Relative Fat Mass and Physical Indices as Predictors of Gallstone Formation: Insights From Machine Learning and Logistic Regression by Deng L, Wang S, Wan D, Zhang Q, Shen W, Liu X, Zhang Y

“…To develop our predictive model, we employed four algorithms—Logistic Regression, Gaussian Naive Bayes (GNB), Multi-Layer Perceptron (MLP), and Support Vector Machine (SVM). …”
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Instagram's impact on dental consumers: analyzing toothpaste hashtags by Khalifa S. Al-Khalifa, Rasha AlSheikh, Basmah O. Alakloby, Hind M. Alharbi, Razan F. Alghamdi, Saqib Ali, Laila Al Dehailan

“…Method: data were acquired for the “Top 12 posts” for each selected hashtag listed by the Instagram search algorithm. The contents of each post, including the number of likes, number of followers, content type, poster role, post content, post theme, post type, and account type were collected. …”
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Simulated low-dose dark-field radiography for detection of COVID-19 pneumonia. by Rafael C Schick, Henriette Bast, Manuela Frank, Theresa Urban, Thomas Koehler, Florian T Gassert, Andreas P Sauter, Bernhard Renger, Alexander A Fingerle, Alexandra Karrer, Marcus R Makowski, Daniela Pfeiffer, Franz Pfeiffer

“…By modifying the image reconstruction algorithm, low-dose radiographs were simulated based on real participant images. …”
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The Potential Clinical Utility of the Customized Large Language Model in Gastroenterology: A Pilot Study by Eun Jeong Gong, Chang Seok Bang, Jae Jun Lee, Jonghyung Park, Eunsil Kim, Subeen Kim, Minjae Kimm, Seoung-Ho Choi

“…<b>Method:</b> We established a customized GPT with the BM25 algorithm using Open AI’s GPT-4o model, which allows it to produce responses in the context of specific documents including textbooks of internal medicine (in English) and gastroenterology (in Korean). …”
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Machine learning and molecular dynamics simulations predict potential TGR5 agonists for type 2 diabetes treatment by Ojochenemi A. Enejoh, Chinelo H. Okonkwo, Hector Nortey, Olalekan A. Kemiki, Ainembabazi Moses, Ainembabazi Moses, Florence N. Mbaoji, Abdulrazak S. Yusuf, Olaitan I. Awe

“…The dataset was cleaned and molecular descriptors based on Lipinski’s rule of five were selected as input features for the ML model, which was built using the Random Forest algorithm. The optimized ML model was used to screen the COCONUT database and predict potential TGR5 agonists based on their molecular features. 6,656 compounds predicted from the COCONUT database were docked within the active site of TGR5 to calculate their binding energies. …”
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Fetal growth and risk of stillbirth: a population-based case-control study. by Radek Bukowski, Nellie I Hansen, Marian Willinger, Uma M Reddy, Corette B Parker, Halit Pinar, Robert M Silver, Donald J Dudley, Barbara J Stoll, George R Saade, Matthew A Koch, Carol J Rowland Hogue, Michael W Varner, Deborah L Conway, Donald Coustan, Robert L Goldenberg, Eunice Kennedy Shriver National Institute of Child Health and Human Development Stillbirth Collaborative Research Network

“…Gestational age at death was determined using an algorithm that considered the time-of-death interval, postmortem examination, and reliability of the gestational age estimate. …”
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A minimal gene set characterizes TIL specific for diverse tumor antigens across different cancer types by Zhen Zeng, Tianbei Zhang, Jiajia Zhang, Shuai Li, Sydney Connor, Boyang Zhang, Yimin Zhao, Jordan Wilson, Dipika Singh, Rima Kulikauskas, Candice D. Church, Thomas H. Pulliam, Saumya Jani, Paul Nghiem, Suzanne L. Topalian, Patrick M. Forde, Drew M. Pardoll, Hongkai Ji, Kellie N. Smith

“…Our three-gene “MANAscore” algorithm outperforms other RNAseq-based algorithms in identifying validated neoantigen-specific CD8+ clones, and accurately identifies TILs that recognize other classes of tumor antigens, including cancer testis antigens, endogenous retroviruses and viral oncogenes. …”
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Integration of machine learning and experimental validation to identify the prognostic signature related to diverse programmed cell deaths in breast cancer by Longpeng Li, Longpeng Li, Jinfeng Zhao, Yaxin Wang, Zhibin Zhang, Wanquan Chen, Jirui Wang, Yue Cai

“…The prognostic signature (PCDRS) were constructed by the best combination of 101 machine learning algorithm combinations, and the C-index of PCDRS was compared with 30 published signatures. …”
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Postcholecystectomy syndrome: the modern approach: resolution of Advisory council by V. T. Ivashkin, A. V. Okhlobystin, D. S. Bordin, E. Ya. Seleznyova, Yu. A. Kucheryavy, Ye. V. Bystrovskaya, O. C. Vasnev, M. F. Osipenko, G. H. Musayev, Yu. O. Shulpekova

“…The Advisory council proposed algorithm for investigation and management of patients with postcholecystectomy syndrome (PCS). …”
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An Integrated Electricity–Gas–Heat Energy System Based on the Synergy of Long- and Short-Term Energy Storage by Min Zhang, Jinhao Wang, Huiqiang Zhi, Jun Zhao, Xiao Chang, Shifeng Zhang, Xiangyu Guo, Tengxin Wang

“…Firstly, an adaptive noise integration empirical modal decomposition method based on the optimization improvement of the grey wolf algorithm is designed for the power allocation strategy of the hybrid energy storage system; secondly, for the electric–gas system, an energy management strategy for the hybrid electric–gas energy storage system, taking into account the operating characteristics of the alkaline electrolyzer, is proposed in order to strengthen the complementary mechanism between electric energy storage and gas energy storage. …”
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Model Prognosis Masa Pengobatan Pasien Tuberkulosis Dengan Metode C4.5 by Rusdah Rusdah, Brian Agni Bregastantyo

“…Therefore, a system is needed to help predict the patient's treatment period by applying the Cross-Industry Standard Process for Data Mining (CRISP-DM) and using a data mining approach by implementing the C4.5 algorithm after exploring the data using several algorithms for classification with the aim of for the results of model performance accuracy for the prognosis of the treatment period of tuberculosis patients. …”
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Vis/NIR Spectroscopy and Vis/NIR Hyperspectral Imaging for Non-Destructive Monitoring of Apricot Fruit Internal Quality with Machine Learning by Tiziana Amoriello, Roberto Ciorba, Gaia Ruggiero, Francesca Masciola, Daniela Scutaru, Roberto Ciccoritti

“…In this study, prediction models were developed based on a multilayer perceptron artificial neural network (ANN-MLP) combined with the Levenberg–Marquardt learning algorithm. Regarding the Vis/NIR spectrophotometer dataset, good predictive performances were achieved for TSS (R² = 0.855) and DM (R² = 0.857), while the performance for TA was unsatisfactory (R² = 0.681). …”
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Prediction of Cisplatin‐Induced Acute Kidney Injury Using an Interpretable Machine Learning Model and Electronic Medical Record Information by Kaori Ambe, Yuka Aoki, Miho Murashima, Chiharu Wachino, Yuto Deki, Masaya Ieda, Masahiro Kondo, Yoko Furukawa‐Hibi, Kazunori Kimura, Takayuki Hamano, Masahiro Tohkin

“…We aimed to develop a predictive model for Cis‐AKI using patient clinical information based on an interpretable machine learning algorithm. This single‐center retrospective study included hospitalized patients aged ≥ 18 years who received the first course of cisplatin chemotherapy from January 1, 2011, to December 31, 2020, at Nagoya City University Hospital. …”
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Penentuan Filterbank Wavelet Menggunakan Algoritma Mean Best Basis untuk Ekstraksi Ciri Sinyal Suara Ber-Noise by Abdurahim Abdurahim, Syahroni Hidayat

“…The Mean Best Basis (MBB) algorithm and db44 and db45 wavelet functions are applied to obtain the WPCC filterbank design. …”
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Akuisisi Foreground dan Background Berbasis Fitur DTC pada Matting Citra secara Otomatis by Meidya Koeshardianto, Eko Mulyanto Yuniarno, Mochamad Hariadi

“…Background acquisition is determined from the variant value of the DCT feature that is clustered using the k-means algorithm. Foreground acquisition is determined by a subset resulting from clustering DCT values with edge detection features. …”
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Could Infectious Agents Play a Role in the Onset of Age-related Macular Degeneration? A Scoping Review by Petra P. Larsen, MD, PhD, Virginie Dinet, PhD, Cécile Delcourt, PhD, Catherine Helmer, MD, PhD, Morgane Linard, MD, PhD

“…Results: Two investigators independently screened the 868 articles obtained by our algorithm and the reference lists of selected studies. …”
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Diagnosis of Malignant Endometrial Lesions from Ultrasound Radiomics Features and Clinical Variables Using Machine Learning Methods by Shanshan Li, Jiali Wang, Li Zhou, Hui Wang, Xiangyu Wang, Jian Hu, Qingxiu Ai

“…And Random Forest model algorithms have demonstrated excellent performance in identifying benign and malignant changes in endometrial tissue. …”
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Predicting phage-host interaction via hyperbolic Poincaré graph embedding and large-scale protein language technique by Jie Pan, Rui Wang, Wenjing Liu, Li Wang, Zhuhong You, Yuechao Li, Zhemeng Duan, Qinghua Huang, Jie Feng, Yanmei Sun, Shiwei Wang

“…In this study, we present GE-PHI, a machine-learning-based model for predicting phage-host interactions (PHIs) by integrating knowledge graph embedding algorithm with a large-scale protein language model. …”
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Analisis Metode Estimasi Biaya pada Perangkat Lunak Beserta Faktor-Faktor yang Mempengaruhi : A Systematic Literature Review by Amelia Devi Putri Ariyanto, Lutfiyatul ‘Azizah, Umi Laili Yuhana

“…Besides, this study also succeeded in finding the best method and combination of methods based on best accuracy, namely COCOMO II and the combination of Genetic Algorithm and Artificial Bee Colony, along with the five main factors that influence cost estimation so that it can be used by researchers or other practitioners to develop cost estimates for software projects. …”
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Digital twin-based modeling of natural gas leakage and dispersion in urban utility tunnels [version 2; peer review: 2 approved] by Jiansong Wu, Jitao Cai, Ziqi Han, Yanzhu Hu, Ming Fu, Yuefei Li, Xin Wang, Xiaofu Zou

“…Based on this model, real-time integration of gas sensor data from utility tunnels is achieved through the DA algorithm. Therefore, the predicted results can be calibrated by the continuous data in the absence of complete source term information. …”
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