AIMC Topic: Liver Neoplasms

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Excited state kinetics of tryptophan and NAD(P)H in blood plasma of normal and abnormal liver conditions: A tool to understand the metabolic changes and classification.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Early diagnosis at the metabolomic level is crucial for the treatment of liver cirrhosis and hepatocellular carcinoma (HCC). In this study, attempts were made to investigate the excited-state kinetics of intrinsic fluorophores, tryptophan and nicotin...

Developing a Novel Artificial Intelligence Framework to Measure the Balance of Clinical Versus Nonclinical Influences on Posthepatectomy Length of Stay.

Annals of surgical oncology
BACKGROUND: Length of stay (LOS) is a key indicator of posthepatectomy care quality. While clinical factors influencing LOS are identified, the balance between clinical and nonclinical influences remains unquantified. We developed an artificial intel...

Statistical and machine learning based platform-independent key genes identification for hepatocellular carcinoma.

PloS one
Hepatocellular carcinoma (HCC) is the most prevalent and deadly form of liver cancer, and its mortality rate is gradually increasing worldwide. Existing studies used genetic datasets, taken from various platforms, but focused only on common different...

Machine learning-based integration reveals immunological heterogeneity and the clinical potential of T cell receptor (TCR) gene pattern in hepatocellular carcinoma.

Apoptosis : an international journal on programmed cell death
The T Cell Receptor (TCR) significantly contributes to tumor immunity, whereas the intricate interplay with the Hepatocellular Carcinoma (HCC) microenvironment and clinical significance remains largely unexplored. Here, we aimed to examine the functi...

Identifying potential signatures of immune cells in hepatocellular carcinoma using integrative bioinformatics approaches and machine-learning strategies.

Immunologic research
Hepatocellular carcinoma (HCC) is a malignant tumor regulated by the immune system. Immunotherapy using checkpoint inhibitors has shown encouraging outcomes in a subset of HCC patients. The main challenges in checkpoint immunotherapy for HCC are to e...

Comparative analysis of the DCNN and HFCNN Based Computerized detection of liver cancer.

BMC medical imaging
Liver cancer detection is critically important in the discipline of biomedical image testing and diagnosis. Researchers have explored numerous machine learning (ML) techniques and deep learning (DL) approaches aimed at the automated recognition of li...

SDR-Former: A Siamese Dual-Resolution Transformer for liver lesion classification using 3D multi-phase imaging.

Neural networks : the official journal of the International Neural Network Society
Automated classification of liver lesions in multi-phase CT and MR scans is of clinical significance but challenging. This study proposes a novel Siamese Dual-Resolution Transformer (SDR-Former) framework, specifically designed for liver lesion class...

Improving Outcomes in Hepatocellular Carcinoma through Integration of Machine Learning: Development of a Tumor-Associated Macrophage Signature.

Digestive diseases (Basel, Switzerland)
INTRODUCTION: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors globally. Macrophages, as essential components of the immune system, play crucial roles in immune regulation, inflammation modulation, and antitumor activity. How...

Impact of deep learning reconstructions on image quality and liver lesion detectability in dual-energy CT: An anthropomorphic phantom study.

Medical physics
BACKGROUND: Deep learning image reconstruction (DLIR) algorithms allow strong noise reduction while preserving noise texture, which may potentially improve hypervascular focal liver lesions.

Intricacies of human-AI interaction in dynamic decision-making for precision oncology.

Nature communications
AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals' cancer progression for effective personalized care. However, AI's imperfections can lead to suboptimal therapeutics...