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COLUMBUS, Ohio, April 22, 2024 Researchers at Ohio State University are pioneering the field of imageomics. Founded on advancements in machine learning and computer vision, the researchers are using imageomics to explore fundamental questions about biological processes by combining images of living organisms with computer-enabled analysis.

The field was the subject of a presentation by Wei-Lun Chao, an investigator at Ohio State Universitys Imageomics Institute and a distinguished assistant professor, during the annual meeting of the American Association for the Advancement of Science (AAAS). The presentation focused on the fields application for micro- to macro-level problems by turning research questions into computable problems.

Nowadays we have many rapid advances in machine learning and computer vision techniques, said Chao. If we use them appropriately, they could really help scientists solve critical but laborious problems.

Traditional methods for image classification with trait detection require a huge amount of human annotation, but our method doesnt, said Chao. We were inspired to develop our algorithm through how biologists and ecologists look for traits to differentiate various species of biological organisms.

Chao said that one of the most challenging parts of fostering imageomics research is integrating different parts of scientific culture to collect enough data and form novel scientific hypotheses from them. That being said, he is enthusiastic about its potential to allow for the natural world to be seen within multiple fields.

What we really want is for AI to have strong integration with scientific knowledge, and I would say imageomics is a great starting point towards that, he said.

Chaos AAAS presentation, An Imageomics Perspective of Machine Learning and Computer Vision: Micro to Global, was part of the session Imageomics: Powering Machine Learning for Understanding Biological Traits.

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Imageomics Applies AI and Vision Advancements to Biological Questions - Photonics.com