Accuracy of a 2-minute eye-tracking assessment to differentiate young children with and without autism by Kristelle Hudry, Lacey Chetcuti, Diana Weiting Tan, Alena Clark, Alexandra Aulich, Catherine A. Bent, Cherie C. Green, Jodie Smith, Kathryn Fordyce, Masaru Ninomiya, Atsushi Saito, Shuji Hakoshima, Andrew J. O. Whitehouse

“…Industry employees who developed the final Algorithm were non-blinded to child group, and considered only gaze fixation durations. …”
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Digital Twin and TD3-Enabled Optimization of xEV Energy Management in Vehicle-to-Grid Networks by Irum Saba, Abdulraheem H. Alobaidi, Sultan Alghamdi, Muhammad Tariq

“…This paper addresses these challenges by proposing an advanced ESS framework that integrates digital twin (DT) technology with the twin-delayed deep deterministic policy gradient (TD3) algorithm, a state-of-the-art reinforcement learning method derived from the deep deterministic policy gradient (DDPG). …”
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A Deep Learning Framework for Chronic Kidney Disease stage classification by Gayathri Hegde M, P Deepa Shenoy, Venugopal KR, Arvind Canchi

“…Timely detection of the CKD stage is essential for enhancing healthcare services and decreasing morbidity and mortality. …”
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Precision Agriculture: Utilizing Machine Learning for Accurate Plant Disease Diagnosis by Divya Banti, Tandan Gajendra

“…Real time real data on crop conditions and stress factors is of great help to early detection of diseases through remote sensing. …”
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Proposed Comprehensive Methodology Integrated with Explainable Artificial Intelligence for Prediction of Possible Biomarkers in Metabolomics Panel of Plasma Samples for Breast Canc... by Cemil Colak, Fatma Hilal Yagin, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

“…The proposed XAI system using interpretable metabolite data can serve as a clinical decision support tool to improve early diagnosis processes.…”
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Does machine learning outperform logistic regression in predicting individual tree mortality? by Aitor Vázquez-Veloso, Astor Toraño Caicoya, Felipe Bravo, Peter Biber, Enno Uhl, Hans Pretzsch

“…Through different case studies, when more variables were used, general performance improved as expected, while more extensive datasets decreased the performance level of the algorithms. …”
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Analysis of a Data-Driven Vector-Borne Dengue Transmission Model for a Tropical Environment in Bangladesh by Mahadee Al Mobin, Md. Kamrujjaman, Md. Mamun Molla, Shi Chen

“…Our experimentation shows that the infection transmission will be at its peak when the length of the on-season is around 10 months. Based on the data of 2022, the current dynamic of the disease scenario in Bangladesh shows that the disease will not persist in the long run but occasional outbreaks may occur, given the right set of conditions. …”
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Examining Deep Learning Techniques for Ethical Artificial Intelligence: Cleansing Malicious Comments from Users by Ji Woong Yoo, Kyoung Jun Lee, Arum Park

“…The primary objective was to evaluate how deep learning techniques can improve the quality of data obtained from news comments. …”
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Climate-Based Prediction of Rice Blast Disease Using Count Time Series and Machine Learning Approaches by Meena Arumugam Gopalakrishnan, Gopalakrishnan Chellappan, Santhosh Ganapati Patil, Santosha Rathod, Kamalakannan Ayyanar, Jagadeeswaran Ramasamy, Sathyamoorthy Nagaranai Karuppasamy, Manonmani Swaminathan

“…The Diebold–Mariano test further demonstrated that ANNs are more predictive than other models. …”
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Prediction of Diabetes in Middle-Aged Adults: A Machine Learning Approach by Gideon Addo, Bismark Amponsah Yeboah, Michael Obuobi, Raphael Doh-Nani, Seidu Mohammed, David Kojo Amakye

“…The participants comprised both diabetic and non-diabetic individuals showing diabetes-like symptoms. …”
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Optimized deep residual networks for early detection of myocardial infarction from ECG signals by Pon Bharathi A, Madavan R, Sakthivel E

“…MI is considered as a life-threatening disease, which leads to an increase number of deaths or damage to the heart, and hence, prompt detection of MI is critical to decrease the mortality rate. …”
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Enhancing Missing Data Imputation for Migrants Data: A Neutrosophic Set-Based Machine Learning Approach by Doaa A. Abdo, A. A. Salama, Alaa A. Abdelmegaly, Hanan Khadari Mahdi Mahmoud

“…This study tackles the problem of missing data in migrant datasets by introducing a new framework that combines machine learning techniques with neutrosophic sets. …”
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A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…The algorithm development process demonstrated the effectiveness of our hybrid approach in dental health analytics. …”
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A method for efficient virtual-physical synchronization of the digital twin system of an excavation-supporting robot cluster targeting coal pillars between mining faces by Qinghua MAO, Junlei SIMA, Hongwei MA, Chuanwei WANG, Yanzhang CHEN, Wenjin GUO, Wenda CUI, Jiashuai CHENG

“…This leads to a decreased data size. A trajectory prediction-correction model was developed for the excavation-supporting robot cluster. …”
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A hybrid approach based on k-nearest neighbors and decision tree for software fault prediction by Manpreet Singh, Jitender Kumar Chhabra

“… Software testing is a very important part of the software development life cycle to develop reliable and bug-free software but it consumes a lot of resources like development time, cost, and effort. …”
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Brain tumor detection through image fusion using whale optimization and edge preserving filter by Bhattiprolu Nagasirisha, Venkatesh Munagala, Ramakrishna Reddy Eamani, Mocherla Venkata Srikanth, Asileti Suneel Kumar, Varre Venkata Kanaka Durga Prasad

“…By maintaining the pertinent details and characteristics of the original images, medical image fusion aims to increase the precision of disease diagnosis. …”
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Resilient VPP cost optimization in DER-driven microgrids for large distribution systems considering uncertainty during extreme events by T.D. Suresh, M. Thirumalai, R. Hemalatha, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…Frequent disruptions from extreme weather events pose a significant threat to modern power distribution systems. …”
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An Adaptive Neural Network Fuzzy Sliding Mode Controller for Tracking Control of Deep-Sea Mining Vehicles by Shidong Wang, Zida Shan, Jialuan Xiao, Junjun Cao, He Zhang, Nan Sun

“…Traditional track-driven deep-sea nodule mining solutions significantly disrupt seabed ecosystems, making them unsuitable for commercial application. …”
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Impact of summer heat and mitigation strategies on apple (Cosmic Crisp®) fruit color dynamics quantified using crop physiology sensing system by Basavaraj R. Amogi, Lav R. Khot, Bernardita V. Sallato

“…Results suggest that prolonged daytime Tair exceeding 35 °C could cause significant degradation of red pigmentation (increasing h° and declining a∗). …”
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Design and Development of Diabetes Management System Using Machine Learning by Robert A. Sowah, Adelaide A. Bampoe-Addo, Stephen K. Armoo, Firibu K. Saalia, Francis Gatsi, Baffour Sarkodie-Mensah

“…This paper describes the design and implementation of a software system to improve the management of diabetes using a machine learning approach and to demonstrate and evaluate its effectiveness in controlling diabetes. …”
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