AIMC Topic: Cell Transformation, Neoplastic
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A novel AI-based score for assessing the prognostic value of intra-epithelial lymphocytes in oral epithelial dysplasia.
British journal of cancer
Nov 30, 2024
BACKGROUND: Oral epithelial dysplasia (OED) poses a significant clinical challenge due to its potential for malignant transformation and the lack of reliable prognostic markers. Current OED grading systems do not reliably predict transformation and s...
Advanced Prediction of Hepatic Oncogenic Transformation in HBV Patients via RNA-Seq Data Analysis and Deep Learning Techniques.
International journal of molecular sciences
Sep 11, 2024
Liver cancer, recognized as a significant global health issue, is increasingly correlated with Hepatitis B virus (HBV) infection, as evidenced by numerous scientific studies. This study aims to examine the correlation between HBV infection and the de...
Identification and analysis of significant genes in nonalcoholic steatohepatitis-hepatocellular carcinoma transformation: Bioinformatics analysis and machine learning approach.
Molecular immunology
Aug 13, 2024
PURPOSE: Nonalcoholic steatohepatitis (NASH) has been an increasingly significant contributor to hepatocellular carcinoma (HCC). Understanding the progression from NASH to HCC is critical to early diagnosis and elucidating the underlying mechanisms.
Liver Neoplasms
Carcinoma, Hepatocellular
Single-Cell Analysis
Disease Progression
Cell Line, Tumor
Cell Transformation, Neoplastic
Suppressor of Cytokine Signaling Proteins
Computational Biology
Gene Expression Regulation, Neoplastic
Non-alcoholic Fatty Liver Disease
Humans
Machine Learning
Prognosis
Machine learning methods in predicting the risk of malignant transformation of oral potentially malignant disorders: A systematic review.
International journal of medical informatics
Mar 22, 2024
BACKGROUND: Oral Potentially Malignant Disorders (OPMDs) refer to a heterogenous group of clinical presentations with heightened rate of malignant transformation. Identification of risk levels in OPMDs is crucial to determine the need for active inte...
Integrated analysis of single-cell RNA-seq and chipset data unravels PANoptosis-related genes in sepsis.
Frontiers in immunology
Jan 3, 2024
BACKGROUND: The poor prognosis of sepsis warrants the investigation of biomarkers for predicting the outcome. Several studies have indicated that PANoptosis exerts a critical role in tumor initiation and development. Nevertheless, the role of PANopto...
Molecular and functional imaging in cancer-targeted therapy: current applications and future directions.
Signal transduction and targeted therapy
Feb 27, 2023
Targeted anticancer drugs block cancer cell growth by interfering with specific signaling pathways vital to carcinogenesis and tumor growth rather than harming all rapidly dividing cells as in cytotoxic chemotherapy. The Response Evaluation Criteria ...
Artificial intelligence uncovers carcinogenic human metabolites.
Nature chemical biology
Aug 11, 2022
The genome of a eukaryotic cell is often vulnerable to both intrinsic and extrinsic threats owing to its constant exposure to a myriad of heterogeneous compounds. Despite the availability of innate DNA damage responses, some genomic lesions trigger m...
Prediction of the risk of cancer and the grade of dysplasia in leukoplakia lesions using deep learning.
Oral oncology
Jun 25, 2022
OBJECTIVES: To estimate the probability of malignancy of an oral leukoplakia lesion using Deep Learning, in terms of evolution to cancer and high-risk dysplasia.
Deep neural network for the determination of transformed foci in Bhas 42 cell transformation assay.
Scientific reports
Dec 2, 2021
Bhas 42 cell transformation assay (CTA) has been used to estimate the carcinogenic potential of chemicals by exposing Bhas 42 cells to carcinogenic stimuli to form colonies, referred to as transformed foci, on the confluent monolayer. Transformed foc...
Artificial intelligence strategy integrating morphologic and architectural biomarkers provides robust diagnostic accuracy for disease progression in chronic lymphocytic leukemia.
The Journal of pathology
Oct 25, 2021
Artificial intelligence-based tools designed to assist in the diagnosis of lymphoid neoplasms remain limited. The development of such tools can add value as a diagnostic aid in the evaluation of tissue samples involved by lymphoma. A common diagnosti...
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