[HTML][HTML] Artificial intelligence, machine learning, and deep learning in liver transplantation
Liver transplantation (LT) is a life-saving treatment for individuals with end-stage liver
disease. The management of LT recipients is complex, predominantly because of the need …
disease. The management of LT recipients is complex, predominantly because of the need …
Application of artificial intelligence for the diagnosis and treatment of liver diseases
Modern medical care produces large volumes of multimodal patient data, which many
clinicians struggle to process and synthesize into actionable knowledge. In recent years …
clinicians struggle to process and synthesize into actionable knowledge. In recent years …
[HTML][HTML] Artificial intelligence in gastroenterology: A state-of-the-art review
PT Kröner, MML Engels, BS Glicksberg… - World journal of …, 2021 - ncbi.nlm.nih.gov
The development of artificial intelligence (AI) has increased dramatically in the last 20 years,
with clinical applications progressively being explored for most of the medical specialties …
with clinical applications progressively being explored for most of the medical specialties …
[PDF][PDF] Applying machine learning in liver disease and transplantation: a comprehensive review
Machine learning (ML) utilizes artificial intelligence to generate predictive models efficiently
and more effectively than conventional methods through detection of hidden patterns within …
and more effectively than conventional methods through detection of hidden patterns within …
The promise of machine learning applications in solid organ transplantation
Solid-organ transplantation is a life-saving treatment for end-stage organ disease in highly
selected patients. Alongside the tremendous progress in the last several decades, new …
selected patients. Alongside the tremendous progress in the last several decades, new …
[PDF][PDF] Supervised machine-learning predictive analytics for prediction of postinduction hypotension
Background: Hypotension is a risk factor for adverse perioperative outcomes. Machine-
learning methods allow large amounts of data for development of robust predictive analytics …
learning methods allow large amounts of data for development of robust predictive analytics …
Long-term mortality risk stratification of liver transplant recipients: real-time application of deep learning algorithms on longitudinal data
Background Survival of liver transplant recipients beyond 1 year since transplantation is
compromised by an increased risk of cancer, cardiovascular events, infection, and graft …
compromised by an increased risk of cancer, cardiovascular events, infection, and graft …
HLA‐B* 35: 01 and green tea–induced liver injury
JH Hoofnagle, HL Bonkovsky, EJ Phillips, YJ Li… - Hepatology, 2021 - journals.lww.com
Modern medical care produces large volumes of multimodal patient data, which many
clinicians struggle to process and synthesize into actionable knowledge. In recent years …
clinicians struggle to process and synthesize into actionable knowledge. In recent years …
Software defect prediction for healthcare big data: an empirical evaluation of machine learning techniques
Software defect prediction (SDP) in the initial period of the software development life cycle
(SDLC) remains a critical and important assignment. SDP is essentially studied during few …
(SDLC) remains a critical and important assignment. SDP is essentially studied during few …
Artificial intelligence in precision medicine in hepatology
The advancement of investigation tools and electronic health records (EHR) enables a
paradigm shift from guideline‐specific therapy toward patient‐specific precision medicine …
paradigm shift from guideline‐specific therapy toward patient‐specific precision medicine …