Multimodal data integration in early-stage breast cancer by Arnau Llinas-Bertran, Maria Butjosa-Espín, Vittoria Barberi, Jose A. Seoane

“…We aimed to describe models that are not only academically and preclinically relevant, but also applicable to clinical settings.…”
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Modeling of human capital reproduction in the mining and metallurgical industry by Zhukov Aleksandr, Pronichkin Sergey, Ovsianikova Natalia, Kartsan Igor, Mihaylov Yuri

“…In the conditions of global transformation, the task of developing algorithms that automate the development of structural stability schemes and build a comprehensive system for leveling dysfunctions of socio-technical systems of human capital reproduction in the mining and metallurgical industry is relevant. …”
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Neoantigen prioritization based on antigen processing and presentation by Serina Tokita, Serina Tokita, Takayuki Kanaseki, Takayuki Kanaseki, Toshihiko Torigoe

“…In fact, since the number of clinically relevant neoantigens present in a patient is generally limited, this process is like finding a needle in a haystack. …”
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Empowering Community Health Workers With Scripted Medicine: Design Science Research Study by Dario Staehelin, Damaris Schmid, Felix Gerber, Mateusz Dolata, Gerhard Schwabe

“…ObjectiveThis study aims to develop Scripted Medicine to empower CHWs to accept broader responsibilities in NCD care. It aims to convey relevant medical and counseling knowledge through medical algorithms and ThinkLets (ie, social scripts). …”
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A review of independent component analysis application to microarray gene expression data by Wei Kong, Charles R. Vanderburg, Hiromi Gunshin, Jack T. Rogers, Xudong Huang

“…Herein we have reviewed the latest applications and the extended algorithms of ICA in gene clustering, classification, and identification. …”
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Prospects for predicting and preventing the heart failure deterioration: an analytical review by V. N. Larina, I. K. Skiba

“…An integrated approach using scales, algorithms and relevant therapy strategies can significantly improve treatment outcomes and quality of life in patients with HF.…”
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Short-Term Prediction of Traffic Flow Based on the Comprehensive Cloud Model by Jianhua Dong

“…These algorithms are designed to address the short-term traffic flow prediction problem. …”
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A Review of Enhancement Techniques for Cone Beam Computed Tomography Images by Hassn Mazin Al-alaaf, Mohammed Sabah Jarjees

“…These methods encompass various mathematical algorithms, machine learning approaches, and hybrid models, which aim to mitigate the imperfections present in CBCT data while preserving diagnostically relevant information. …”
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An Overview of Application of Machine Learning Models in Urban Flood Simulation and Forecasting by CHEN Zeming, FANG Xuhong, LI Jiaye, WANG Mengyao, CHEN Aifang, YIN Ling

“…Additionally, this paper also focused on the research on urban flood simulation and forecasting models based on machine learning algorithms published in the recent five years, summarized the technical processes for urban flood simulation and forecasting models based on machine learning algorithms, and proposed several current technological bottlenecks and potential solutions. …”
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Machine learning models predict risk of lower extremity deep vein thrombosis in hospitalized patients with spontaneous intracerebral hemorrhage by Weizhi Qiu, Penglei Cui, Shaojie Li, Zhenzhou Tang, Jiani Chen, Jiayin Wang, Yasong Li

“…Screening by the LASSO and Boruta algorithms yielded 15 and 7 potentially relevant variables, respectively, resulting in the identification of six significant predictors associated with DVT. …”
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A Comprehensive Approach to Rustc Optimization Vulnerability Detection in Industrial Control Systems by Kaifeng Xie, Jinjing Wan, Lifeng Chen, Yi Wang

“…This paper proposes a test case generation method based on large language models (LLMs), which utilizes prompt templates and optimization algorithms to generate a code relevant to specific optimization passes, especially for real-time control logic and safety-critical modules unique to the industrial control field. …”
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A Hybrid Approach for Target Discrimination in Remote Sensing: Combining YOLO and CNN-Based Classifiers by Jamesson Lira Silva, Fabiano da Cruz Nogueira, Douglas Damião de Carvalho, Elcio Hideiti Shiguemori, Angelo Passaro

“…Additionally, our research investigated the use of two CNN architectures, Inception-v3 and VGG-16, to extract relevant information from the images. The attributes obtained from the CNNs were used as input for three classification algorithms: multilayer perceptron (MLP), logistic regression, and support vector machine (SVM), thereby completing the target discrimination process. …”
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Overview of smart sensors based on machine learning by Wang Shuaida, Lin Guanying, Wang Nuansheng, Li Yang, Yin Meihua

“…With the rapid development of machine learning, intelligent models created by machine learning algorithms are gradually becoming the core part of new sensor data analysis. …”
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Using Adaptive Content Recommendations to Improve Logic and Programming Teaching and Learning by Aluizio Haendchen Filho, Adson Marques da Silva Esteves, Hércules Antonio do Prado, Edilson Ferneda, André Luis Alice Raabe

“…The high dropout rate in Information Technologies courses is a relevant problem in many countries, mainly because of the increasing demand for professionals in this sector. …”
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Impact of Lexical Features on Answer Detection Model in Discussion Forums by Atif Khan, Muhammad Adnan Gul, Abdullah Alharbi, M. Irfan Uddin, Shaukat Ali, Bader Alouffi

“…Prior studies have used different combinations of both lexical and nonlexical features to retrieve the most relevant answers from discussion forums, and hence, there is no standard/general set of features that could be effectively used for relevant answer/reply post classification. …”
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Quantum-enhanced intelligent system for personalized adaptive radiotherapy dose estimation by Radhey Lal, Rajiv Kumar Singh, Dinesh Kumar Nishad, Saifullah Khalid

“…The system efficiently models radiation transport and predicts patient-specific dose distributions by integrating quantum algorithms, deep learning, and Monte Carlo simulations. …”
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Effectiveness of Explainable Artificial Intelligence (XAI) Techniques for Improving Human Trust in Machine Learning Models: A Systematic Literature Review by In-On Wiratsin, Chaiyong Ragkhitwetsagul

“…Most decision-making processes worldwide are increasingly relying on artificial intelligence (AI) algorithms to enhance human welfare. Explainable Artificial Intelligence (XAI) techniques are pivotal in addressing the bottlenecks of utilizing machine learning (ML) algorithms, aiming to enhance human trust by providing transparency and interpretability. …”
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Artificial intelligence in breast oncology by Alexander Mundinger

“…AI self-correcting algorithms and the alignment of AI constructed goals with human ethics are imperative to prevent patient harm. …”
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Sparse Learning of the Disease Severity Score for High-Dimensional Data by Ivan Stojkovic, Zoran Obradovic

“…Some steps in that direction have been taken and machine learning algorithms for extracting scoring functions from data have been proposed. …”
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A Novel Feature Selection Method for Classification of Medical Data Using Filters, Wrappers, and Embedded Approaches by Saba Bashir, Irfan Ullah Khattak, Aihab Khan, Farhan Hassan Khan, Abdullah Gani, Muhammad Shiraz

“…Feature selection is the process of identifying the most relevant features from the given data having a large feature space. …”
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