TKIs in combination with immunotherapy for hepatocellular carcinoma
B Stefanini, L Ielasi, R Chen, C Abbati… - Expert review of …, 2023 - Taylor & Francis
Introduction The treatment landscape of hepatocellular carcinoma (HCC) has significantly
changed over the last 5 years with multiple options in the frontline, second line, and beyond …
changed over the last 5 years with multiple options in the frontline, second line, and beyond …
Biomarkers for diagnosis and therapeutic options in hepatocellular carcinoma
Liver cancer is a global health challenge, causing a significant social-economic burden.
Hepatocellular carcinoma (HCC) is the predominant type of primary liver cancer, which is …
Hepatocellular carcinoma (HCC) is the predominant type of primary liver cancer, which is …
Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study
Deep learning (DL) can predict microsatellite instability (MSI) from routine histopathology
slides of colorectal cancer (CRC). However, it is unclear whether DL can also predict other …
slides of colorectal cancer (CRC). However, it is unclear whether DL can also predict other …
Battle of the biopsies: Role of tissue and liquid biopsy in hepatocellular carcinoma
The diagnosis and management of hepatocellular carcinoma (HCC) have improved
significantly in recent years. With the introduction of immunotherapy-based combination …
significantly in recent years. With the introduction of immunotherapy-based combination …
Deep learning-based phenoty** reclassifies combined hepatocellular-cholangiocarcinoma
Primary liver cancer arises either from hepatocytic or biliary lineage cells, giving rise to
hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICCA). Combined …
hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICCA). Combined …
From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology
Hematoxylin-and eosin-stained whole-slide images (WSIs) are the foundation of diagnosis
of cancer. In recent years, development of deep learning-based methods in computational …
of cancer. In recent years, development of deep learning-based methods in computational …
Facts and hopes on the use of artificial intelligence for predictive immunotherapy biomarkers in cancer
Immunotherapy by immune checkpoint inhibitors has become a standard treatment strategy
for many types of solid tumors. However, the majority of patients with cancer will not …
for many types of solid tumors. However, the majority of patients with cancer will not …
Artificial intelligence-based pathology as a biomarker of sensitivity to atezolizumab–bevacizumab in patients with hepatocellular carcinoma: a multicentre retrospective …
Background Clinical benefits of atezolizumab plus bevacizumab (atezolizumab–
bevacizumab) are observed only in a subset of patients with hepatocellular carcinoma and …
bevacizumab) are observed only in a subset of patients with hepatocellular carcinoma and …
Artificial intelligence for prediction of response to cancer immunotherapy
Y Yang, Y Zhao, X Liu, J Huang - Seminars in Cancer Biology, 2022 - Elsevier
Artificial intelligence (AI) indicates the application of machines to imitate intelligent behaviors
for solving complex tasks with minimal human intervention, including machine learning and …
for solving complex tasks with minimal human intervention, including machine learning and …
[HTML][HTML] Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review
Background The widespread use of Immune checkpoint-inhibitors (ICI) has revolutionised
treatment of multiple cancer types. However, selecting patients who may benefit from ICI …
treatment of multiple cancer types. However, selecting patients who may benefit from ICI …