Machine learning models for diagnosing lymph node recurrence in postoperative PTC patients: a radiomic analysis by Feng Pang, Lijiao Wu, Jianping Qiu, Yu Guo, Liangen Xie, Shimin Zhuang, Mengya Du, Danni Liu, Chenyue Tan, Tianrun Liu

“…Using 3D Slicer software, Regions of Interest (ROI) were delineated on enhanced venous phase CT images, analyzing 302 positive and 391 negative lymph nodes. …”
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Concept of a geoinformation platform for landmines and other explosive objects detection and mapping with UAV by Mykhailo Popov, Sergey Stankevich, Sergey Mosov, Stanislav Dugin, Stanislav Golubov, Artem Andreiev, Artur Lysenko, Ievgen Saprykin

“…At present, the concept is being developed in the form of a geoinformation platform research prototype involving an open-source Quantum GIS (QGIS) software system and Python programming language, which is used to create plug-ins for QGIS. …”
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Understanding Flaky Tests Through Linguistic Diversity: A Cross-Language and Comparative Machine Learning Study by Azeem Ahmad, Xin Sun, Muhammad Rashid Naeem, Yasir Javed, Mohammad Akour, Kristian Sandahl

“…We compare the performance of classifiers such as Random Forest, Decision Tree, Naive Bayes, Support Vector Machine, and Logistic Regression in both single-language and cross-language settings. …”
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AI-enhanced automation of building energy optimization using a hybrid stacked model and genetic algorithms: Experiments with seven machine learning techniques and a deep neural net... by Mohammad H. Mehraban, Samad ME Sepasgozar, Alireza Ghomimoghadam, Behrouz Zafari

“…Recent advances in artificial intelligence (AI) may allow for precise measurement and optimization of building energy saving, which is yet to be explored. …”
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Evaluation of choices and time spent on an open online elective course by undergraduate medical students during the COVID-19 pandemic by Z Mfeka, A Turner, J E Wolvaardt, D Muganhiri

“…The COVID-19 pandemic highlighted the weakness of relying on in-person tuition in higher education. …”
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The development and use of data warehousing in clinical settings: a scoping review by Shiyang Lyu, Simon Craig, Simon Craig, Gerard O'Reilly, Gerard O'Reilly, David Taniar

“…We searched four databases (PubMed, CINAHL, Scopus and IEEE-Xplore), identifying peer-reviewed, English-language studies from 1st January 2014 to 1st January 2024, that focus on data warehousing in healthcare, covering either general or specialised data warehouse applications. Python programming was used to extract the search results and transform the data into a tabular format for analysis.ResultsAfter removing 1,194 duplicates, 4,864 unique papers remained. …”
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Detection of Victimization Patterns and Risk of Gender Violence Through Machine Learning Algorithms by Edna Rocio Bernal-Monroy, Erika Dajanna Castañeda-Monroy, Rafael Ricardo Rentería-Ramos, Sixto Enrique Campaña-Bastidas, Jessica Barrera, Tania Maribel Palacios-Yampuezan, Olga Lucía González Gustin, Carlos Fernando Tobar-Torres, Zeneida Rocio Ceballos-Villada

“…Implemented in Python and R, the models were statistically validated to ensure their reliability. …”
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Identifying chemotherapy beneficiaries in nasal and paranasal sinus cancers: epidemiological trends and machine learning insights by Zihan Chen, Zongwei Huang, Yuhui Pan, Youliang Weng, Zijie Wu, Jing Wang, Wenxi Wu, Xinyi Hong, Xin Chen, Sufang Qiu

“…Additionally, ten advanced machine learning models were utilized and evaluated in Python to predict patient survival outcomes. Results This study analyzed data from 3,190 patients. …”
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Análise do perfil de médicos matriculados no curso “Atenção aos problemas neurológicos frequentes na Atenção Básica” by Victória Flor Bretas, Thais Nara Costa Ferreira, Felipe César Soares, Leonardo Cançado Monteiro Savassi

“…Métodos: Realizou-se a análise do comportamento de médicos no curso, a partir do banco de dados de matrículas, sob responsabilidade da Secretaria Executiva da UNA-SUS, com análise quantitativa da correlação das matrículas e taxas de conclusão com dados demográficos ao longo dos quatro anos de oferta a partir do software Python versão 3.12.0. Resultados: Houve 4.014 médicos matriculados, com pico de matrículas em 2021 e melhores taxas de conclusão em 2020, a maioria mulheres (61,83%), da região Sudeste (31,98%) e da faixa etária de 31 a 35 anos, com maior volume de matriculados entre 26 e 40 anos. …”
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The relationship between activities of daily living and speech impediments based on evidence from statistical and machine learning analyses by Liu Jun, Hongguo Li, Yu Mao, Lan Hu, Dan Wu

“…Machine learning algorithms, specifically Support Vector Machine (SVM), Decision Tree (DT), and Logistic Regression (LR), were implemented in Python 3.10.2.ResultsAnalysis of demographic characteristics revealed that the average BI score in the “With Speech impediments” group was 49.46, significantly lower than the average score of 85.11 in the “Without Speech impediments” group. …”
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Ensemble learning to predict short birth interval among reproductive-age women in Ethiopia: evidence from EDHS 2016–2019 by Jenberu Mekurianew Kelkay, Deje Sendek Anteneh, Henok Dessie Wubneh, Abraham Dessie Gessesse, Gebeyehu Fassil Gebeyehu, Kalkidan Kassahun Aweke, Mikiyas Birhanu Ejigu, Mathias Amare Sendeku, Kirubel Adrissie Barkneh, Hasset Girma Demissie, Wubshet D. Negash, Birku Getie Mihret

“…Results Random forest demonstrated the best performance with an accuracy 97.84%, recall of 99.70%, F1-score of 97.81%, 98.95% precision on test data and AUC (98%). Region, residency, age of women, sex of child, respondent education, distance health facility, husband education and religion were top predicting factors of short birth interval among women in Ethiopia. …”
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Machine-learning algorithm to predict home delivery after antenatal care visit among reproductive age women in East Africa by Agmasie Damtew Walle, Shimels Derso Kebede, Jibril Bashir Adem, Daniel Niguse Mamo

“…A total weighted sample of 44,123 women was analyzed using Python version 3.11. Nine supervised machine-learning algorithms were applied, following Yufeng Guo's steps for supervised learning. …”
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Application Of ArtifiCial Intelligence in E-Governance: A Comparative Study of Supervised Machine Learning and Ensemble Learning Algorithms on Crime Prediction. by Niyonzima, Ivan, Muhaise, Hussein, Akankwasa, Aureri

“…The supervised machine learning algorithms used include K-Nearest Neighbor (KNN), decision tree classifier (CART), Naïve Bayes (NB) and Support vector machine (SVM). …”
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Can Peritumoral Radiomics Based on MRI Predict the Microvascular Invasion Status of Combined Hepatocellular Carcinoma and Cholangiocarcinoma Before Surgery? by Guo L, Huang C, Hao P, Jia N, Zhang L

“…The tumor in MRI images was segmented by ITK-SNAP software in three dimensions and extended 1 centimeter(cm) towards the tumor periphery. Then, the Python open-source platform was used for radiomics analysis. …”
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Application of models in predicting sputum conversion after two months of intensive phase of anti-tuberculosis medication in Taraba State by D. N Kevin, S. Bello, B. M Gabdebo, A. F Ayodele, A Walter, U. E Etim

“…Descriptive statistics were performed on the sociodemographic characteristics and Python statistical software was used to develop predictive models, decision tree, and logistic regression. …”
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Pretreatment CT-Based Machine Learning Radiomics Model Predicts Response in Inoperable Stage III NSCLC Treated with Concurrent Radiochemotherapy Plus PD-1 Inhibitors by Ya Li Bachelor, Min Zhang Bachelor, Yong Hu MM, Bo Du Bachelor, Youlong Mo Bachelor, Tianchu He MM, Mingdan Zhao Bachelor, Benlan Li Bachelor, Ji Xia Bachelor, Zhongjun Huang Bachelor, Fangyang Lu MD, Zhen Huang Bachelor, Bing Lu MD, Jie Peng MD

“…First, ITK-SNAP software was used to delineate the primary tumor lesions in the lung window and define a region of interest (ROI). Second, features were extracted using Python (version 3.6) and filtered using Least absolute shrinkage and selection operator regression. …”
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Study of the interval width of features for improving forecasting efficiency of the transport flow intensity by I. N. Pugachev, N. G. Sheshera, D. Yе. Grigorov

“…The values at which temperature regimes (air, soil and dew point) best describe the intensity of the traffic flow were established. …”
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Validation of automated paper screening for esophagectomy systematic review using large language models by Rashi Ramchandani, Eddie Guo, Esra Rakab, Jharna Rathod, Jamie Strain, William Klement, Risa Shorr, Erin Williams, Daniel Jones, Sebastien Gilbert

“…GPT-4’s inclusion and exclusion decision were compared to those decided human reviewers. …”
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Comparison between transtracheal and intravenous 2% lignocaine in attenuating hemodynamic stress response following direct laryngoscopy and endotracheal intubation: a randomized co... by Monotosh Pramanik, Uddalak Chattopadhyay, Shalini Chaudhuri, Syed Sadaqat Hussain, Nikhil Kumar Singh, Sandipan Banerjee, Shreyasi Ray, Jyotirmay Kirtania

“…Conclusion Transtracheal lignocaine is more likely to maintain stable hemodynamics during intubation compared to intravenous lignocaine. Trial registration CTRI/2023/06/054125 [Registered on: 19/06/2023]. …”
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Improving automated deep phenotyping through large language models using retrieval-augmented generation by Brandon T. Garcia, Lauren Westerfield, Priya Yelemali, Nikhita Gogate, E. Andres Rivera-Munoz, Haowei Du, Moez Dawood, Angad Jolly, James R. Lupski, Jennifer E. Posey

“…Abstract Background Diagnosing rare genetic disorders relies on precise phenotypic and genotypic analysis, with the Human Phenotype Ontology (HPO) providing a standardized language for capturing clinical phenotypes. …”
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