Classification of psychiatry clinical notes by diagnosis: a deep learning and machine learning approach by Sergio Rubio-Martín, María Teresa García-Ordás, Antonio Serrano-García, Clara Margarita Franch-Pato, Arturo Crespo-Álvaro, José Alberto Benítez-Andrades

“…The only exception was SMOTE, which showed a positive effect specifically with Bidirectional Encoder Representations from Transformers (BERT)-based models. …”
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The research on enhancing LA estimation accuracy across domains for small sample data based on data augmentation and data transfer integration optimization system by Ai-Dong Wang, Rui-Jie Li, Xiang-Qian Feng, Zi-Qiu Li, Wei-Yuan Hong, Hua-Xing Wu, Dan-Ying Wang, Song Chen

“…Methods: This research utilizes canopy image data acquired from the 2023–2024 rice full-cycle multi-view RGB imaging system (with dual front and side camera positions). …”
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Point Cloud-Based Proactive Link Quality Prediction for Millimeter-Wave Communications by Shoki Ohta, Takayuki Nishio, Riichi Kudo, Kahoko Takahashi, Hisashi Nagata

“…Previous studies have proposed machine learning-based methods to predict received signal strength for future time periods using time series of depth images to mitigate the line-of-sight (LOS) path blockage by pedestrians in mmWave communication. …”
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TFNet: point cloud Semantic Segmentation Network based on Triple feature extraction by Yong Li, Falin Chen, Qi Lin, Zhen Li, Dongxu Gao, Jingchao Yang

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Steel Roll Eye Pose Detection Based on Binocular Vision and Mask R-CNN by Xuwu Su, Jie Wang, Yifan Wang, Daode Zhang

“…To achieve automation at the inner corner guard installation station in a steel coil packaging production line and enable automatic docking and installation of the inner corner guard after eye position detection, this paper proposes a binocular vision method based on deep learning for eye position detection of steel coil rolls. …”
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Bolt Loosening and Preload Loss Detection Technology Based on Machine Vision by Zhiqiang Shang, Xi Qin, Zejun Zhang, Hongtao Jiang

“…This study proposes a high-precision bolt key point positioning and recognition method based on deep learning to address the high cost, low efficiency, and poor safety of current bolt loosening identification methods. …”
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Learning Transversus Abdominis Activation in Older Adults with Chronic Low Back Pain Using an Ultrasound-Based Wearable: A Randomized Controlled Pilot Study by Luis Perotti, Oskar Stamm, Hannah Strohm, Jürgen Jenne, Marc Fournelle, Nils Lahmann, Ursula Müller-Werdan

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Validation of a deep learning–based AI system for HER2-targeted breast cancer assessment using ultrasound imaging in a clinical setting by Kathryn Malherbe

“…BackgroundThis study evaluates the performance of a deep learning–based artificial intelligence (AI) system developed under the Stradexa (a branded form of doxorubicin used regionally in South Africa) initiative, designed for real-time risk stratification and treatment monitoring in HER2-positive breast cancer. …”
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SHIVA-CMB: a deep-learning-based robust cerebral microbleed segmentation tool trained on multi-source T2*GRE- and susceptibility-weighted MRI by Ami Tsuchida, Martin Goubet, Philippe Boutinaud, Iana Astafeva, Victor Nozais, Pierre-Yves Hervé, Thomas Tourdias, Stéphanie Debette, Marc Joliot

“…An increasing number of automated CMB detection methods being proposed are based on supervised deep learning (DL). …”
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Integrating user demographic parameters for mouse behavioral biometric-based assessment fraud detection in online education platforms by Aditya Subash, Insu Song, Ickjai Lee, Kyungmi Lee

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The Most Effective Interventions for Classification Model Development to Predict Chat Outcomes Based on the Conversation Content in Online Suicide Prevention Chats: Machine Learnin... by Salim Salmi, Saskia Mérelle, Renske Gilissen, Rob van der Mei, Sandjai Bhulai

“…ResultsAccording to the machine learning model, helpers’ positive affirmations and expressing involvement contributed to improved scores of the help seekers. …”
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IMPLEMENTING EDUCATIONAL DIGITAL GAMES INTO TEACHER-TRAINING PRO- GRAMMES: A CASE-STUDY BASED ON GERMAN EXPERIENCE by Amélia Lopes, Anasatasiia Tokarieva, Іnna Chyzhykova

“…The work is also based on a constructivist theory of learning that emphasises how games generate meaning and reflect broader social and cultural discourses and a participatory seminar organisation, based on the reflective exploration of games. …”
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An retrospective study on the effects of deep learning model-based optimization emergency nursing on treatment compliance and curative effect of patients with acute left heart fail... by Qian Dai, Jing Huang, Hui Huang, Lin Song

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Teaching opportunities for anamnesis interviews through AI based teaching role plays: a survey with online learning students from health study programs by Katharina Rädel-Ablass, Klaus Schliz, Cornelia Schlick, Benjamin Meindl, Sandra Pahr-Hosbach, Hanna Schwendemann, Stephanie Rupp, Marion Roddewig, Claudia Miersch

“…Abstract Background This study presents a novel approach to educational role-playing through an AI-based bot, leveraging GPT-4 to simulate anamnesis interviews in various learning scenarios. …”
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Family History of Hypertension Predicts Thyroid Cancer Risk in Women: A Population‐Based Cross‐Sectional Study With Integrative Machine Learning and Genomic Analyses by Zijin Wang, Yanhui Lin, Fanke Meng, Yuxin Sun, Ziran Zhang, Tong Wu, Min Fu, Fanye Wu, Zhengran Li, Zejun Chen

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Evaluation of a Machine Learning Model Based on Laboratory Parameters for the Prediction of Influenza A and B in Chongqing, China: Multicenter Model Development and Validation Stud... by Weiwei Hu, Yulong Liu, Jian Dong, Xuelian Peng, Chunyan Yang, Honglin Wang, Yong Chen, Shan Shi, Jin Li

“…ObjectiveThis study aimed to develop a machine learning model using 24 routine blood parameters to predict influenza A and B infections and validate a deployable diagnostic tool for low-resource clinical settings. …”
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Supervised Machine Learning Models for Predicting Sepsis-Associated Liver Injury in Patients With Sepsis: Development and Validation Study Based on a Multicenter Cohort Study by Jingchao Lei, Jia Zhai, Yao Zhang, Jing Qi, Chuanzheng Sun

“…Traditional diagnostic tools are often limited, and machine learning techniques offer promising solutions for predicting adverse outcomes in patients with sepsis. …”
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Data augmentation based on the WGAN-GP with data block to enhance the prediction of genes associated with RNA methylation pathways by Tuo Jiang, Cong Shen, Pingjian Ding, Lingyun Luo

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Machine Learning in the National Economy by Azamjon A. Usmonov

“…Thus, the use of modern machine learning methods in economics allows us to obtain accurate forecasts, identify patterns in economic data, and make strategic decisions based on objective analysis.Conclusion. …”
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A network-based approach to discover diagnostic metabolite markers associated with depressive features for major depressive disorder by Yuzhen Zheng, Duan Zeng, Ying Tian, Siyuan Li, Shen He, Huafang Li, Huafang Li, Huafang Li

“…Diagnostic models were developed based on the identified hub metabolites, using six supervised machine-learning algorithms. …”
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