The application of machine learning (ML) to address population health challenges has received much less attention than its application in the clinical setting. One such challenge is addressing disparities in early childhood cognitive development-a co...
Journal of medical engineering & technology
Jun 9, 2022
The technological inference in procedures applied to healthcare is frequently investigated in order to understand the real contribution to decision-making and clinical improvement. In this context, the theoretical field of machine learning has suitab...
Biomechanical simulation enables medical researchers to study complex mechano-biological conditions, although for soft tissue modeling, it may apply highly nonlinear multi-physics theories commonly implemented by expensive finite element (FE) solvers...
Although groundwater (GW) potential zoning can be beneficial for water management, it is currently lacking in several places around the world, including Pakistan's Quetta Valley. Due to ever increasing population growth and industrial development, GW...
Karyotyping is an examination that helps in detecting chromosomal abnormalities. Chromosome analysis is a very challenging task which requires various steps to obtain a karyotype. The challenges associated with chromosome analysis are overlapping and...
The success behind Machine Learning (ML) methods has largely been attributed to the quality and quantity of the available data which can spread across multiple owners. A Federated Learning (FL) from distributed datasets often provides a reliable solu...
Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential ...
With time, textual data is proliferating, primarily through the publications of articles. With this rapid increase in textual data, anonymous content is also increasing. Researchers are searching for alternative strategies to identify the author of a...
Data-driven models based on deep learning have led to tremendous breakthroughs in classical computer vision tasks and have recently made their way into natural sciences. However, the absence of domain knowledge in their inherent design significantly ...
We propose an approach to learn effective evolution equations for large systems of interacting agents. This is demonstrated on two examples, a well-studied system of coupled normal form oscillators and a biologically motivated example of coupled Hodg...
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