AIMC Topic: Antineoplastic Agents
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Dumpling GNN: Hybrid GNN Enables Better ADC Payload Activity Prediction Based on the Chemical Structure.
International journal of molecular sciences
May 19, 2025
Antibody-drug conjugates (ADCs) are promising cancer therapeutics, but optimizing their cytotoxic payloads remains challenging. We present DumplingGNN, a novel hybrid Graph Neural Network architecture for predicting ADC payload activity and toxicity....
Deep transfer learning approach for automated cell death classification reveals novel ferroptosis-inducing agents in subsets of B-ALL.
Cell death & disease
May 18, 2025
Ferroptosis is a recently described type of regulated necrotic cell death whose induction has anti-cancer therapeutic potential, especially in hematological malignancies. However, efforts to uncover novel ferroptosis-inducing therapeutics have been l...
Low-cost robotic manipulation of live microtissues for cancer drug testing.
Science advances
May 16, 2025
The scarcity of human biopsies available for drug testing is a paramount challenge for developing therapeutics, disease models, and personalized treatments. Microtechnologies that combine the microscale manipulation of tissues and fluids offer the ex...
Fake It till You Predict It: Data Augmentation Strategies to Detect Initiation and Termination of Oncology Treatment.
Studies in health technology and informatics
May 15, 2025
At the hospital, the dispersion of information regarding anti-cancer treatment makes it difficult to extract. We proposed a solution capable of identifying dates, drugs and their temporal relationship within free-text oncology reports with very few m...
Machine Learning Models Predicting Hospital Admissions During Chemotherapy Utilising Longitudinal Symptom Severity Reports and Patient-Reported Outcome Measures.
Studies in health technology and informatics
May 15, 2025
Chemotherapy toxicity can lead to acute hospital admissions, negatively impacting the healthcare system and patients' well-being. Machine learning (ML) models identifying patients at risk of emergency admissions are often developed on data lacking pa...
Integrating Bulk and Single-Cell Transcriptomics with Machine Learning Reveals a Heme Metabolism-Based Panel for Lung Adenocarcinoma Chemotherapy Resistance.
International journal of molecular sciences
May 14, 2025
Lung adenocarcinoma (LUAD) is a leading cause of cancer-related mortality, with heme metabolism playing a critical role in tumor progression and treatment resistance. This study investigates the clinical implications of heme metabolism in LUAD, focus...
Transcriptome
Cell Line, Tumor
Single-Cell Analysis
Female
Antineoplastic Agents
Gene Expression Profiling
Cisplatin
Heme
Drug Resistance, Neoplasm
Lung Neoplasms
Gene Expression Regulation, Neoplastic
Ferroptosis
Humans
Machine Learning
Prognosis
Multidrug Resistance-Associated Protein 2
Adenocarcinoma of Lung
Multidrug Resistance-Associated Proteins
Active Learning-Based Prediction of Drug Combination Efficacy.
ACS nano
May 13, 2025
Combination therapy, which involves the use of multiple drugs, has emerged as a promising approach to cancer treatment. However, traditional combination therapy development is constrained by the vast experimental design space, requiring exhaustive te...
Artificial Intelligence-Guided Cancer Engineering for Tumor Normalization Executed by Tumor Lysosomal-Triggered Supramolecular Chiral Peptide.
ACS nano
May 13, 2025
Cancer engineering for tumor normalization offers a promising therapeutic strategy to reverse malignant cells and their supportive tumor microenvironment into a more benign state. Herein, an artificial intelligence (AI) approach was developed using m...
Application of Artificial Intelligence in Cardio-Oncology Imaging for Cancer Therapy-Related Cardiovascular Toxicity: Systematic Review.
JMIR cancer
May 9, 2025
BACKGROUND: Artificial intelligence (AI) is a revolutionary tool yet to be fully integrated into several health care sectors, including medical imaging. AI can transform how medical imaging is conducted and interpreted, especially in cardio-oncology.
Assessing the quality and readability of patient education materials on chemotherapy cardiotoxicity from artificial intelligence chatbots: An observational cross-sectional study.
Medicine
Apr 11, 2025
Artificial intelligence (AI) and the introduction of Large Language Model (LLM) chatbots have become a common source of patient inquiry in healthcare. The quality and readability of AI-generated patient education materials (PEM) is the subject of man...
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