PATHOLOGY TEACHING LEARNING METHODS – STUDENTS’ PERCEPTION AND FEEDBACK by Dr. Fauzia Sadiq, Dr. Asad Amin, Taha Tariq, Javeria Ahmed, Azan Ali, Dr. Shazia I Rasa

“…Monitoring the teaching and learning methods of the facilitators is necessary for departmental quality improvement.  …”
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Deep Learning Methods in Soft Robotics: Architectures and Applications by Tomáš Čakurda, Monika Trojanová, Pavlo Pomin, Alexander Hošovský

“…The area of soft robotics has been subject to intense research efforts in the past two decades and constitutes a paradigm for advanced machine design in future robotic applications. However, standard methods for industrial robotics may be difficult to apply when analyzing soft robots. …”
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Machine learning methods in psychiatry: a brief introduction by Hongyue Wang, Bokai Wang, Xin M Tu, Changyong Feng, Zhirou Zhou, Tsung-Chin Wu

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Machine Learning-Driven Methods for Nanobody Affinity Prediction by Hua Feng, Xuefeng Sun, Ning Li, Qian Xu, Qin Li, Shenli Zhang, Guangxu Xing, Gaiping Zhang, Fangyu Wang

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Innovative Learning Methods and Design Strategies of Library Buildings by Seyla KOÇAK, Selin YILDIZ

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Deep Reinforcement Learning: A Chronological Overview and Methods by Juan Terven

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Prediction of the Costs of Forwarding Contracts with Machine Learning Methods by Stanisław Kaźmierczak

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Prospects for the application of active learning methods in modern education by Tunzala Verdiyeva

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Application of Machine Learning Methods for Gravity Anomaly Prediction by Katima Zhanakulova, Bakhberde Adebiyet, Elmira Orynbassarova, Ainur Yerzhankyzy, Khaini-Kamal Kassymkanova, Roza Abdykalykova, Maksat Zakariya

“…This study evaluates machine learning (ML) methods—Support Vector Regression (SVR), Gaussian Process Regression (GPR), and Ensemble of Trees—for predicting gravity anomalies in southeastern Kazakhstan and compares their effectiveness with traditional Kriging interpolation. …”
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Machine Learning Methods for Weather Forecasting: A Survey by Huijun Zhang, Yaxin Liu, Chongyu Zhang, Ningyun Li

“…Research on specific tasks such as global weather forecasting, downscaling, extreme weather prediction, and how to combine machine learning methods with physical principles are very active in the current field. …”
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Temporal and spatial self supervised learning methods for electrocardiograms by Wenping Chen, Huibin Wang, Lili Zhang, Min Zhang

“…Abstract The limited availability of labeled ECG data restricts the application of supervised deep learning methods in ECG detection. Although existing self-supervised learning approaches have been applied to ECG analysis, they are predominantly image-based, which limits their effectiveness. …”
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Introduction to deep learning methods for multi‐species predictions by Yuqing Hu, Sara Si‐Moussi, Wilfried Thuiller

“…This paper explores the potential of deep learning methods to overcome these challenges and provide more accurate multi‐species predictions. …”
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Detection of child depression using machine learning methods. by Umme Marzia Haque, Enamul Kabir, Rasheda Khanam

“…As a result, our objective is to 1) create a model that can predict depression in children and adolescents aged 4-17 years old, 2) evaluate the results of ML algorithms to determine which one outperforms the others and 3) associate with the related issues of family activities and socioeconomic difficulties that contribute to depression.<h4>Methods</h4>The YMM, the second Australian Child and Adolescent Survey of Mental Health and Wellbeing 2013-14 has been used as data source in this research. …”
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Machine Learning Methods in Customer Segmentation and Recommendation Systems by Guo Yiran

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Historical Perspectives in Volatility Forecasting Methods with Machine Learning by Zhiang Qiu, Clemens Kownatzki, Fabien Scalzo, Eun Sang Cha

“…While recent works show promising advances in machine learning and artificial intelligence for volatility forecasting, a comprehensive assessment of current statistical and learning-based methods is lacking. …”
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Housing Value Forecasting Based on Machine Learning Methods by Jingyi Mu, Fang Wu, Aihua Zhang

“…In this paper, on the basis of the actual data, the values of Boston suburb houses are forecast by several machine learning methods. According to the predictions, the government and developers can make decisions about whether developing the real estate on corresponding regions or not. …”
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INNOVATION METHODS FOR LEARNING IN CONTEXT OF SCHOOL EDUCATION GOALS. by M.I. Savchenko, N. I. Lytvynenko

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Survey of text classification methods based on deep learning by Sijia DU, Haining YU, Hongli ZHANG

“…Text classification is a research hot spot in the field of natural language processing,which is mainly used in public opinion detection,news classification and other fields.In recent years,artificial neural networks has good performance in many tasks of natural language processing,the application of neural network technology to text classification has also made many achievements.In the field of text classification based on deep learning,numerical representation of text and deep-learning-based text classification are two main research directions.The important technology of word embedding in text representation and the implementation principle and research status of deep learning method applied in text classification were systematically analyzed and summarized.And the shortcomings and the development trend of text classification methods in view of the current technology development were analyzed.…”
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Comparison of Machine Learning Methods for Calories Burn Prediction by Alfred Tan Jing Sheng, Zarina Che Embi, Noramiza Hashim

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Prediction of Rheological Parameters of Polymers by Machine Learning Methods by T. N. Kondratieva, A. S. Chepurnenko

“…All polymer materials and composites based on them are characterized by pronounced rheological properties, the prediction of which is one of the most critical tasks of polymer mechanics. Machine learning methods open up great opportunities in predicting the rheological parameters of polymers. …”
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