The application of blockchain with a comparative approach and its impact on risk, flexibility and internal control evaluation by mohammadsadegh aminipoor, HamidReza GholamniaRoshan, azadeh kiapour, Iman Dadashi

“…In general, the use of blockchain can affect the following: Risk: Blockchain minimizes the possibility of changing and falsifying information by using strong encryption and security algorithms. …”
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Machine learning applications to classify and monitor medication adherence in patients with type 2 diabetes in Ethiopia by Ewunate Assaye Kassaw, Ewunate Assaye Kassaw, Ashenafi Kibret Sendekie, Ashenafi Kibret Sendekie, Bekele Mulat Enyew, Biruk Beletew Abate, Biruk Beletew Abate

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Artificial intelligence-based radiogenomics reveals the potential immunoregulatory role of COL22A1 in glioma and its induced autoimmune encephalitis by Bingchao Yan, Bingchao Yan, Qian Chen, Dacheng Wang, Leili Ding, Leili Ding, Jingfeng Qu, Renfei Du, Renfei Du, Wenjie Shi, Ulf D. Kahlert, Zhengquan Yu

“…BackgroundThe tumor microenvironment plays a crucial role in the progression of both glioma and glioma-induced autoimmune encephalitis. …”
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The dark side of generative artificial intelligence: A critical analysis of controversies and risks of ChatGPT by Krzysztof Wach, Cong Doanh Duong, Joanna Ejdys, Rūta Kazlauskaitė, Pawel Korzynski, Grzegorz Mazurek, Joanna Paliszkiewicz, Ewa Ziemba

“…Advocating for the regulation of the AI market is crucial to ensure a level playing field, promote fair competition, protect intellectual property rights and privacy, and prevent potential geopolitical risks. …”
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Antibiogram use on dairy cattle for bovine respiratory disease: Factors associated with bacterial pathogen identification and prediction of bacterial recovery using machine learnin... by Hugo F. Monteiro, Alejandro Hoyos-Jaramillo, Adriana Garzon, Heather M. Fritz, Craig C. Miramontes, Isabelle M. Matos, Terry W. Lehenbauer, Sharif Aly, Fabio S. Lima, Richard V. Pereira

“…For factors associated with the culture-positive of M. haemolytica in BRD clinical cases, an interaction was also observed between age and season, but the farm further played a role in the odds of being culture-positive, with one farm having considerably greater odds than the remaining ones. …”
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Improved estimation of two-phase capillary pressure with nuclear magnetic resonance measurements via machine learning by Oriyomi Raheem, Misael M. Morales, Wen Pan, Carlos Torres-Verdín

“…In contrast, nuclear magnetic resonance (NMR) measurements, which provide information on pore body size distribution, are faster and can be leveraged to estimate capillary pressure using machine learning algorithms. …”
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A Deep Learning-Based Echo Extrapolation Method by Fusing Radar Mosaic and RMAPS-NOW Data by Shanhao Wang, Zhiqun Hu, Fuzeng Wang, Ruiting Liu, Lirong Wang, Jiexin Chen

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Retrospective analysis of COVID-19 clinical and laboratory data: Constructing a multivariable model across different comorbidities by Mahdieh Shokrollahi Barough, Mohammad Darzi, Masoud Yunesian, Danesh Amini Panah, Yekta Ghane, Sam Mottahedan, Sohrab Sakinehpour, Tahereh Kowsarirad, Zahra Hosseini-Farjam, Mohammad Reza Amirzargar, Samaneh Dehghani, Fahimeh Shahriyary, Mohammad Mahdi Kabiri, Marzieh Nojomi, Neda Saraygord-Afshari, Seyedeh Ghazal Mostofi, Zeynab Yassin, Nazanin Mojtabavi

“…Machine learning algorithms were employed to identify relevant features and calculate predictive probability scores. …”
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Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Identification of geochemical anomalies plays an essential role in mineral exploration. Recent research investigations have shown that Machine Learning (ML) algorithms can identify geochemical anomalies associated with mineralization that represent targets for mineral exploration. …”
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Enhancing Corn Image Resolution Captured by Unmanned Aerial Vehicles With the Aid of Deep Learning by Emilia Alves Nogueira, Bruno Moraes Rocha, Gabriel da Silva Vieira, Afonso Ueslei da Fonseca, Juliana Paula Felix, Antonio Oliveira-Jr, Fabrizzio Soares

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Predicting adherence to gamified cognitive training using early phase game performance data: Towards a just-in-time adherence promotion strategy. by Yuanying Pang, Ankita Singh, Shayok Chakraborty, Neil Charness, Walter R Boot, Zhe He

“…Conversely, a positive correlation between the number of sessions played and adherence highlighted the importance of early active involvement.…”
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Forecasting readmission in COVID-19 patients utilizing blood biomarkers and machine learning in the Hospital-at-Home program by Maria Glòria Bonet-Papell, Maria Glòria Bonet-Papell, Georgina Company-Se, María Delgado-Capel, Beatriz Díez-Sánchez, Lourdes Mateu-Pruñosa, Roger Paredes-Deirós, Jordi Ara del Rey, Lexa Nescolarde

“…Classification algorithms can aid clinicians in making informed decisions regarding patient transfers from conventional hospitalization to HaH.…”
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GCBRGCN: Integration of ceRNA and RGCN to Identify Gastric Cancer Biomarkers by Peng Zhi, Yue Liu, Chenghui Zhao, Kunlun He

“…Gastric cancer (GC) is a prevalent malignancy, and the discovery of biomarkers plays a crucial role in the diagnosis and prognosis of GC. …”
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Innovative data techniques for centrifugal pump optimization with machine learning and AI model. by Gaurav Sandeep Dave, Amar Pradeep Pandhare, Atul Prabhakar Kulkarni, Dhananjay Vasant Khankal

“…The quality of recorded data plays a crucial role and directly influences the data transformation phase in machine learning (ML) and deep learning (DL) models. …”
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Machine learning-driven discovery of anoikis-related biomarkers in Adult T-Cell Leukemia/Lymphoma subtypes by Mohadeseh Zarei Ghobadi, Elaheh Afsaneh

“…We then applied Least Absolute Shrinkage and Selection Operator (LASSO) regression to select the most informative features. Subsequently, we employed decision trees, random forest, extreme gradient boosting, support vector machine, and logistic regression algorithms to identify classifier genes distinguishing each ATLL subtype from asymptomatic carriers. …”
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Predictive biomarkers and molecular subtypes in DLBCL: insights from PCD gene expression and machine learning by Tiantian He, Jie Geng, Chuandong Hou, Hongyi Li, Hong Zhang, Peng Zhao, Peifeng He, Xuechun Lu

“…Programmed cell death (PCD) plays a critical role in the development and progression of various cancers. …”
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Linking online activity to offline behavior: A meta-review of three decades of online-to-offline scholarship with future implications for AI by Scott Leo Renshaw, Kathleen M. Carley

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Developing a cost-effective tool for choke flow rate prediction in sub-critical oil wells using wellhead data by Zhiwei Xun, Farag M. A. Altalbawy, Prakash Kanjariya, R. Manjunatha, Debasish Shit, M. Nirmala, Ajay Sharma, Sarbeswara Hota, Shirin Shomurotova, Fadhil Faez Sead, Hojjat Abbasi, Mohammad Mahtab Alam

“…This endeavor is rigorously informed by comprehensive data acquired from an operational petroleum production facility in the Middle East. …”
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Exploration of common pathogenesis and candidate hub genes between HIV and monkeypox co-infection using bioinformatics and machine learning by Jialu Li, Yiwei Hao, Liang Wu, Hongyuan Liang, Liang Ni, Fang Wang, Sa Wang, Yujiao Duan, Qiuhua Xu, Jinjing Xiao, Di Yang, Guiju Gao, Yi Ding, Chengyu Gao, Jiang Xiao, Hongxin Zhao

“…TFs and miRNAs associated with these hub genes, playing a key role in regulating viral infection and inflammation due to the activation of antiviral innate immunity, were also identified through network analysis. …”
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GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…Implementing traditional OPF algorithms can be challenging for large-scale networks with complex topologies and constraints. …”
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