Exploring cement Production's role in GDP using explainable AI and sustainability analysis in Nepal by Ramhari Poudyal, Biplov Paneru, Bishwash Paneru, Tilak Giri, Bibek Paneru, Tim Reynolds, Khem Narayan Poudyal, Mohan B. Dangi

“…Utilizing regression models like Extra Trees (Extremely Randomized Trees) Regressor, CatBoost (Categorial Boosting) Regressor, and XGBoost (eXtreme Gradient Boosting) Regressor, Random Forest and Ensemble of Sparse Embedded Trees (SET) machine learning is used to examine the demand, supply, and Gross Domestic Product (GDP) performance of cement manufacturing in India which shares a common cement related infrastructure to Nepal. …”
Get full text

Better understanding the phenotypic effects of drugs through shared targets in genetic disease networks by Elena Díaz-Santiago, Aurelio A. Moya-García, Jesús Pérez-García, Raquel Yahyaoui, Raquel Yahyaoui, Christine Orengo, Florencio Pazos, James R. Perkins, James R. Perkins, James R. Perkins, Juan A. G. Ranea, Juan A. G. Ranea, Juan A. G. Ranea, Juan A. G. Ranea

“…The overlap of these results with the SIDER databases of known drug side effects was up to 10 times higher than random, depending on the target type, disease database and score threshold used. …”
Get full text

Hubungan Tingkat Pengetahuan Ibu dengan Pemberian Imunisasi Dasar Lengkap pada Bayi di Kelurahan Parupuk Tabing Wilayah Kerja Puskesmas Lubuk Buaya Kota Padang Tahun 2013 by Atika Putri Dewi, Eryati Darwin, Edison .

“…Jumlah sampel 63 orang diambil secara Random Sampling. Data dikumpulkan melalui wawancara menggunakan kuesioner dan observasi.pengolahan data dilakukan secara komputerisasi dengan analisis uji Chi-Square pada α=0,05. …”
Get full text

Faktor-Faktor yang Berhubungan dengan Pola Pemberian ASI Eksklusif di Wilayah Kerja Puskesmas Bungus Tahun 2014 by Selvi Indriani Nasution, Nur Indrawati Liputo, Mahdawaty Masri

“…Total sample were 82 respondents which were taken by multistage random sampling. Data analysis was done by chi-square test. …”
Get full text

Application of Machine Learning to Background Rejection in Very-high-energy Gamma-Ray Observation by Jie Li, Hongkui Lv, Yang Liu, Jiajun Huang, Yu Wang, Wenbin Lin

“…Among these methods, XGBoost, CatBoost, and DNN demonstrate stronger classification capabilities than decision trees and random forests, while the fusion model exhibits the best discriminatory ability. …”
Get full text

Detection of atrial fibrillation in primary care with radial pulse palpation, electronic blood pressure measurement and handheld single-lead electrocardiography: a diagnostic accur... by Wim A M Lucassen, Henk C P M van Weert, Bjorn Winkens, Henri E J H Stoffers, J André Knottnerus, Steven B Uittenbogaart, Nicole Verbiest-van Gurp, Petra M G Erkens

“…Similarly, to limit verification bias, a random sample of patients with three negative index tests received this reference test. …”
Get full text

A Comparative Analysis of Explainable Artificial Intelligence Models for Electric Field Strength Prediction over Eight European Cities by Yiannis Kiouvrekis, Ioannis Givisis, Theodor Panagiotakopoulos, Ioannis Tsilikas, Agapi Ploussi, Ellas Spyratou, Efstathios P. Efstathopoulos

“…The analysis incorporated six core approaches: k-Nearest Neighbors, XGBoost, Random Forest, Neural Networks, Decision Trees, and Linear Regression. …”
Get full text

Prevalence and associated factors of malaria among the displaced population in refugee camps in Africa: a systematic review and meta-analysis by Habtu Debash, Ermiyas Alemayehu, Melaku Ashagrie Belete, Hussen Ebrahim, Ousman Mohammed, Daniel Gebretsadik, Mihret Tilahun, Alemu Gedefie

“…Data extraction was executed using Microsoft Excel, and the meta-analysis was performed with STATA 14 software. A random-effects model was used to estimate the pooled prevalence and associated factors of malaria. …”
Get full text

Functional gastrointestinal disorders predictors in neonates and toddlers: A machine learning approach to risk assessment by Flavia Indrio, Elio Masciari, Flavia Marchese, Matteo Rinaldi, Gianfranco Maffei, Ilaria Gangai, Assunta Grillo, Roberta De Benedetto, Enea Vincenzo Napolitano, Isadora Beghetti, Luigi Corvaglia, Antonio Di Mauro, Arianna Aceti

“…The study employed both traditional statistical methods and artificial intelligence (AI) techniques, specifically a random forest classification model, to identify key risk factors associated with the development of FGIDs. …”
Get full text

Hubungan Faktor Lingkungan dengan Kejadian Diare Balita di Wilayah Kerja Puskesmas Kambang Kecamatan Lengayang Kabupaten Pesisir Selatan Tahun 2013 by Fitra Dini, Rizanda Machmud, Roslaili Rasyid

“…Penelitian menggunakan desain analitik cross sectional dengan jumlah subjek 63 orang dengan teknik multi stage random sampling. Penelitian menggunakan kuesioner melalui wawancara dan observasi. …”
Get full text

Annual cycle variations in the gut microbiota of migratory black-necked cranes by Yujia Zhang, Ruifeng Ma, Suolangduoerji, Shujuan Ma, Shujuan Ma, Akebota Nuertai, Ke He, Hongyi Liu, Ying Zhu

“…Thirty-six ASVs were identified by random forest analysis to distinguish samples from distinct seasons. …”
Get full text

Machine learning prediction of anxiety symptoms in social anxiety disorder: utilizing multimodal data from virtual reality sessions by Jin-Hyun Park, Yu-Bin Shin, Dooyoung Jung, Ji-Won Hur, Seung Pil Pack, Heon-Jeong Lee, Hwamin Lee, Chul-Hyun Cho, Chul-Hyun Cho

“…We developed ML models that predict the upper tertile group for various anxiety symptoms in SAD using Random Forest, extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost) models. …”
Get full text

Radiomics model based on computed tomography images for prediction of radiation-induced optic neuropathy following radiotherapy of brain and head and neck tumors by Elham Raiesi Nafchi, Pedram Fadavi, Sepideh Amiri, Susan Cheraghi, Maryam Garousi, Mansoureh Nabavi, Iman Daneshi, Marzieh Gomar, Malihe Molaie, Ali Nouraeinejad

“…We integrated CT image features with dosimetric and clinical data subsequently, ranked 5 supervised ML models Bernoulli Naive Bayes, Decision Tree, Gradient Boosting Decision Trees, K-Nearest Neighbor, and Random Forest on 4 input datasets to predict radiation-induced visual complications classifiers by implementing 5-fold cross-validation. …”
Get full text

Post-Vaccination Anaphylaxis in Adults: A Systematic Review and Meta-Analysis by Flavia Pennisi, Anna Carole D’Amelio, Rita Cuciniello, Stefania Borlini, Luigi Mirzaian, Giovanni Emanuele Ricciardi, Massimo Minerva, Vincenza Gianfredi, Carlo Signorelli

“…The protocol was registered in PROSPERO in advance (ID CRD42024566928). Random-effects and fixed-effects models were used to pool data and estimate the logit proportion, with the logit-transformed proportion serving as the effect size, thereby allowing for the calculation of event rates. …”
Get full text

Blinding assessment in randomised sham-controlled trials of acupuncture:protocol for a systematic survey by Ling Li, Xin Sun, Jiali Liu, Minghong Yao, Yong Fu, Jiahui Yang, Xiaochao Luo

“…When sufficient data are available, we will also use random-effects meta-regression to explore the relationship.Ethics and dissemination Ethical approval is not required. …”
Get full text

Are neurasthenia and depression the same disease entity? An electroencephalography study by Ge Dang, Lin Zhu, Chongyuan Lian, Silin Zeng, Xue Shi, Zian Pei, Xiaoyong Lan, Jian Qing Shi, Nan Yan, Yi Guo, Xiaolin Su

“…Among the classification models, random forest performed best with an accuracy of 0.93, area under the receiver operating characteristic curve of 0.97, and area under the precision-recall curve of 0.96. …”
Get full text

Perbedaan Asupan Natrium Dan Kalium Pada Penderita Hipertensi Dan Normotensi Masyarakat Etnik Minangkabau di Kota Padang by Mifthahul Jannah, Delmi Sulastri, Yuniar Lestari

“…Jumlah sampel sebanyak 254 orang yang diambil secara multi stage random sampling. Data responden dikumpulkan dengan kuisioner, tekanan darah dengan sphygmomanometer, asupan natrium dan kalium dengan food frequency questionnaire (FFQ). …”
Get full text

Hubungan Pengetahuan dan Sikap Terhadap Rokok Dengan Kebiasaan Merokok Siswa SMP di Kota Padang by Afdol Rahmadi, Yuniar Lestari, Yenita Yenita

“…The number of samples is as many as 96 students, which was taken by sampling technique namely Cluster Sampling and Simple Random Sampling. Data were collected by questionnaire. …”
Get full text

Global seroprevalence of Toxoplasma gondii in pregnant women: a systematic review and meta-analysis by Nader Salari, Avijeh Rahimi, Hosna Zarei, Amir Abdolmaleki, Shabnam Rasoulpoor, Shamarina Shohaimi, Masoud Mohammadi

“…The heterogeneity index was found high (I2:98.9) and the random effect model was used for analysis. The egger test revealed the absence of publication bias in collected studies (p:0.088). …”
Get full text

Genetic inbreeding load and its individual prediction for milk yield in French dairy sheep by Simona Antonios, Silvia T. Rodríguez-Ramilo, Andres Legarra, Jean-Michel Astruc, Luis Varona, Zulma G. Vitezica

“…First, based on substitution effect under non-random matings, we showed analytically that inbreeding load of an ancestor can be expressed as an additive genetic effect. …”
Get full text