AIMC Topic: Liver Neoplasms

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GATNNCDA: A Method Based on Graph Attention Network and Multi-Layer Neural Network for Predicting circRNA-Disease Associations.

International journal of molecular sciences
Circular RNAs (circRNAs) are a new class of endogenous non-coding RNAs with covalent closed loop structure. Researchers have revealed that circRNAs play an important role in human diseases. As experimental identification of interactions between circR...

Application of an extreme learning machine network with particle swarm optimization in syndrome classification of primary liver cancer.

Journal of integrative medicine
OBJECTIVE: By optimizing the extreme learning machine network with particle swarm optimization, we established a syndrome classification and prediction model for primary liver cancer (PLC), classified and predicted the syndrome diagnosis of medical r...

Classification of focal liver lesions in CT images using convolutional neural networks with lesion information augmented patches and synthetic data augmentation.

Medical physics
PURPOSE: We propose a deep learning method that classifies focal liver lesions (FLLs) into cysts, hemangiomas, and metastases from portal phase abdominal CT images. We propose a synthetic data augmentation process to alleviate the class imbalance and...

Pure laparoscopic versus robotic liver resections: Multicentric propensity score-based analysis with stratification according to difficulty scores.

Journal of hepato-biliary-pancreatic sciences
BACKGROUND: The benefits of pure laparoscopic and robot-assisted liver resections (LLR and RALR) are known in comparison to open surgery. The aim of the present retrospective comparative study is to investigate the role of RALR and LLR according to d...

Robotic resection for hydatid disease of the liver.

BMJ case reports
Robotic-assisted surgery for the management of hepatic echinococcosis was introduced in 2016. The advantage it offers over laparoscopy is less rigidity with the use of the 360° rotation of the Endo-Wrist technology, thus allowing the preservation of ...

Single-breath-hold T2WI liver MRI with deep learning-based reconstruction: A clinical feasibility study in comparison to conventional multi-breath-hold T2WI liver MRI.

Magnetic resonance imaging
OBJECTIVE: To investigate the clinical feasibility of single-breath-hold (SBH) T2-weighted (T2WI) liver MRI with deep learning-based reconstruction in the evaluation of image quality and lesion delineation, compared with conventional multi-breath-hol...

Application of machine learning to large in-vitro databases to identify cancer cell characteristics: telomerase reverse transcriptase (TERT) expression.

Oncogene
Advances in biotechnology and machine learning have created an enhanced environment for unearthing and exploiting previously unrecognized relationships between genomic and epigenetic data with potential therapeutic implications. We applied advanced a...