Quantifying the tumour vasculature environment from CD-31 immunohistochemistry images of breast cancer using deep learning based semantic segmentation by Tristan Whitmarsh, Wei Cope, Julia Carmona-Bozo, Roido Manavaki, Stephen-John Sammut, Ramona Woitek, Elena Provenzano, Emma L. Brown, Sarah E. Bohndiek, Ferdia A. Gallagher, Carlos Caldas, Fiona J. Gilbert, Florian Markowetz

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Advanced Network Traffic Prediction Using Deep Learning Techniques: A Comparative Study of SVR, LSTM, GRU, and Bidirectional LSTM Models by Wang Yuxin

“…These findings underscore the significant potential of deep learning models, particularly GRU and Bidirectional LSTM, in improving the precision and reliability of network traffic predictions. …”
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Learning to Listen to Non-spoken Voices. Including Young People With Intellectual Disabilities Who are Non-speaking as Primary Participants in Qualitative Research by Beverley Samways, Pauline Heslop

“…The paper concludes with some brief learnings and reflections on the research journey. …”
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Machine learning analysis of pathological images to predict 1-year progression-free survival of immunotherapy in patients with small-cell lung cancer by Hirotaka Matsumoto, Hiroaki Akamatsu, Nobuyuki Yamamoto, Yuki Sato, Daichi Fujimoto, Yoshihiko Taniguchi, Motohiro Tamiya, Yasuhiro Koh, Junya Fukuoka, Hisashi Tanaka, Naoki Furuya, Ryota Shibaki, Tsukasa Nozawa, Akira Sano, Yuka Kitamura, Takashi Kijima, Toshihide Yokoyama, Satoru Miura, Akito Hata, Jun Sugisaka

“…The primary outcome was the mean area under the curve (AUC) of machine learning models in predicting the 1-year PFS.Results We analyzed 100,544 patches of pathological images from 78 patients. …”
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Optimization and modeling of sulfur removal from liquid fuel using carbon-based adsorbents through synergistic application of RSM and machine learning by Karim Maghfour Sarkarabad, Mohsen Shayanmehr, Ahad Ghaemi

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Penerapan Model Pembelajaran Penemuan Terbimbing (Guided Discovery Learning) untuk Meningkatkan Hasil Belajar dan Keterampilan Proses Sains Siswa by Hanis Destrini, Nirwana Nirwana, Indra Sakti

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Enhancing Arabic text-to-speech synthesis for emotional expression in visually impaired individuals using the artificial hummingbird and hybrid deep learning model by Mahmoud M. Selim, Mohammed S. Assiri

“…Natural Language Processing (NLP) and machine learning (ML) techniques provide powerful tools for analysing social media text data, helping detect emotional distress and providing timely support. …”
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Embedding research capacity strengthening in multi-country studies in low-and middle-income countries: learnings from sexual and reproductive health research by Anne M. Khisa, Hesborn Wao, Vanessa Brizuela, Rachidatou Compaoré, Adama Baguiya, Alejandra López Gómez, Mercedes Bonet, Seni Kouanda, Anna Thorson, Evelyn Gitau

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RETRACTED ARTICLE: A prospective diagnostic model for breast cancer utilizing machine learning to examine the molecular immune infiltrate in HSPB6 by Lizhe Wang, Yu Wang, Yueyang Li, Li Zhou, Sihan Liu, Yongyi Cao, Yuzhi Li, Shenting Liu, Jiahui Du, Jin Wang, Ting Zhu

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Model Analisis Aktivitas Tutor Dalam Learning Management System Berdasarkan Data Log Menggunakan K-Means Dan Deteksi Outlier by Agusriandi Agusriandi, Elihami Elihami, Irman Syarif, Ita Sarmita Samad

“…Another fact showed who were tutors rarely provided feedback both in narrative and assessment when giving assignments so that the tutors in doing online learning has not met the standard process in online learning. …”
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An explainable deep learning model for diabetic foot ulcer classification using swin transformer and efficient multi-scale attention-driven network by R. Karthik, Armaano Ajay, Anshika Jhalani, Kruthik Ballari, Suganthi K

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Examining the role of ClassPoint tool in shaping EFL students' perceived E-learning experiences: A social cognitive theory perspective by Huma Akram, Abbas Hussein Abdelrady

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Forecasting Weather using Deep Learning from the Meteorological Stations Data : A Study of Different Meteorological Stations in Kaski District, Nepal by Supath Dhital, Kapil Lamsal, Sulav Shrestha, Umesh Bhurtyal

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Enhancing Transient Stability of DFIG-Based Wind Turbine Systems Using Deep Learning-Controlled Resistance-Based Fault Current Limiters by Yaoying Wang

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Insights into the contribution of multiple factors on Ixodes ricinus abundance across Europe spanning 20 years using different machine learning algorithms by Samantha Lansdell, Abin Zorto, Misaki Seto, Edessa Negera, Saeed Sharif, Sally Cutler

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Optimizing chickpea yield prediction under wilt disease through synergistic integration of biophysical and image parameters using machine learning models by RN Singh, P. Krishnan, C. Bharadwaj, Sonam Sah, B. Das

“…Yield reductions of 44-69% were observed in susceptible genotypes. Machine learning models were able to give accurate early yield predictions. …”
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Over-Dimension and Over-Load (ODOL) truck in highways: Prevalence and modeling intention to operate ODOL truck, lesson learned from Indonesia by Ari Widyanti, Justin Mulya Gananda, Titah Yudhistira, Widyarini Weningtyas, Ludfi Pratiwi Bowo, Sinung Nugoroho

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Novel Unsupervised Machine Learning Method for Identifying Falling from Height Hazards in Building Information Models through Path Simulation Sampling by Yu Yan, Shen Zhang, Xingyu Wang, Xuechun Li

“…To address this issue, we proposed a new identification method for FFH risk points by incorporating BIM, path simulation, and machine learning techniques. Our approach, based on the likelihood exposure consequence criterion, efficiently identified and prioritized hazardous FFH risk points. …”
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PhyIndBC: Development of a machine learning tool for screening of potential breast cancer inhibitors from phytochemicalsGitHub by Agneesh Pratim Das, Subhash M. Agarwal

Subjects: “…Machine learning…”
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Analisis Sentimen E-Learning X Terhadap Antarmuka Pengguna Menggunakan Kombinasi Multinomial Naive Bayes Dan Pendekatan Design Thinking by Baenil Huda, Irwan Sembiring, Iwan Setiawan, Danny Manongga, Hindriyanto Dwi Purnomo, Hendry Hendry, Ahmad Fauzi, April Lia Hananto, Tukino Tukino

“… Penelitian ini bertujuan untuk menganalisis sentimen pengguna terhadap antarmuka e-learning X menggunakan kombinasi Multinomial Naive Bayes dan pendekatan Design Thinking. …”
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