Text-to-Image Synthesis With Generative Models: Methods, Datasets, Performance Metrics, Challenges, and Future Direction by Sarah K. Alhabeeb, Amal A. Al-Shargabi

“…Text-to-image synthesis, the process of turning words into images, opens up a world of creative possibilities, and meets the growing need for engaging visual experiences in a world that is becoming more image-based. As machine learning capabilities expanded, the area progressed from simple tools and systems to robust deep learning models that can automatically generate realistic images from textual inputs. …”
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Comprehensive Evaluation of Phenotypic Traits in Vegetable Faba Bean (Vicia faba L.) Germplasms Based on Multivariate Statistical Methods by Linlin Wang, Yangmin Zhong, Ruifang Ma, Hanmei Li, Tingfu Liu

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Majority Voting Ensemble of Deep CNNs for Robust MRI-Based Brain Tumor Classification by Kuo-Ying Liu, Nan-Han Lu, Yung-Hui Huang, Akari Matsushima, Koharu Kimura, Takahide Okamoto, Tai-Been Chen

“…Performance was assessed using accuracy, Kappa coefficient, true positive rate, precision, confusion matrix, and ROC curves. …”
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Satisfaction and Self-Confidence of Moroccan Nursing Students in Simulation-Based Learning and Their Associations with Simulation Design Characteristics and Educational Practices by Hicham Blaak, Abdelmajid Lkoul, Hayat Iziki, Abdelhadi El Haddaouy, Ahmed Kharabch, Rachid Razine, Lahcen Belyamani, Majdouline Obtel

“…Furthermore, various learning methods (B = 0.112, <i>p</i> = 0.037, 95% CI [0.007; 0.217]) and objectives/information clarity (B = 0.175, <i>p</i> = 0.040, 95% CI [0.008; 0.342]) had a significant positive effect on satisfaction. …”
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Panoramic radiographic features for machine learning based detection of mandibular third molar root and inferior alveolar canal contact by A. Canberk Ulusoy, Tuğçe Toprak, M. Alper Selver, Pelin Güneri, Betül İlhan

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Prediction of recurrence after surgery for pituitary adenoma using machine learning- based models: systematic review and meta-analysis by Ibrahim Mohammadzadeh, Bardia Hajikarimloo, Behnaz Niroomand, Nasira Faizi, Pooya Eini, Mohammad Amin Habibi, Alireza Mohseni, Mohammadmahdi Sabahi, Abdulrahman Albakr, Michael Karsy, Hamid Borghei-Razavi

“…Abstract Background Predicting pituitary adenoma (PA) recurrence after surgical resection is critical for guiding clinical decision-making, and machine learning (ML) based models show great promise in improving the accuracy of these predictions. …”
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Research on the application of network security defence in database security services based on deep learning integrated with big data analytics by Feilu Hang, Linjiang Xie, Zhenhong Zhang, Wei Guo, Hanruo Li

“…Additionally, an Artificial Neural Network (ANN)-based Deep Learning (DL) method for Anomaly Detection (AD) is presented in this work. …”
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Meta-analysis of machine learning models for the diagnosis of central precocious puberty based on clinical, hormonal (laboratory) and imaging data by Yilin Chen, Xueqin Huang, Lu Tian

“…With the widespread application of artificial intelligence in medicine, some studies have utilized clinical, hormonal (laboratory) and imaging data-based machine learning (ML) models to identify CPP. …”
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LI-RADS-based hepatocellular carcinoma risk mapping using contrast-enhanced MRI and self-configuring deep learning by Róbert Stollmayer, Selda Güven, Christian Marcel Heidt, Kai Schlamp, Pál Novák Kaposi, Oyunbileg von Stackelberg, Hans-Ulrich Kauczor, Miriam Klauss, Philipp Mayer

“…These limitations could potentially be alleviated using recent deep learning-based segmentation and classification methods such as nnU-Net. …”
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Mixed-methods feasibility outcomes for a novel ACT-based video game ‘ACTing Minds’ to support mental health by Darren J Edwards, Andrew H Kemp, Tom C Gordon

“…Objectives To determine the feasibility and acceptability of ‘ACTing Minds’, a novel single-player adventure video game based on acceptance and commitment therapy (ACT).Design A single-arm, mixed-methods repeated measures feasibility study.Setting Intervention and questionnaires were completed at home by participants. …”
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PENERAPAN INQUIRY BASED LEARNING UNTUK MENGETAHUI RESPON BELAJAR SISWA PADA MATERI KONSEP DAN PENGELOLAAN KOPERASI by Heru Kusmaryono, Rokhis Setiawati

“…The results showed that students gave<br />positive responses toward the application of Inquiry Based Learning method since<br />students’ responses were very high at 85.51%.…”
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Application of Machine Learning Models for the Early Detection of Metritis in Dairy Cows Based on Physiological, Behavioural and Milk Quality Indicators by Karina Džermeikaitė, Justina Krištolaitytė, Ramūnas Antanaitis

“…Models were evaluated based on accuracy, sensitivity, specificity, positive and negative predictive values (PPV, NPV), area under the receiver operating characteristic (ROC) area under the curve (AUC), and Matthews correlation coefficient (MCC). …”
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THE CORRELATION BETWEEN LEARNING STRATEGIES AND STUDENTS’ WRITING ACHIEVEMENT THROUGH PROCESS-BASED APPROACH IN THE THINK-PAIR-SHARE TECHNIQUE by Nirmala Bestari, Agustinus Bambang Setiyadi, Flora Flora

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A machine learning model accurately identifies glycogen storage disease Ia patients based on plasma acylcarnitine profiles by Joost Groen, Bas M. de Haan, Ruben J. Overduin, Andrea B. Haijer-Schreuder, Terry GJ Derks, M. Rebecca Heiner-Fokkema

“…As GSD Ia patients demonstrate altered lipid metabolism and mitochondrial fatty acid oxidation, we built a machine learning model to identify GSD Ia patients based on plasma acylcarnitine profiles. …”
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Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines by Qin Li, Nan Lin, Zuheng Wang, Yuexi Chen, Yuli Xie, Xuemei Wang, Jirui Tang, Yuling Xu, Min Xu, Na Lu, Yiqian Huang, Jiamin Luo, Zhenfang Liu, Li Jing

“…This study aimed to analyze pathogen distribution, drug-resistance patterns and develop a novel predictive model for 30-day mortality in HM patients with BSIs. Methods A retrospective analysis of 231 HM patients with positive blood cultures was conducted. …”
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Development of Machine Learning–Based Risk Prediction Models to Predict Rapid Weight Gain in Infants: Analysis of Seven Cohorts by Miaobing Zheng, Yuxin Zhang, Rachel A Laws, Peter Vuillermin, Jodie Dodd, Li Ming Wen, Louise A Baur, Rachael Taylor, Rebecca Byrne, Anne-Louise Ponsonby, Kylie D Hesketh

“…MethodsData from 7 Australian and New Zealand cohorts were pooled for risk model development and validation (n=5233). …”
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Development and Evaluation of a Virtual Reality-Based Mandarin Language Learning System Enriched with Chinese Cultural and Geographical Contexts by Rizaldi Eko Prasetyo, Esther Irawati Setiawan, Joan Santoso

“…After testing using this method, the results obtained were an increase in learning outcomes of 22% from learning that initially used conventional learning to learning based on Virtual Reality technology. …”
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Development of Educational Game-assisted Accounting Learning Media based on Role-Playing Game to Improve Students' Analytical Abilities by Dian Novianti Sitompul, Faisal Rahman Dongoran, Harningsih Fitri

“…This study aims to develop educational game-assisted accounting learning media based on role playing game to improve students' analytical abilities. …”
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Machine learning-based prediction of carotid intima–media thickness progression: a three-year prospective cohort study by An Zhou, Kui Chen, Kui Chen, Yonghui Wei, Qu Ye, Qu Ye, Yuanming Xiao, Rong Shi, Jiangang Wang, Wei-Dong Li

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Effectiveness of Radiomics-Based Machine Learning Models in Differentiating Pancreatitis and Pancreatic Ductal Adenocarcinoma: Systematic Review and Meta-Analysis by Lechang Zhang, Dewei Li, Tong Su, Tong Xiao, Shulei Zhao

“…Some investigators have explored radiomics-based machine learning (ML) models for distinguishing PDAC from MFP. …”
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