A Novel Approach to Detect Malware Based on API Call Sequence Analysis by Youngjoon Ki, Eunjin Kim, Huy Kang Kim

“…We adopt DNA sequence alignment algorithms and extract common API call sequence patterns of malicious function from malware in different categories. …”
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The role of artificial intelligence in promoting health and developing preventive strategies for diabetes by Ameneh Marzban

“…Dear Editor Diabetes remains a significant public health challenge, and the integration of artificial intelligence (AI) presents remarkable opportunities to enhance early diagnosis, personalized treatment, and effective prevention strategies.1 AI algorithms, including supervised learning and convolutional neural networks, can efficiently analyze large datasets to identify patterns and risk factors associated with diabetes, surpassing the capabilities of traditional methods.2 This advanced analysis enables healthcare providers to predict the likelihood of diabetes in individuals and populations, facilitating timely interventions and customized prevention strategies. …”
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Enhancing Transpiration Estimates: A Novel Approach Using SIF Partitioning and the TL-LUE Model by Tewekel Melese Gemechu, Baozhang Chen, Huifang Zhang, Junjun Fang, Adil Dilawar

“…Existing methodologies, including traditional techniques like the Penman–Monteith model, remote sensing approaches utilizing Solar-Induced Fluorescence (SIF), and machine learning algorithms, have demonstrated varying levels of effectiveness in ET estimation. …”
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Video Pulses: User-Based Modeling of Interesting Video Segments by Markos Avlonitis, Konstantinos Chorianopoulos

“…Previous research in video retrieval has focused on content-based techniques, such as pattern recognition algorithms that attempt to understand the low-level features of a video. …”
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The Prognostic Significance of Sleep and Circadian Rhythm for Myocardial Infarction Outcomes: Case-Control Study by Wei-Chih Chin, Pao-Hsien Chu, Lung-Sheng Wu, Kuang-Tso Lee, Chen Lin, Chien-Te Ho, Wei-Sheng Yang, I-Hang Chung, Yu-Shu Huang

“…ObjectiveWe aimed to evaluate how sleep patterns and disrupted circadian rhythm affect the prognosis of MI, using actigraphy and heart rate variability (HRV). …”
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Quality of a fished resource: Assessing spatial and temporal dynamics. by Sarah J Teck, Julio Lorda, Nick T Shears, Tal Ben-Horin, Rebecca E Toseland, Sarah T Rathbone, Dave Rudie, Steven D Gaines

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Evaluating the performance of herd-specific long short-term memory models to identify automated health alerts associated with a ketosis diagnosis in early-lactation cows by N. Taechachokevivat, B. Kou, T. Zhang, M.E. Montes, J.P. Boerman, J.S. Doucette, R.C. Neves

“…Long short-term memory (LSTM) models are machine learning models capable of learning temporal patterns and making predictions based on time series data. …”
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A specific expression profile of LC3B and p62 is associated with nonresponse to neoadjuvant chemotherapy in esophageal adenocarcinomas. by Olivia Adams, Félice A Janser, Bastian Dislich, Sabina Berezowska, Magali Humbert, Christian A Seiler, Dino Kroell, Julia Slotta-Huspenina, Marcus Feith, Katja Ott, Mario P Tschan, Rupert Langer

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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…The scientific study of algorithms and statistical models are used by computer systems that use patterns and inference to perform tasks rather than using clear instructions. …”
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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

“…Enrichment analysis was performed to explore the potential functions of SRmRNAs. Multiple machine learning algorithms were employed to construct a prognostic signature. …”
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Emerging Diagnostic Approaches for Musculoskeletal Disorders: Advances in Imaging, Biomarkers, and Clinical Assessment by Rahul Kumar, Kiran Marla, Kyle Sporn, Phani Paladugu, Akshay Khanna, Chirag Gowda, Alex Ngo, Ethan Waisberg, Ram Jagadeesan, Alireza Tavakkoli

“…Artificial intelligence and machine learning algorithms now automate image interpretation, predict clinical outcomes, and enhance clinical decision support, complementing conventional clinical evaluations. …”
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Flow Characteristics by Blood Speckle Imaging in Non-Stenotic Congenital Aortic Root Disease Surrounding Valve-Preserving Operations by Shihao Liu, Justin T. Tretter, Lama Dakik, Hani K. Najm, Debkalpa Goswami, Jennifer K. Ryan, Elias Sundström

“…BSI, utilizing block-matching algorithms, enabled detailed visualization and quantification of flow parameters from the echocardiographic data. …”
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Will Artificial Intelligence Replace Physicians or Augment Their Capabilities? by Sara Rahmati Roodsari, Alireza Zali, Mohammad Rahmati-Roodsari, Behina Forouzanmehr

“…In medical imaging, deep learning algorithms, especially those trained with genetic algorithms, have demonstrated immense promise to improve the accuracy of pneumonia and COVID-19 diagnosis from chest X-rays. …”
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Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…The model proposed uses the state-of-art algorithms including the decision trees, support vector machines and the deep learning techniques in the feature extraction and pattern recognition as well as binary classification. …”
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Digital removal of dermal denticle layer using geometric AI from 3D CT scans of shark craniofacial structures enhances anatomical precision by Sang Wha Kim, Adams Hei Long Yuen, Hyun Woo Kim, Seyoung Lee, Sung Bin Lee, Young Min Lee, Won Joon Jung, Cherry Tsz Ching Poon, Dasol Park, Sangyun Kim, Sang Guen Kim, Jung Woo Kang, Jun Kwon, Su Jin Jo, Sib Sankar Giri, Hyunjung Park, Jong-pil Seo, Deok-Soo Kim, Byung Yeop Kim, Se Chang Park

“…This study presents an artificial intelligence (AI)-based solution using machine-learning algorithms for digitally removing dermal denticle layer from CT scans of shark craniofacial skeleton. …”
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End-to-end deep fusion of hyperspectral imaging and computer vision techniques for rapid detection of wheat seed quality by Tingting Zhang, Jing Li, Jinpeng Tong, Yihu Song, Li Wang, Renye Wu, Xuan Wei, Yuanyuan Song, Rensen Zeng

“…Internal seed quality was further assessed using scanning electron microscopy, dissection, and standard germination tests. Both conventional machine learning algorithms and deep convolutional neural networks (DCNN) were employed to develop discriminative models using independent datasets. …”
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Circadian rhythm abnormalities and autonomic dysfunction in patients with Chronic Fatigue Syndrome/Myalgic Encephalomyelitis. by Trinitat Cambras, Jesús Castro-Marrero, Maria Cleofé Zaragoza, Antoni Díez-Noguera, José Alegre

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Spatiotemporal evolution of interseismic coupling and stress accumulation near an asperity on a vertical strike-slip fault: Insights from three-dimensional viscoelastic numerical s... by LI Yebo, HUANG Luyuan, YAO Rui, TIAN Yiwei, YANG Shuxin

“…These models incorporate vertical strike-slip faults and use sophisticated contact algorithms to simulate the mechanical locking associated with asperities. …”
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Calculation Model of Multi-roll Straightening Process Based on Bilinear Hardening and Power Hardening by ZHU Xiaoyu, CHENG Zixing, WANG Xiaogang, HAN Peisheng

“…The bilinear model shows a linear increase in error, while the power model displays a nonlinear pattern. The magnitude of the hardening coefficient affects only the degree of curvature error, not the underlying behavior or material applicability. …”
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Identification of biomarkers for the diagnosis of type 2 diabetes mellitus with metabolic associated fatty liver disease by bioinformatics analysis and experimental validation by Guiling Wu, Guiling Wu, Sihui Wu, Sihui Wu, Tian Xiong, Tian Xiong, Tian Xiong, You Yao, You Yao, Yu Qiu, Yu Qiu, Yu Qiu, Liheng Meng, Cuihong Chen, Xi Yang, Xi Yang, Xi Yang, Xinghuan Liang, Yingfen Qin

“…Candidate biomarkers were screened using machine learning algorithms combined with 12 cytoHubba algorithms, and a diagnostic model for T2DM-related MAFLD was constructed and evaluated.The CIBERSORT method was used to investigate immune cell infiltration in MAFLD and the immunological significance of central genes. …”
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