AI Medical Compendium Topic:
Neoplasms

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Improving chimeric antigen receptor T-cell therapies by using artificial intelligence and internet of things technologies: A narrative review.

European journal of pharmacology
Cancer poses a formidable challenge in the field of medical science, prompting the exploration of innovative and efficient treatment strategies. One revolutionary breakthrough in cancer therapy is Chimeric Antigen Receptor (CAR) T-cell therapy, an av...

Essentiality, protein-protein interactions and evolutionary properties are key predictors for identifying cancer-associated genes using machine learning.

Scientific reports
The distinctive nature of cancer as a disease prompts an exploration of the special characteristics the genes implicated in cancer exhibit. The identification of cancer-associated genes and their characteristics is crucial to further our understandin...

Tissue specific tumor-gene link prediction through sampling based GNN using a heterogeneous network.

Medical & biological engineering & computing
A tissue sample is a valuable resource for understanding a patient's symptoms and health status in relation to tumor growth. Recent research seeks to establish a connection between tissue-specific tumor samples and genetic markers (genes). This break...

A Conversation with ChatGPT on Contentious Issues in Senescence and Cancer Research.

Molecular pharmacology
Artificial intelligence (AI) platforms, such as Generative Pretrained Transformer (ChatGPT), have achieved a high degree of popularity within the scientific community due to their utility in providing evidence-based reviews of the literature. However...

Prediction of anti-cancer drug synergy based on cross-matching network and cancer molecular subtypes.

Computers in biology and medicine
At present, anti-cancer drug synergy therapy is one of the most important methods to overcome drug resistance and reduce drug toxicity in cancer treatment. High-throughput screening through deep learning can effectively improve the efficiency of disc...

ISMI-VAE: A deep learning model for classifying disease cells using gene expression and SNV data.

Computers in biology and medicine
Various studies have linked several diseases, including cancer and COVID-19, to single nucleotide variations (SNV). Although single-cell RNA sequencing (scRNA-seq) technology can provide SNV and gene expression data, few studies have integrated and a...

Adverse Event Signal Detection Using Patients' Concerns in Pharmaceutical Care Records: Evaluation of Deep Learning Models.

Journal of medical Internet research
BACKGROUND: Early detection of adverse events and their management are crucial to improving anticancer treatment outcomes, and listening to patients' subjective opinions (patients' voices) can make a major contribution to improving safety management....

Tumor Segmentation in Intraoperative Fluorescence Images Based on Transfer Learning and Convolutional Neural Networks.

Surgical innovation
OBJECTIVE: To propose a transfer learning based method of tumor segmentation in intraoperative fluorescence images, which will assist surgeons to efficiently and accurately identify the boundary of tumors of interest.

Deciphering Ferroptosis: From Molecular Pathways to Machine Learning-Guided Therapeutic Innovation.

Molecular biotechnology
Ferroptosis is a unique form of cell death reliant on iron and lipid peroxidation. It disrupts redox balance, causing cell death by damaging the plasma membrane, with inducers acting through enzymatic pathways or transport systems. In cancer treatmen...