Development of Deep Learning Models for Real-Time Thoracic Ultrasound Image Interpretation by Austin J. Ruiz, Sofia I. Hernández Torres, Eric J. Snider

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Precision forecasting for hybrid energy systems using five deep learning algorithms for meteorological parameter prediction by Ceren Ceylan, Zehra Yumurtacı

“…In addition, most of the research uses the same algorithmic solution to all the meteorological parameters without identifying parameter-specific optimization potential, and recent research is verified on actual future time steps instead of historical train-test split. …”
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Dye-cleaning prediction with a variant of nature-inspired algorithms coupled with extreme gradient boosting by Tiyasha Tiyasha, Chijioke Elijah Onu, Mohamed A. Ismail, Rama Rao Karri, Abdelfattah Amari, Vinay Kumar, Suraj Kumar Bhagat

“…Abstract This research proposes the use of hybrid machine learning methods to mimic dye removal efficiency. …”
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Kernel to computation: identifying optimal feature set for red rice classification by Suma D, Narendra V G, Darshan Holla M, Shreyas, Raviraja Holla M

“…While existing research focuses extensively on white rice classification with readily available datasets, automated classification of red rice varieties remains largely unexplored with no publicly available datasets, creating a significant research gap in agricultural image processing applications. …”
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Optimizing machine learning algorithms for diabetes data: A metaheuristic approach to balancing and tuning classifiers parameters by Hauwau Abdulrahman Aliyu, Ibrahim Olawale Muritala, Habeeb Bello-Salau, Salisu Mohammed, Adeiza James Onumanyi, Ore-Ofe Ajayi

“…To address these issues, this research focuses on devising a methodological metaheuristic optimization, a machine learning algorithm tailored for diabetes data balancing, and classifier hyperparameter tuning. …”
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Object Detection using YOLOv8 : A Systematic Review by Nugraha Asthra Megantara, Ema Utami

“…This study is expected to be an important reference for researchers and practitioners in developing YOLOv8-based object detection models for real-world applications.…”
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IMPROVING PREDICTION OF DEPRESSION AN ANALYTICAL COMPARISON BETWEEN HYBRID AI, MACHINE LEARNING AND DEEP LEARNING APPROACHES by Kanchapogu Naga Raju, Sachi Nandan Mohanty

“…Through the use of a comprehensive hyperparameter refining step, our research route was supported, which ensured that the ability of each model to accurately forecast was improved. …”
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Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients by Aref Andishgar, Sina Bazmi, Kamran B. Lankarani, Seyed Alireza Taghavi, Mohammad Hadi Imanieh, Gholamreza Sivandzadeh, Samira Saeian, Nazanin Dadashpour, Alireza Shamsaeefar, Mahdi Ravankhah, Hamed Nikoupour Deylami, Reza Tabrizi, Mohammad Hossein Imanieh

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Radiomics-based machine learning role in differential diagnosis between small renal oncocytoma and clear cells carcinoma on contrast-enhanced CT: A pilot study by Roberto Francischello, Salvatore Claudio Fanni, Martina Chiellini, Maria Febi, Giorgio Pomara, Claudio Bandini, Lorenzo Faggioni, Riccardo Lencioni, Emanuele Neri, Dania Cioni

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Potential of machine learning methods in operational risk stratification in patients with coronary artery disease scheduled for coronary bypass surgery by E. Z. Golukhova, M. A. Keren, T. V. Zavalikhina, N. I. Bulaeva, D. S. Akatov, I. Yu. Sigaev, K. B. Yakhyaeva, D. A. Kolesnikov

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Implementing a deep learning model for defect classification in Thai Arabica green coffee beans by Sujitra Arwatchananukul, Dan Xu, Phasit Charoenkwan, Sai Aung Moon, Rattapon Saengrayap

“…However, the Thai coffee business must ensure consistent quality standards and is currently heavily dependent on manual labor, to first identify, and then remove substandard unroasted coffee beans. This research developed a classification model based on a Convolutional Neural Network to detect 17 types of defects in green coffee beans. …”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…Improved nutrient prediction is also advantageous from an environmental perspective, as it reduces the need for superfluous fertilizer applications and prevents discharge caused by excess fertilizers. Further research will be conducted on reinforcement learning for adaptive searching, multi-objective optimization, and the facilitation of hyperparameter tuning to develop more precise models for predicting soil nutrients.…”
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SGO enhanced random forest and extreme gradient boosting framework for heart disease prediction by Anima Naik, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…Both models are further optimized through hyperparameter tuning using the Social Group Optimization (SGO) algorithm. …”
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Achieving high-accuracy skin cancer classification with deep learning optimized by ant colony algorithm by Amany M. Sarhan, Hesham A. Ali, Shady Yasser, Mohamed Gobara, Ahmed A. Kandil, Ghada Sherif, Esraa Moustafa

“…Additionally, this framework provides a foundation for future research in applying deep learning to medical image analysis and healthcare diagnostics.…”
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Beyond labels: determining the true type of blood gas samples in ICU patients through supervised machine learning by Johan Helleberg, Anna Sundelin, Johan Mårtensson, Olav Rooyackers, Ragnar Thobaben

“…This approach shows promise for improving the accuracy of research and clinical applications relying on blood gas data.…”
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Exploration and Exploitation Mechanism in Pairwise Test Case Generation: A Systematic Literature Review by Muhammad Sabo Yahaya, Ahmad Sobri B. Hashim, Abdullateef Oluwagbemiga Balogun, Aminu Aminu Muazu, Fatima Sabo Usman, Dahiru Adamu Aliyu, Abdullahi Uwaisu Muhammad

“…This review offers valuable insights into advancing Software testing methodologies and presents recommendations for future research to improve efficiency, scalability, and fault detection in pairwise testing.…”
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Machine learning optimization of environmental factors influencing biomass and nutritional composition in local algal species by Aisha Khan, Saleem Ullah, Rifat Ali, Mahwish Rehman, Said Moshawih, Khang Wen Goh, Long Chiau Ming, Lai Ti Gew

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Predictive analytics of complex healthcare systems using deep learning based disease diagnosis model by Muhammad Kashif Saeed, Alanoud Al Mazroa, Bandar M. Alghamdi, Fouad Shoie Alallah, Abdulrhman Alshareef, Ahmed Mahmud

“…Thus, the recognition and classification of LCC are among the cutting-edge research regions, particularly in the biological healthcare and medical fields. …”
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Explainable machine learning and feature engineering applied to nanoindentation data by C.O.W. Trost, S. Žák, S. Schaffer, L. Walch, J. Zitz, T. Klünsner, H. Leitner, L. Exl, M.J. Cordill

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Using ML techniques to predict extubation outcomes for patients with central nervous system injuries in the Yun-Gui Plateau by Zi-han Chen, Hao-tian Wu, Zhou Yao, Qian Liu, Hong-mei Zhang, Xiao-chen Li, Li-qing Yao, Xue Yang

“…This study evaluated the effectiveness of conventional models for predicting extubation outcomes and analyzed the factors influencing extubation results at high altitudes, laying the groundwork for clinical use and future research. Nevertheless, further research will see advantages in using multicentric approaches and broadening clinical indicators.…”
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