Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning by Jie Huang, Yanli Zhao, Zhanxiao Tian, Wei Qu, Xia Du, Jie Zhang, Meng Zhang, Yunlong Tan, Zhiren Wang, Shuping Tan

“…In this study, a discriminative model of schizophrenic speech based on deep learning is developed, which combines different emotional stimuli and features. …”
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Identification of Crucial Genes Associated With MYCN‐Driven Neuroblastoma Based on Single‐Cell Analysis and Machine Learning by Jiasi Zhang, Yichen Lei, Yaqin Wang, Wen Yu, Xiaoyan Zhao, Yongbing Zhu, Dedong Zhang, Siying Liu, Aiguo Liu

“…Key genes were then identified using machine learning based random survival forest (RSF) and nomogram analyses. …”
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An innovative model based on machine learning and fuzzy logic for tracking lower limb exercises in stroke patients by Utpal Chandra Das, Ngoc Thien Le, Timporn Vitoonpong, Chalermdej Prapinpairoj, Kawee Anannub, Wasan Akarathanawat, Aurauma Chutinet, Nijasri Charnnarong Suwanwela, Pasu Kaewplung, Surachai Chaitusaney, Watit Benjapolakul

“…The proposed methodology integrates two models: a fuzzy logic rule-based system and a K-Nearest Neighbor(K-NN) machine learning model. …”
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An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

“…To address these challenges, this study proposes a novel deep reinforcement learning (DRL)-based framework, integrating a convolutional neural network (CNN) for hierarchical feature extraction and a recurrent neural network (RNN) for sequential pattern recognition and time-series modeling. …”
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Deep learning-based semantic segmentation for rice yield estimation by analyzing the dynamic change of panicle coverage by Hyeok-Jin Bak, Eun-Ji Kim, Ji-Hyeon Lee, Sungyul Chang, Dongwon Kwon, Woo-Jin Im, Woon-Ha Hwang, Jae-Ki Chang, Nam-Jin Chung, Wan-Gyu Sang

“…Therefore, this study presents a novel temporal framework for rice phenotyping and yield prediction by integrating high-resolution RGB imagery with deep learning-based semantic segmentation.MethodsHigh-resolution RGB images of rice canopies were acquired over two growing seasons. …”
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Machine learning based predictive modeling and risk factors for prolonged SARS-CoV-2 shedding by Yani Zhang, Qiankun Li, Haijun Duan, Liang Tan, Ying Cao, Junxin Chen

“…The results of real-time polymerase chain reaction (RT-PCR) tests determined the duration of viral shedding from the first day of SARS-CoV-2 positivity to the day of SARS-CoV-2 negativity. The extreme gradient boosting (XGBoost) machine learning method was employed to establish a prediction model for prolonged SARS-CoV-2 shedding and analyze significant risk factors. …”
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Deep learning-based automated measurement of hip key angles and auxiliary diagnosis of developmental dysplasia of the hip by Ruixin Li, Xiao Wang, Tianran Li, Beibei Zhang, Xiaoming Liu, Wenhua Li, Qirui Sui

“…The angles of Sharp, Tönnis, and Center edge, as evaluated by the deep learning-based convolutional neural network model, exhibit robust diagnostic performance in identifying both developmental dysplasia of the hip and borderline developmental dysplasia of the hip. …”
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Machine learning‐based model for worsening heart failure risk in Chinese chronic heart failure patients by Ziyi Sun, Zihan Wang, Zhangjun Yun, Xiaoning Sun, Jianguo Lin, Xiaoxiao Zhang, Qingqing Wang, Jinlong Duan, Li Huang, Lin Li, Kuiwu Yao

“…A clinical risk calculation tool was subsequently developed based on these findings. Methods and results This nested case–control study included 200 patients with chronic heart failure (CHF) from the China‐Japan Friendship Hospital (September 2019 to December 2022). …”
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PseudoCell: Hard Negative Mining as Pseudo Labeling for Deep Learning-Based Centroblast Cell Detection by Narongrid Seesawad, Piyalitt Ittichaiwong, Thapanun Sudhawiyangkul, Phattarapong Sawangjai, Peti Thuwajit, Paisarn Boonsakan, Supasan Sripodok, Kanyakorn Veerakanjana, Komgrid Charngkaew, Ananya Pongpaibul, Napat Angkathunyakul, Narit Hnoohom, Sumeth Yuenyong, Chanitra Thuwajit, Theerawit Wilaiprasitporn

“…<italic>Objective:</italic> To address this limitation, we propose <italic>PseudoCell</italic>, an object detection framework for automated centroblast detection in WSI, eliminating the need for extensive pathologist&#x0027;s refined labels. <italic>Methods:</italic> <italic>PseudoCell</italic> leverages a combination of pathologist-provided centroblast labels and pseudo-negative labels generated from undersampled false-positive predictions based on cell morphology features. …”
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Predicting the risk of postoperative avascular necrosis in patients with talar fractures based on an interpretable machine learning model by Jian Zhang, Jian Zhang, Jian Zhang, Jihai Xu, Jihai Xu, Jiapei Yu, Jiapei Yu, Jiapei Yu, Hong Chen, Hong Chen, Xin Hong, Songou Zhang, Xin Wang, Xin Wang, Chengchun Shen, Chengchun Shen, Chengchun Shen

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Integrating Basic Electrocardiogram Interpretation into Advanced Cardiovascular Life Support Stations Through Simulation-Based Learning Among Preclinical Medical Students: Comparin... by Kaophiphat Thammasoon, Sethapong Lertsakulbunlue, Anupong Kantiwong

“…Background: Simulation-based learning (SBL) was introduced at Phramongkutklao College of Medicine to improve electrocardiogram skills within an advanced cardiovascular life support (ACLS) context for pre-clinical students.Objectives: This study compared the perceptions of third-year students and teachers regarding the SBL course.Methods: A cross-sectional study included 96 students and 10 instructors. …”
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A correlation-based binary particle swarm optimization method for feature selection in human activity recognition by Huaijun Wang, Ruomeng Ke, Junhuai Li, Yang An, Kan Wang, Lei Yu

“…However, in some scenarios, the optimization method based on this independence hypothesis results in poor recognition performance. …”
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XGBoost-SHAP-based interpretable diagnostic framework for knee osteoarthritis: a population-based retrospective cohort study by Zijuan Fan, Wenzhu Song, Yan Ke, Ligan Jia, Songyan Li, Jiao Jiao Li, Yuqing Zhang, Jianhao Lin, Bin Wang

“…Methods In this retrospective, population-based cohort study, anonymized questionnaire data was retrieved from the Wu Chuan KOA Study, Inner Mongolia, China. …”
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Exploring the Relationship between Lifelong Learning Components and Evidence- Based Medicine Acceptance among Physiopathology Students at Mazandaran University of Medical Sciences,... by Parinaz Talebi, Nassim Ghahrani, Forouzan Sadeghimahalli, Siavash Moradi

“…Among the components of lifelong learning, only the information search skill subscale showed a significant positive correlation with the evidence-based medicine acceptance score. …”
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Post-COVID-19 Benign Paroxysmal Positional Vertigo by Siniša Maslovara, Andro Košec

“…The symptoms occurred when lying in bed and turning to the right and assuming an upright position. The diagnosis of posterior semicircular canal BPPV (PC-BPPV) was made based on a subjectively and objectively positive right-sided Dix–Hallpike test. …”
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How can ecology-based civics learning media "PKN Ekologi" foster ecological competence in students? by Yoga Ardian Feriandi, Risti Aulia Ulfah

“…PKN Ecology is a digital-based learning media that adopts the principle of augmented Reality. …”
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Can digital economy improve urban ecological development? evidence based on double machine learning analysis by Yuchen Jiang, Lei Li, Yue Xu

“…In response to these problems, the double machine learning method is applied to assess the effect of DE on UED. …”
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Detection of Invasive Species (Siam Weed) Using Drone-Based Imaging and YOLO Deep Learning Model by Deepak Gautam, Zulfadli Mawardi, Louis Elliott, David Loewensteiner, Timothy Whiteside, Simon Brooks

“…We specifically examined the effects of input training images, solar illumination, and model complexity on the model’s detection performance and investigated the sources of false positives. Drone-based RGB images were acquired from four sites in the Townsville region of Queensland to train and test a deep learning model (YOLOv5). …”
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Historical Values and Character Education Based on Batu Urip Local Wisdom as a History Learning Resource by Agus Susilo, Yohana Satinem, Sarkowi Sarkowi

“…The novelty of this study lies in developing interactive digital history learning media based on local values. The study's conclusion confirms that integrating local wisdom in history learning effectively fosters cultural identity, positive character, and students' interest in globalization. …”
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Hotspots and Trends in Social-Emotional Learning Research in China: A Visual Analysis Based on CiteSpace by Sarentonglaga Menghe, Amartuvshin Deleg

“…Based on the CiteSpace visualization analysis method, this study systematically examines the research status, key issues, and development trends in the field of social-emotional learning (SEL) in China from 2012 to 2024. …”
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