Paul Baird

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Professorial Fellow

University of Melbourne

Australia

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About

Paul Baird is a Professorial Fellow at the University of Melbourne, Australia. His research interests encompass a range of topics including keratoconus, artificial intelligence in medical applications, and body composition analysis in cancer patients. Recent articles authored by him focus on the predictive tools for chemotherapy toxicities and the genetic architectures related to age-related macular degeneration across different ancestries.

Recent Grants

Grant: Close

Genetic variations affecting clearance of unhealthy neurons lead to neurological diseases

Open Date: 2013-01-01

Close Date: 2015-12-31

Grant: Close

How we can use genetic findings to improve health of people with common eye diseases in our society

Open Date: 2012-01-01

Close Date: 2016-12-31

Grant: Close

Myopia: gene-environment interactions

Open Date: 2012-01-01

Close Date: 2014-12-31

Grant: Close

Identifying a genetic variant that influences treatmentto ranibizumab (Lucentis) for the eye disease age-related macular degeneration (AMD)

Open Date: 2011-01-01

Close Date: 2013-12-31

Grant: Close

Predictors of treatment outcomes for AMD.

Open Date: 2010-01-01

Close Date: 2012-12-31

Articles (17)

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2022

Collaborators (23)

Wen Zhang

UNITED STATES

Paul Baird

Research Interests

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About

Recent Grants

Articles (17)

Does Keratoconus Follow Rundle’s Curve?

Improving the prediction of chemotherapy dose-limiting toxicity in colon cancer patients using an AI-CT-based 3D body composition of the entire L1–L5 lumbar spine

Body composition assessment by artificial intelligence can be a predictive tool for short-term postoperative complications in Hartmann’s reversals

Genome-wide association analyses identify distinct genetic architectures for age-related macular degeneration across ancestries

Using a new artificial intelligence-aided method to assess body composition CT segmentation in colorectal cancer patients

Artificial intelligence measured 3D body composition to predict pathological response in rectal cancer patients

The association of body composition on chemotherapy toxicities in non-metastatic colorectal cancer patients: a systematic review

A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration

Rare variant analyses across multiethnic cohorts identify novel genes for refractive error

Can AI-based body composition assessment outperform body surface area in predicting dose-limiting toxicities for colonic cancer patients on chemotherapy?

Keratoconus International Consortium (KIC)- advancing keratoconus research

The extracellular microenvironment in immune dysregulation and inflammation in retinal disorders

Comparison of CT derived body composition at the thoracic T4 and T12 with lumbar L3 vertebral levels and their utility in patients with rectal cancer

Stratification of keratoconus progression using unsupervised machine learning analysis of tomographical parameters

Exploring the contribution of ARMS2 and HTRA1 genetic risk factors in age-related macular degeneration.

Non-genetic risk factors for keratoconus

Examining Corneal Tissue Exportation Fee and Its Impact on Equitable Allocation

Collaborators (23)

Wen Zhang

Karin Verspoor

Adnan Tufail

Jeremy Guggenheim

Kathryn P Burdon

Sara Vogrin

Juho Wedenoja

Joseph Marsh

Jessica Cooke Bailey

Stuart MacGregor

Jamie Craig

Michael Hunter

Samantha Sze-Yee Lee

Joan Bailey-Wilson

Mark Daniell

Tom MacGillivray

Seyhan Yazar

Kenji Yamashiro

Georgios Voloudakis

Virginie Verhoeven

Jason Charng

Cathy Williams

Ian McAllister

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