Retraction: Advanced machine learning-guided optimization platform for high-yield soluble expression of Pseudomonas aeruginosa exotoxin A in engineered Escherichia coli strains

Deep learning approaches show promise for predicting childhood malnutrition: A comparative study with traditional machine learning methods using survey data

Deepak Bastola, Yang Li

Childhood malnutrition remains a major public health concern in Nepal and other low-resource settings, while conventional case-finding approaches are labor-intensive and frequently unavailable in remote areas. This study provides one of the first applications of machine learning…Read more

Retraction: Convolutional neural network model by deep learning and teaching robot in keyboard musical instrument teaching

Expression of Concern: Classification of white blood cells (leucocytes) from blood smear imagery using machine and deep learning models: A global scoping review

Development of a predictive model for PM2.5 over the greater Athens metropolitan area, Greece, at a 1 km by 1 km grid using satellite measurements and machine learning methods

Seyong Chang, Evangelia Samoli, Evangelia Diapouli, Konstantina Dimakopoulou, Barrak Alahmad, Petros Koutrakis

Background Ambient PM 2.5 exposure is strongly associated with adverse health effects, including all-cause mortality. However, the lack of monitoring networks globally necessitates a better understanding of the spatiotemporal distribution of near-surface PM 2.5 pollution. While g…Read more

Data-driven prediction and thermodynamic performance assessment of industrial cooling towers using advanced machine learning algorithms

Syed Rehman Jamil, Adeel Shehzad, Muhammad Usman, Muhammad Mujtaba Abbas, Omama Zainab Qaisrani, Muhammad Wajid Saleem, et al.

Cooling towers are an important part of the thermal system in industries, where they are used to remove unwanted heat and help maintain the proper performance of the machines. Four machine learning algorithms, namely random forest, support vector machine (SVM), decision tree, and…Read more

Platform workers not by chance: Exploring the digital labour markets in Italy with machine learning and explainable AI

Clara Punzi, Valeria Cirillo, Dario Guarascio, Roberto Pellungrini, Fosca Giannotti

Digital labour platforms are reshaping the world of work across a wide range of sectors, offering greater flexibility and accessibility than traditional labour markets. However, existing research suggests that platform work is often associated with low-quality working conditions…Read more