Developing an efficient explainable artificial intelligence approach for accurate reverse osmosis desalination plant performance prediction: application of SHAP analysis by Meysam Alizamir, Mo Wang, Rana Muhammad Adnan Ikram, Sungwon Kim, Kaywan Othman Ahmed, Salim Heddam

“…In this study, the predictive accuracy of six different machine learning models, including Natural Gradient-based Boosting (NGBoost), Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Support vector regression (SVR), Gaussian Process Regression (GPR), and Extremely Randomized Tree (ERT) was evaluated for modelling the parameter of permeate flow as a key element in system efficiency, energy consumption, and water quality using six various input combinations of feed water salt concentration, condenser inlet temperature, feed flow rate, and evaporator inlet temperature. …”
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Cellular senescence promotes macrophage-to-myofibroblast transition in chronic ischemic renal disease by Yu Zhao, Xiang-Yang Zhu, Wenqi Ma, Ying Zhang, Fei Yuan, Seo Rin Kim, Hui Tang, Kyra Jordan, Amir Lerman, Tamara Tchkonia, James L. Kirkland, Lilach O. Lerman

“…MMT markers and TGF-β/Smad3 expression also rose in these macrophages and decreased after IFITM3 or ITGB3 silencing. p16 INK-4a -expressing macrophages may regulate interstitial fibrosis in RAS via MMT. This process is associated with elevated expression of ITGB3 and TGF-β/Smad3 pathway activation through neighboring senescent cell-derived IFITM3. …”
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Mosquito prevention strategies can improve indoor heat stress in hot climates: a case of traditional Kenyan homes by Haiwei Li, Haimavati Raman, Bernard Abong’o, Teresa Bange, Yongling Zhao, Carol Brayne, Ronita Bardhan

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An ensemble strategy for piRNA identification through hybrid moment-based feature modeling by Mansoor Ahmed Rasheed, Tamim Alkhalifah, Fahad Alturise, Yaser Daanial Khan

“…Such accurate instrumentation of transposon-associated piRNA tags can considerably involve the study of small ncRNAs and support the understanding of the gametogenesis process. First, a number of moments were adopted for the conversion of the primary sequences into feature vectors. …”
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Application of Spectral Phototherapy in the Treatment of Patients with Ronchopathy and Obstructive Sleep Apnea Syndrome: a Prospective Study by Bair A. Zhigzhitov, Larisa A. Marchenkova, Vladimir B. Knyazkov, Daria D. Lebedeva, Lev G. Agasarov

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Osteoplastic biomaterials from organic and mineral components of the bone matrix: a literature review by Pavel А. Markov, Petr S. Eremin, Elena S. Berezkina, Marina V. Volkova, Irina A. Usova, Ilmira R. Gilmutdinova

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Comparative study on risk prediction model of type 2 diabetes based on machine learning theory: a cross-sectional study by Shu Wang, Shuang Wang, Rong Chen, Ling Luo, Qiaoli Zhang, Danli Kong, Rudai Cao, Chunwen Lin, Jialu Huang, Haibing Yu, Yuan Lin Ding

“…In the initial population, we excluded individuals with more than 20% missing data and eventually included 4106 subjects.Design K nearest neighbour algorithm and synthetic minority oversampling technique were used to process the data. Single factor analysis was used for preliminary selection of variables. …”
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Assessing veterinary professionals’ perspectives on community knowledge, attitudes, and practices regarding dog rabies in Turkana, Kenya by Moumita Das, Moumita Das, María Sol Pérez Aguirreburualde, Job Ronoh Kipkemoi, Erenius Lochede Nakadio, Andres M. Perez, Andres M. Perez, Melinda Wilkins

“…The main reservoir and vector for human transmission of the disease is domestic dogs. …”
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Construction of a feature gene and machine prediction model for inflammatory bowel disease based on multichip joint analysis by Yan Chaosheng, Sun Haowen, Rao Jingjing, Dai Yuanyuan, Duan Wenhui, Sheng Yingyue, Xue Yuzheng

“…Moreover, we used the SHAP model to interpret the results of the machine learning process. Finally, we examined the relationships between the differentially expressed genes and immune cells. …”
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Predicting cardiotoxicity in drug development: A deep learning approach by Kaifeng Liu, Huizi Cui, Xiangyu Yu, Wannan Li, Weiwei Han

“…Using computational methods, this study facilitates a more efficient drug development process, reduces costs, and improves the safety of new drug candidates, ultimately benefiting medical and public health.…”
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Kinematics of the Kashmir Himalaya: Inferences from geological and geodetic data by Ahsan Afzal Wani, Bikram Singh Bali, Sareer Ahmad Mir, Mohammad Irfan Wani

“…To quantify the vertical and horizontal deformation rates in the Kashmir Valley, we use GAMIT/GLOBK software to process the GPS data. The lateral motion data indicate that the Indian plate continues to move towards the Eurasian plate at a rate of 36–42 mm/yr, while the vertical vectors infer a transition zone across the Kashmir valley.Using ArcGIS, Iso-base and Iso-ketabase maps were generated from the GPS vertical vectors to study the vertical deformation status of the Kashmir Valley. …”
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A comprehensive investigation of morphological features responsible for cerebral aneurysm rupture using machine learning by Mostafa Zakeri, Amirhossein Atef, Mohammad Aziznia, Azadeh Jafari

“…The aim of this research is to provide valuable insights that can help make informed decisions during the treatment process and potentially save the lives of future patients. …”
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Development of a machine learning prediction model for loss to follow-up in HIV care using routine electronic medical records in a low-resource setting by Tamrat Endebu, Girma Taye, Wakgari Deressa

“…On the basis of the ML feature selection process, six strong predictors of LTFU were identified: differentiated service delivery model, adherence, tuberculosis preventive therapy, follow-up period, nutritional status, and address information. …”
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Quantitative Methods of Selecting a Tool for Project Management in the Financial Sector by D. A. Vlasov, P. A. Karasev, A. V. Sinchukov

“…Within the framework of this article, the features of the choice of a project management tool in the financial sector based on the use of quantitative methods that make the decision-making process significantly more meaningful and effective are disclosed.The aim of the study is to develop elements of a methodology for quantitative analysis of alternative tools, including recommendations on the choice of alternatives and criteria for their analysis, as well as the complex use of various methods to justify the final choice of an instrument.The research materials and methods reflected in the methodology of quantitative analysis of alternative project management tools in the financial sphere, and implemented in the course of the research, are based on supplementing the results obtained through the use of the classical basic level method – the method of geometric averages by methods of advanced level decision theory – the method of eigenvalues and vectors, as well as the ideal point method. …”
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Best Band Selection using Principle Component Analysis Algorithm from Remote Sensing Data by Maha Hasso, Mona Siddiq

“…In this paper we use principle component analysis  algorithm applied on remote sensing data and find covariance matrix for bands that should be processed then find eigen vector using Jacobi methods .The algorithm was  applied on multispectral images of Thematic Mapper sensor , it concluded that the six  band was  the best band , the value of it’s eigen value    was the biggest one  and the value of signal to noise ratio equals to 74.7217. …”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Operational risk data were collected, pre-processed, and then used for predictions with machine learning models, including Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), Logistic Regression (LR), Naïve Bayes (NB), and k-Nearest Neighbors (KNN). …”
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Machine learning in assessing the association between the size and structure of the ascending aortic wall in patients with aortic dilatation of varying severity by V. E. Uspenskiy, V. L. Saprankov, V. I. Mazin, D. G. Zavarzina, A. B. Malashicheva, O. B. Irtyuga, O. M. Moiseeva, M. L. Gordeev

“…Standard paraclinical investigations and pathological examination of the VA wall were used. Statistical processing was carried out in the SPYDER 4.1.5 environment (Python 3.8), and included univariate correlation analysis, logistic regression analysis, as well as supervised machine learning (ML) methods (support vector machine, k-nearest neighbor method, random forest).Results. …”
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Abnormal heart sound recognition using SVM and LSTM models in real-time mode by Moy’awiah A. Al-Shannaq, Areen Nasrawi, Abed Al-Raouf K. Bsoul, Ahmad A. Saifan

“…The proposed solution relies on the support vector machine and the long-short term memory neural network to distinguish between normal and abnormal heartbeat sounds and to recognize the type of abnormality (in the case distinguished) respectively. …”
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Klasifikasi Cyberbullying Pada Tweet Bahasa Sunda Dengan Menggunakan Hybrid Learning Model by Anisa Putri Setyaningrum, Muhammad Fahmy Nadhif

“…However, detecting it automatically remains challenging, mainly due to limited datasets and the difficulty of processing the language effectively. This study aims to develop a Sundanese cyberbullying detection system using a combination of stemming and hybrid learning models. …”
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A Novel Adaptive Fine-Tuning Algorithm for Multimodal Models: Self-Optimizing Classification and Selection of High-Quality Datasets in Remote Sensing by Yi Ren, Tianyi Zhang, Zhixiong Han, Weibin Li, Zhiyang Wang, Wenbo Ji, Chenhao Qin, Licheng Jiao

“…Next, the data within each cluster are processed by calculating the translational difference between the original and perturbed data in the multimodal large model’s vector space. …”
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