[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 …
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 …
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 …
Effectiveness of mobile health‐based self‐management application for posttransplant cares: A systematic review
Background and aims Patients after transplantation need medical management for the rest
of their lives, and self‐management seems to lead to greater adherence to medical …
of their lives, and self‐management seems to lead to greater adherence to medical …
[HTML][HTML] A new COVID-19 intubation prediction strategy using an intelligent feature selection and K-NN method
ZA Varzaneh, A Orooji, L Erfannia… - Informatics in medicine …, 2022 - Elsevier
Background Predicting severe respiratory failure due to COVID-19 can help triage patients
to higher levels of care, resource allocation and decrease morbidity and mortality. The need …
to higher levels of care, resource allocation and decrease morbidity and mortality. The need …
A machine learning classifier for predicting stable MCI patients using gene biomarkers
Alzheimer's disease (AD) is a neurodegenerative disorder with an insidious onset and
irreversible condition. Patients with mild cognitive impairment (MCI) are at high risk of …
irreversible condition. Patients with mild cognitive impairment (MCI) are at high risk of …
Artificial Intelligence in Liver Diseases: Recent Advances
F Lu, Y Meng, X Song, X Li, Z Liu, C Gu, X Zheng… - Advances in …, 2024 - Springer
Liver diseases cause a significant burden on public health worldwide. In spite of great
advances during recent years, there are still many challenges in the diagnosis and treatment …
advances during recent years, there are still many challenges in the diagnosis and treatment …
Development and evaluation of a machine learning prediction model for flap failure in microvascular breast reconstruction
AC O'Neill, D Yang, M Roy, S Sebastiampillai… - Annals of surgical …, 2020 - Springer
Background Despite high success rates, flap failure remains an inherent risk in
microvascular breast reconstruction. Identifying patients who are at high risk for flap failure …
microvascular breast reconstruction. Identifying patients who are at high risk for flap failure …