AIMC Topic: Cell Transformation, Neoplastic
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In silico saturation mutagenesis of cancer genes.
Nature
Jul 28, 2021
Despite the existence of good catalogues of cancer genes, identifying the specific mutations of those genes that drive tumorigenesis across tumour types is still a largely unsolved problem. As a result, most mutations identified in cancer genes acros...
Machine learning-based investigation of the cancer protein secretory pathway.
PLoS computational biology
Apr 5, 2021
Deregulation of the protein secretory pathway (PSP) is linked to many hallmarks of cancer, such as promoting tissue invasion and modulating cell-cell signaling. The collection of secreted proteins processed by the PSP, known as the secretome, is ofte...
Identification of Latent Oncogenes with a Network Embedding Method and Random Forest.
BioMed research international
Sep 23, 2020
Oncogene is a special type of genes, which can promote the tumor initiation. Good study on oncogenes is helpful for understanding the cause of cancers. Experimental techniques in early time are quite popular in detecting oncogenes. However, their def...
External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodules.
Thorax
Mar 5, 2020
BACKGROUND: Estimation of the risk of malignancy in pulmonary nodules detected by CT is central in clinical management. The use of artificial intelligence (AI) offers an opportunity to improve risk prediction. Here we compare the performance of an AI...
Neoplasm Staging
Cell Transformation, Neoplastic
Cohort Studies
ROC Curve
Lung Neoplasms
Multiple Pulmonary Nodules
Early Detection of Cancer
Neoplasm Invasiveness
Predictive Value of Tests
Area Under Curve
Male
Middle Aged
Risk Assessment
Incidence
Retrospective Studies
Female
Aged
Adult
Humans
Artificial Intelligence
Neural Networks, Computer
Algorithms
Databases, Factual
Prognosis
Prediction of melanoma evolution in melanocytic nevi via artificial intelligence: A call for prospective data.
European journal of cancer (Oxford, England : 1990)
Aug 8, 2019
Recent research revealed the superiority of artificial intelligence over dermatologists to diagnose melanoma from images. However, 30-50% of all melanomas and more than half of those in young patients evolve from initially benign lesions. Despite its...
Advances in the computational and molecular understanding of the prostate cancer cell nucleus.
Journal of cellular biochemistry
Jun 20, 2018
Nuclear alterations are a hallmark of many types of cancers, including prostate cancer (PCa). Recent evidence shows that subvisual changes, ones that may not be visually perceptible to a pathologist, to the nucleus and its ultrastructural components ...
Identification of transcription factors that may reprogram lung adenocarcinoma.
Artificial intelligence in medicine
Apr 1, 2017
BACKGROUND: Lung adenocarcinoma is one of most threatening disease to human health. Although many efforts have been devoted to its genetic study, few researches have been focused on the transcription factors which regulate tumor initiation and progre...
Humans
Transcription, Genetic
Computational Biology
Artificial Intelligence
Transcription Factors
Epigenesis, Genetic
Adenocarcinoma of Lung
Gene Regulatory Networks
Adenocarcinoma
Gene Expression Regulation, Neoplastic
Lung Neoplasms
Databases, Genetic
Signal Transduction
Cell Transformation, Neoplastic
Genome instability model of metastatic neuroblastoma tumorigenesis by a dictionary learning algorithm.
BMC medical genomics
Sep 10, 2015
BACKGROUND: Metastatic neuroblastoma (NB) occurs in pediatric patients as stage 4S or stage 4 and it is characterized by heterogeneous clinical behavior associated with diverse genotypes. Tumors of stage 4 contain several structural copy number aberr...
FTIR-based machine learning for prediction of malignant transformation in oral epithelial dysplasia.
The Analyst
Jun 23, 2025
Oral squamous cell carcinoma (OSCC) is an aggressive cancer with a poor prognosis. Oral epithelial dysplasia (OED) is a precancerous lesion associated with an increased risk of malignant transformation (MT) into OSCC. However, current histopathologic...
Single-cell analyses unravel ecosystem dynamics and intercellular crosstalk during gallbladder cancer malignant transformation.
Hepatology communications
Jun 1, 2025
BACKGROUND: Gallbladder cancer (GBC) is a rare but aggressive malignancy, often detected late due to early asymptomatic stages. Understanding cellular and molecular changes from normal tissue to high-grade intraepithelial neoplasia (HGIN) and invasiv...
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