AIMC Topic: Liver

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Deep learning-based attenuation correction method in Tc-GSA SPECT/CT hepatic imaging: a phantom study.

Radiological physics and technology
This study aimed to evaluate a deep learning-based attenuation correction (AC) method to generate pseudo-computed tomography (CT) images from non-AC single-photon emission computed tomography images (SPECT) for AC in Tc-galactosyl human albumin dieth...

Application of transfer learning to predict drug-induced human in vivo gene expression changes using rat in vitro and in vivo data.

PloS one
The liver is the primary site for the metabolism and detoxification of many compounds, including pharmaceuticals. Consequently, it is also the primary location for many adverse reactions. As the liver is not readily accessible for sampling in humans;...

Should AI allocate livers for transplant? Public attitudes and ethical considerations.

BMC medical ethics
BACKGROUND: Allocation of scarce organs for transplantation is ethically challenging. Artificial intelligence (AI) has been proposed to assist in liver allocation, however the ethics of this remains unexplored and the view of the public unknown. The ...

Artificial Intelligence-powered automatic volume calculation in medical images - available tools, performance and challenges for nuclear medicine.

Nuklearmedizin. Nuclear medicine
Volumetry is crucial in oncology and endocrinology, for diagnosis, treatment planning, and evaluating response to therapy for several diseases. The integration of Artificial Intelligence (AI) and Deep Learning (DL) has significantly accelerated the a...

Application of artificial intelligence techniques for non-alcoholic fatty liver disease diagnosis: A systematic review (2005-2023).

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Non-alcoholic fatty liver disease (NAFLD) is a common liver disease with a rapidly growing incidence worldwide. For prognostication and therapeutic decisions, it is important to distinguish the pathological stages of NAFLD:...

Multi-task machine learning models for simultaneous prediction of tissue-to-blood partition coefficients of chemicals in mammals.

Environmental research
Tissue-to-blood partition coefficients (P) are crucial for assessing the distribution of chemicals in organisms. Given the lack of experimental data and laborious nature of experimental methods, there is an urgent need to develop efficient predictive...

Deep Learning Framework for Liver Segmentation from -Weighted MRI Images.

Sensors (Basel, Switzerland)
The human liver exhibits variable characteristics and anatomical information, which is often ambiguous in radiological images. Machine learning can be of great assistance in automatically segmenting the liver in radiological images, which can be furt...

Shear wave elastography-based deep learning model for prognosis of patients with acutely decompensated cirrhosis.

Journal of clinical ultrasound : JCU
PURPOSE: This study aimed to develop and validate a deep learning model based on two-dimensional (2D) shear wave elastography (SWE) for predicting prognosis in patients with acutely decompensated cirrhosis.

Color-coded laparoscopic liver resection using artificial intelligence: A preliminary study.

Journal of hepato-biliary-pancreatic sciences
Tashiro and colleagues demonstrated for the first time that an artificial intelligence system can precisely identify intrahepatic vascular structures during laparoscopic liver resection in real time through color coding under bleeding and indocyanine...