa Kayondo

“…We enrolled mother-baby pairs for both groups, obtaining maternal data via structured questionnaires The diagnosis of EONS was made using the WHO Young Infant Integrated Management of Childhood Illnesses algorithm. …”
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Fecal occult blood affects intestinal microbial community structure in colorectal cancer by Wu Guodong, Wu Yinhang, Wu Xinyue, Shen Hong, Chu Jian, Qu Zhanbo, Han Shuwen

“…Characteristic gut bacteria were screened, and various machine learning algorithms were applied to construct CRC risk prediction models. …”
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Explainable machine learning for predicting lung metastasis of colorectal cancer by Zhentian Guo, Zongming Zhang, Limin Liu, Yue Zhao, Zhuo Liu, Chong Zhang, Hui Qi, Jinqiu Feng, Peijie Yao

“…We selected the best algorithm and visualized it using SHAP. We conducted a validation of the model utilizing data from a Chinese hospital to assess its practicality. …”
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Android malware detection based on APK signature information feedback by Xin-yu LIU, Jian WENG, Yue ZHANG, Bing-wen FENG, Jia-si WENG

“…A new malware detection method based on APK signature of information feedback (SigFeedback) was proposed.Based on SVM classification algorithm,the method of eigenvalue extraction adoped heuristic rule learning to sig APK information verify screening,and it also implemented the heuristic feedback,from which achieved the purpose of more accurate detection of malicious software.SigFeedback detection algorithm enjoyed the advantage of the high detection rate and low false positive rate.Finally the experiment show that the SigFeedback algorithm has high efficiency,making the rate of false positive from 13% down to 3%.…”
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Android malware detection based on APK signature information feedback by Xin-yu LIU, Jian WENG, Yue ZHANG, Bing-wen FENG, Jia-si WENG

“…A new malware detection method based on APK signature of information feedback (SigFeedback) was proposed.Based on SVM classification algorithm,the method of eigenvalue extraction adoped heuristic rule learning to sig APK information verify screening,and it also implemented the heuristic feedback,from which achieved the purpose of more accurate detection of malicious software.SigFeedback detection algorithm enjoyed the advantage of the high detection rate and low false positive rate.Finally the experiment show that the SigFeedback algorithm has high efficiency,making the rate of false positive from 13% down to 3%.…”
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Machine learning in dentistry and oral surgery: charting the course with bibliometric insights by Shuangwei Liu, Yuquan Hao, Shijie Zhu, Liyao Wan, Zhe Yi, Zhichang Zhang

“…Moreover, challenges, such as data availability and security, algorithmic biases, and “black-box models”, must be addressed. …”
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High prevalence of resistance to macrolides and fluoroquinolones in Mycoplasma genitalium isolated from patients in two Russian megalopolises – Moscow and St. Petersburg in 2021– 2... by Edelstein I.A., Gushchin A.E., Gladin D.P., Romanov A.V., Negasheva E.S., Frigo N.V., Kozlov R.S., Potekaev N.N., Kozlova N.S., Borukhovich D.G.

“…The most common combination of mutations was A2059G (23S rRNA) + S80I (parC), which made up to 33% (18/54) in St. Petersburg and 25.7% (25/97) in Moscow. …”
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Multi-Class Classification Using Improved Mahalanobis-Taguchi System Based on Binary Tree and Its Application by Niu Junlei

“…Aiming at the inadequacy of Mahalanobis-Taguchi System(MTS), an improved MTS optimization model(MTSO) is proposed. The core idea is that a number of optimization objectives are proposed based on the purpose and characteristics of the data classification problem and optimization model is used for screening important variables instead of orthogonal arrays and signal-noise-ratio. …”
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A statistical method for high-throughput emergence rate calculation for soybean breeding plots based on field phenotypic characteristics by Yan Sun, Mengqi Li, Meiling Liu, Jingyi Zhang, Yingli Cao, Xue Ao

“…Then, a soybean seedling counting algorithm was constructed: by establishing a soybean seedling growth model, the idea of “growth normalization” was proposed, and the expansion-compression factor was defined to eliminate the influence of soybean seedling growth inconsistency on counting. …”
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Hydraulic Pump Fault Diagnosis Method Based on EWT Decomposition Denoising and Deep Learning on Cloud Platform by Wanlu Jiang, Zhenbao Li, Sheng Zhang, Teng Wang, Shuqing Zhang

“…Compared with ensemble empirical mode decomposition (EEMD) and complementary ensemble empirical mode decomposition (CEEMD), the results show that the axial piston pump fault diagnosis algorithm based on EWT and 1D-CNN has higher fault identification accuracy.…”
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Research on Feature Extraction of Performance Degradation for Flexible Material R2R Processing Roller Based on PCA by Yaohua Deng, Huiqiao Zhou, Kexing Yao, Zhiqi Huang, Chengwang Guo

“…The Jacobi iteration method was introduced to derive the algorithm for solving eigenvalue and eigenvector of the covariance matrix. …”
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AI-Powered Synthesis of Structured Multimodal Breast Ultrasound Reports Integrating Radiologist Annotations and Deep Learning Analysis by Khadija Azhar, Byoung-Dai Lee, Shi Sub Byon, Kyu Ran Cho, Sung Eun Song

“…Additionally, the deep-learning-based algorithm, utilizing DenseNet-121 as its core model, achieved an overall accuracy of 0.865, precision of 0.868, recall of 0.847, F1-score of 0.856, and area under the receiver operating characteristics of 0.92 in classifying tissue stiffness in breast US shear-wave elastography (SWE-mode) images. …”
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