Abstract: As a follow-up to the first IEEE Transactions on Medical Imaging (TMI) special issue on the theme of ... motivation for the development of network-based, data-driven, and learning-oriented ...

A study reveals machine learning algorithms can predict compressive strength in concrete with waste glass powder, enhancing ...

Eye-Tracking, Machine Learning, Distance Learning, Online Learning, E-Learning, Bibliometric Analysis Share and Cite: Ayan, E ...

Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...

In an effort to equip aspiring technologists and researchers with cutting-edge skills, Jamia Millia Islamia (JMI) has ...

Next, you’ll dive into the world of causal effect estimation, consistently progressing towards modern machine learning methods. Step-by-step, you’ll discover Python causal ecosystem and harness the ...

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical ...

In this paper, we propose an approach based on One-Class Support Vector Machine (SVM) to solve MIL problem in the region-based Content Based Image ... to the learning process. Performance is evaluated ...

aArtificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA bDepartment of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer ...