AIMC Topic: Liver Transplantation

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Multimodal treatment of colorectal liver metastases: Where are we? Current strategies and future perspectives.

Bioscience trends
Despite the continued high prevalence of colorectal cancer in the Western world, recent years have witnessed a decline in its mortality rate, largely attributable to the sustained advancement of multimodal treatment modalities for metastatic patients...

A snapshot of challenges and opportunities faced by the scientific workforce in liver transplantation-a survey of the International Liver Transplantation Society (ILTS).

Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society
Basic and translational research (B&TR) in liver transplantation (LT) underwent considerable changes and shifts over the past decade. To capture the current landscape and future potential of B&TR in LT, we conducted an online survey within the Inte...

Development of a natural language processing algorithm to extract social determinants of health from clinician notes.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Disparities in access to the organ transplant waitlist are well-documented, but research into modifiable factors has been limited due to a lack of access to organized prewaitlisting data. This study aimed to develop a natural language processing (NLP...

Deep learning for hepatocellular carcinoma recurrence before and after liver transplantation: a multicenter cohort study.

Scientific reports
Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) is a major contributor to mortality. We developed a recurrence prediction system for HCC patients before and after LT. Data from patients with HCC who underwent LT were retros...

Transforming liver transplant allocation with artificial intelligence and machine learning: a systematic review.

BMC medical informatics and decision making
BACKGROUND: The principles of urgency, utility, and benefit are fundamental concepts guiding the ethical and practical decision-making process for organ allocation; however, LT allocation still follows an urgency model.

Advanced prognostic modeling with deep learning: assessing long-term outcomes in liver transplant recipients from deceased and living donors.

Journal of translational medicine
BACKGROUND: Predicting long-term outcomes in liver transplantation remain a challenging endeavor. This research aims to harness the power of deep learning to develop an advanced prognostic model for assessing long-term outcomes, with a specific focus...

Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients.

Scientific reports
Post-Liver transplantation (LT) survival rates stagnate, with biliary complications (BC) as a major cause of death. We analyzed longitudinal data with a median 19-month follow-up. BC was diagnosed with ultrasounds and MRCP. Missing data was imputed u...

The Liver Intensive Care Unit.

Clinics in liver disease
Major advances in managing critically ill patients with liver disease have improved their prognosis and access to intensive care facilities. Acute-on-chronic liver failure (ACLF) is now a well-defined disease and these patients can be fast-tracked fo...

Gender-Equity Model for Liver Allocation Using Artificial Intelligence (GEMA-AI) for Waiting List Liver Transplant Prioritization.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
BACKGROUND & AIMS: We aimed to develop and validate an artificial intelligence score (gender-equity model for liver allocation using artificial intelligence [GEMA-AI]) to predict liver transplantation (LT) waiting list outcomes using the same input v...