AIMC Topic: Cholangiocarcinoma

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Comparison of Machine Learning Models Using Diffusion-Weighted Images for Pathological Grade of Intrahepatic Mass-Forming Cholangiocarcinoma.

Journal of imaging informatics in medicine
Is the radiomic approach, utilizing diffusion-weighted imaging (DWI), capable of predicting the various pathological grades of intrahepatic mass-forming cholangiocarcinoma (IMCC)? Furthermore, which model demonstrates superior performance among the d...

Applications of artificial intelligence in biliary tract cancers.

Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology
Biliary tract cancers are malignant neoplasms arising from bile duct epithelial cells. They include cholangiocarcinomas and gallbladder cancer. Gallbladder cancer has a marked geographical preference and is one of the most common cancers in women in ...

Deep learning-based phenotyping reclassifies combined hepatocellular-cholangiocarcinoma.

Nature communications
Primary liver cancer arises either from hepatocytic or biliary lineage cells, giving rise to hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICCA). Combined hepatocellular- cholangiocarcinomas (cHCC-CCA) exhibit equivocal or mixed ...

Implications of ultrasound-based deep learning model for preoperatively differentiating combined hepatocellular-cholangiocarcinoma from hepatocellular carcinoma and intrahepatic cholangiocarcinoma.

Abdominal radiology (New York)
OBJECTIVES: The current study developed an ultrasound-based deep learning model to make preoperative differentiation among hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), and combined hepatocellular-cholangiocarcinoma (cHCC-ICC...

MRI-based automatic identification and segmentation of extrahepatic cholangiocarcinoma using deep learning network.

BMC cancer
BACKGROUND: Accurate identification of extrahepatic cholangiocarcinoma (ECC) from an image is challenging because of the small size and complex background structure. Therefore, considering the limitation of manual delineation, it's necessary to devel...

Clinical Outcomes of Robotic Resection for Perihilar Cholangiocarcinoma: A First, Multicenter, Trans-Atlantic, Expert-Center, Collaborative Study.

Annals of surgical oncology
INTRODUCTION: Perihilar cholangiocarcinoma is a difficult cancer to treat with frequent vascular invasion, local recurrence, and poor survival. Due to the need for biliary anastomosis and potential vascular resection, the standard approach is an open...

Identification of a novel bile marker clusterin and a public online prediction platform based on deep learning for cholangiocarcinoma.

BMC medicine
BACKGROUND: Cholangiocarcinoma (CCA) is a highly aggressive malignant tumor, and its diagnosis is still a challenge. This study aimed to identify a novel bile marker for CCA diagnosis based on proteomics and establish a diagnostic model with deep lea...

Robotic approach for perihilar cholangiocarcinoma: from Bismuth 1 to vascular resection.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Implementation of minimally invasive surgical approaches for perihilar cholangiocarcinoma (pCCA) has been relatively slow compared to other indications. This is due to the complexity of the disease and the need of advanced skills for the ...

EDLM: Ensemble Deep Learning Model to Detect Mutation for the Early Detection of Cholangiocarcinoma.

Genes
The most common cause of mortality and disability globally right now is cholangiocarcinoma, one of the worst forms of cancer that may affect people. When cholangiocarcinoma develops, the DNA of the bile duct cells is altered. Cholangiocarcinoma claim...