Publications > Journals > Journal of Clinical and Translational Hepatology > Special Feature

Time: March 18, 2022


Journal: Journal of Clinical and Translational Hepatology

Special Issue: Artificial Intelligence in Liver Disease- Step towords Precision Medicine

Guest Editor-in-Chief: Prof. Ashok Choudhury

Guest Editors: Mamatha Bhat, Sumeet Asrani, Connel A Valerie, Xiaolong Qi 

Status: Open

Submission deadline: July 31, 2022

Publication date: An article will be published online as soon as it is accepted.

Guest Editor-in-Chief Profiles:

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Ashok Choudhury, MD DM

Dr Ashok Choudhury currently works as Head of Gastroenterology, Hepatology and Liver Transplantation at the Institute of Liver Sciences-Narayana Health, Gurugram., India. He is also an Honorary Professor of Gastroenterology and Hepatology at KIMS Bhubaneswar, India. His research is focused on acute-on-chronic liver failure, liver decompensation, sepsis, liver transplantation, and hepatocellular carcinoma (HCC) and Artificial Intelligence (AI) via both clinical as well as translational studies. He was awarded Best Abstract and a Fellow Research award by the American Association for Study of Liver Disease in 2014, a Young Investigator Award by the International Liver Transplant Society in 2016, and a Young Investigator Award by the Asia Pacific Association for Study of Liver in 2017. He has expertise conducting multicentric collaborative studies and handling big data. He was the Principal Coordinator of the APASL ACLF Research Consortium from 2014 to January 2022 and also the Principal Investigator for the Global Study on Liver (CLEARED study) and the Asia Pacific study on COVID and liver injury (APCOLIS study). Currently, he has ongoing research projects related to the use of artificial intelligence in liver failure, Liver Transplant, Cirrhosis and decompensation and HCC.  

Artificial intelligence (AI) is the new era of data science and is rapidly gaining utility in the health sector. Given the demonstrated performance of AI in different domains and the rapid progress of methodology improvement, deep learning paradigms have introduced exciting and new opportunities for biomedical informatics. There are many aspects of deep learning that could be helpful in the diagnosis and management of liver diseases, with advantages such as superior performance, an end-to-end learning scheme with integrated feature learning, and the capability of handling complex and multi-modality data. Currently, digital imaging technology for radiology and histopathology is expanding the horizon. AI is now being applied for liver disease across the spectrum i.e. nonalcoholic fatty liver disease (NAFLD), liver fibrosis, liver cancer, cirrhosis, complications of cirrhosis and also for management of pre- and post-liver transplant. The use of AI in liver disease is still in the early stages but is emerging. There is an immediate need for improved methods, tools that enable deep learning interface with information and guidance for clinical decision-making and treatments

For this special issue, we invite front-line hepatologists and liver researchers to submit high-quality scientific manuscripts regarding the application of AI in the management of liver disease. Potential topics include, but are not limited to:

The authors should refer to the Instructions for Authors in preparing the manuscript and kindly submit it through the Online Submission System directly.

Priority will be given with the same high standards of peer review and publication process for these articles. All publications will open free access to all readers. We guarantee that all accepted papers related to AI in Liver Disease will be highlighted in a special section on our website.


Online submission system: https://www.editorialmanager.com/jcth/

Instructions for authors: Please state in a cover letter that the manuscript is being submitted for inclusion in the special issue ‘Acute liver failure (ALF)’ and follow the usual JCTH instructions. Please refer to: https://www.xiahepublishing.com/journal/jcth/instruction

For any inquiries, please contact the journal by e-mail: [email protected]