Lionel Tim-Ee Cheng

Clinical Associate Professor

Duke-NUS Medical School

Singapore

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Dr. Lionel Tim-Ee Cheng is a Clinical Associate Professor at Duke-NUS Medical School in Singapore. His research focuses on the development and application of advanced technologies such as deep learning and natural language processing in medical diagnostics and treatment monitoring. Recent publications include studies on intestinal ultrasound in inflammatory bowel disease, biomarkers for bariatric surgery impacts, and automated labeling of radiology reports. His work aims to enhance clinical practices through innovative approaches in artificial intelligence and radiology education.

Articles (16)

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2025

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2024

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2024

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2023

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2023

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2023

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2020

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2020

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2020

Collaborators (3)

Nichole Tan

National University of Singapore

SINGAPORE

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Nan Liu

Associate Professor

National University of Singapore (NUS)

SINGAPORE

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Kevin Tan

National Neuroscience Institute

SINGAPORE

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Lionel Tim-Ee Cheng

Research Interests

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Articles (16)

Clinical and environmental impact of intestinal ultrasound for inflammatory bowel disease: a tertiary centre experience in Southeast Asia

The Glutamate-Serine-Glycine Index as a Biomarker to Monitor the Effects of Bariatric Surgery on Non-alcoholic Fatty Liver Disease

Application of deep learning algorithms in classification and localization of implant cutout for the postoperative hip

Deep Learning Model and its Application for the Diagnosis of Exudative Pharyngitis

A translational perspective towards clinical AI fairness

Application of a deep learning algorithm in the detection of hip fractures

Multiparametric Magnetic Resonance Imaging and Magnetic Resonance Elastography to Evaluate the Early Effects of Bariatric Surgery on Nonalcoholic Fatty Liver Disease

Future Online Radiology Education: The Importance of Curriculum

Novel use of natural language processing for registry development in peritoneal surface malignancies

The role of magnetic resonance tumour regression grade in the prediction of regression and survival of rectal adenocarcinoma after long-course chemoradiotherapy: a cohort study

Automated labelling of radiology reports using natural language processing: Comparison of traditional and newer methods

Erratum: Future Online Radiology Education: The Importance of Curriculum

Inferring cancer disease response from radiology reports using large language models with data augmentation and prompting

Chest Radiographs and CTs in the Era of COVID-19: Indications, Operational Safety Considerations and Alternative Imaging Practices

Touch Me Not: Physical Distancing in Radiology During Coronavirus Disease 2019 (COVID-19).

Déjà Vu or Jamais Vu? How the Severe Acute Respiratory Syndrome Experience Influenced a Singapore Radiology Department's Response to the Coronavirus Disease (COVID-19) Epidemic.

Collaborators (3)

Nichole Tan

Nan Liu

Kevin Tan

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