On the effect of sampling frequency on the electricity theft detection performance by Fatemeh Soleimani Nasab, Foad Ghaderi

“…Abstract Electricity theft is a common problem in many countries and affects the revenue of the electricity industry significantly. Recently, machine and deep learning techniques are being used widely to detect thieves by analysing the consumption patterns. …”
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Innovative AI Solutions for Water-Efficient Smart Irrigation in Agriculture by Saha Laboni, Dubey Ahilya

“…The proposed AI solutions are integrated platform of machine learning algorithms and sensor data, predictive analytics for the purpose to generate a water efficient irrigation framework reacts dynamically to the crops' needs and environmental conditions. …”
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Interpretable Identification of Dynamic Adaptive Streaming over HTTP (DASH) Flows Based on Feature Engineering by Arkadiusz Biernacki

“…The clustering used the most significant features to group similar traffic patterns. We employed the following three algorithms that represent different clustering methodologies: partition-based, density-based, and probabilistic approaches. …”
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Enhancing Neurodegenerative Disease Diagnosis Through Confidence-Driven Dynamic Spatio-Temporal Convolutional Network by Ning Yuan, Donghai Guan, Shengrong Li, Li Zhang, Qi Zhu

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Role of mass spectrometry-based serum proteomics signatures in predicting clinical outcomes and toxicity in patients with cancer treated with immunotherapy by Young Kwang Chae, Emma Yu, Na Hyun Kim, Min Jeong Kim, Leeseul Kim, Hyung-Gyo Cho, Yeonggyeong Park, Yoonhee Choi, Seung Pyo Daniel Hong

“…These protein signatures are derived from patient serum samples based on mass spectrometry and act as biomarkers to predict response to immunotherapy. Using machine learning algorithms, serum proteomic tests were developed through training data sets from advanced non-small cell lung cancer (Host Immune Classifier, Primary Immune Response) and malignant melanoma patients (PerspectIV test). …”
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Clinical prediction of intravenous immunoglobulin-resistant Kawasaki disease based on interpretable Transformer model. by Gahao Chen, Ziwei Yang

“…A cohort of 1,578 pediatric KD cases was systematically divided into training and validation sets. Six machine learning algorithms - Random Forest (RF), AdaBoost, Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Tabular Prior-data Fitted Network version 2.0 (TabPFN-V2) - were implemented with five-fold cross-validation to optimize model hyperparameters. …”
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Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis by Lu Xing, Tao Wu, Li Yu, Nian Zhou, Zhao Zhang, Yunjing Pu, Jinnan Wu, Hong Shu

“…This study aims to screen potential diagnostic indicators affected by DNA methylation for psoriasis based on bioinformatics using multiple machine learning algorithms and to preliminarily explore its molecular mechanisms. …”
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Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis. by Jessica L Nielson, Shelly R Cooper, John K Yue, Marco D Sorani, Tomoo Inoue, Esther L Yuh, Pratik Mukherjee, Tanya C Petrossian, Jesse Paquette, Pek Y Lum, Gunnar E Carlsson, Mary J Vassar, Hester F Lingsma, Wayne A Gordon, Alex B Valadka, David O Okonkwo, Geoffrey T Manley, Adam R Ferguson, TRACK-TBI Investigators

“…Our hypothesis was two-fold: 1) A machine learning tool known as topological data analysis (TDA) would reveal data-driven patterns in patient outcomes to identify candidate biomarkers of recovery, and 2) TDA-identified biomarkers would significantly predict patient outcome recovery after TBI using more traditional methods of univariate statistical tests. …”
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A novel flexible near-infrared endoscopic device that enables real-time artificial intelligence fluorescence tissue characterization. by Gareth Gallagher, Ra'ed Malallah, Jonathan P Epperlein, Jeffrey Dalli, Niall Hardy, Abhinav Jindal, Pol G MacAonghusa, Ronan A Cahill

“…Here, to close this technical gap, we present our development of a colonoscope-compatible flexible imaging probe for NIR-ICG visualization combined with a full field of view machine learning (ML) algorithm for fluorescence quantification and perfusion pattern cross-correlation (including first in human testing). …”
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Optimization of IoT-Based Motion Intelligence Monitoring System by Jian Qiao, Zhendong Zhang, Enqing Chen

“…For active pattern recognition, two types of classification algorithms with different complexity are proposed based on Support Vector Machine (SVM) and deep neural networks, respectively, to adapt to scenarios with different computational capabilities. …”
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Load Balancing and Server Consolidation in Cloud Computing Environments: A Meta-Study by Mohammed Ala'anzy, Mohamed Othman

“…Just considering energy-efficiency (that can be attained efficiently by consolidate the servers) may not be enough for real applications because it may cause problems such as unbalanced load for each Physical Machine (PM). Therefore, this paper surveys published load balancing algorithms that achieved by server consolidation via a meta-analysis. …”
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GREEN ECONOMY AND HOLISTIC PLANNING BY ARTIFICIAL INTELLIGENCEAPPLICATION by STEVOVIC IVAN, HADROVIĆ SABAHUDIN, JOVANOVIC MIHAILO

“…On the one hand, IT such as machine learning, data analytics, and optimization algorithms offer immense potential to enhance resource efficiency, optimize energy systems, and facilitate sustainable decision-making processes. …”
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Review of Modern Forest Fire Detection Techniques: Innovations in Image Processing and Deep Learning by Berk Özel, Muhammad Shahab Alam, Muhammad Umer Khan

“…Furthermore, we explore the utilization of deep learning and machine learning in training intelligent algorithms to recognize fire patterns and features. …”
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A deep learning model for predicting systemic lupus erythematosus-associated epitopes by Jiale He, Zixia Liu, Xiaopo Tang

“…Results The hybrid model outperformed both baseline machine learning algorithms and ablated versions of itself. …”
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Early Breast Cancer Prediction Using Thermal Images and Hybrid Feature Extraction-Based System by Doaa Youssef, Hanan Atef, Shaimaa Gamal, Jala El-Azab, Tawfik Ismail

“…The back end of the methodology uses support vector machine (SVM) and extreme gradient boosting (XGB) classification algorithms to establish the relationship between the retrieved feature vector and breast functionality. …”
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Accurate and affordable multi-cancer early detection and localization via plasma cfDNA multi-omic profiling by Pin Cui, Weihuang He, Mingji Feng, Hanming Lai

“…Findings: In this study, we performed both WGBS and WGS on 17 healthy individuals, 26 HCC patients, 32 lung cancer patients, and 15 colorectal patients to prove the feasibility of inferring cfDNA methylation patterns using cfDNA fragmentation profile. By combining cfDNA cleavage profile of CpG sites with machine learning algorithms, we have identified specific CpG cleavage profile as biomarkers to predict the methylation status of individual CpG sites, based on which we built in silico classifiers for prediction of each of the four groups previously mentioned, achieving considerable performance of AUC ranging from 0.8896 to 0.959. …”
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Temporal Backtracking and Multistep Delay of Traffic Speed Series Prediction by Licheng Qu, Minghao Zhang, Zhaolu Li, Wei Li

“…With a real traffic data set, the coordinate descent algorithm was employed to search and determine the optimal backtracking length of traffic sequence, and multistep delay predictions were performed to demonstrate the relationship between delay steps and prediction accuracies. …”
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Automated Image-Based Wound Area Assessment in Outpatient Clinics Using Computer-Aided Methods: A Development and Validation Study by Kuan-Chen Li, Ying-Han Lee, Yu-Hsien Lin

“…K-means clustering is a machine learning algorithm that segments the wound region by grouping pixels in an image according to their color similarity. …”
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Rural Landscape Characters and Spatial Correlation Mechanism in the Tiaoxi River – Canal Basin in Zhejiang Province by Lin ZHANG, You ZUO, Binyi LIU

“…Future research will construct a spatio-temporal dynamic dataset of canal heritage landscapes, which aims to enhance the fine-grained character extraction and type classification accuracy of machine learning algorithm models for rural landscapes. …”
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Drunk Driver Detection Using Thermal Facial Images by Chin-Heng Chai, Siti Fatimah Abdul Razak, Sumendra Yogarayan, Ramesh Shanmugam

“…This study aims to investigate and propose a machine learning approach that can accurately detect alcohol consumption by analyzing the thermal patterns of facial features. …”
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