AIMC Topic: Antineoplastic Agents
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DRExplainer: Quantifiable interpretability in drug response prediction with directed graph convolutional network.
Artificial intelligence in medicine
Mar 4, 2025
Predicting the response of a cancer cell line to a therapeutic drug is pivotal for personalized medicine. Despite numerous deep learning methods that have been developed for drug response prediction, integrating diverse information about biological e...
Evaluating feature extraction in ovarian cancer cell line co-cultures using deep neural networks.
Communications biology
Feb 25, 2025
Single-cell image analysis is crucial for studying drug effects on cellular morphology and phenotypic changes. Most studies focus on single cell types, overlooking the complexity of cellular interactions. Here, we establish an analysis pipeline to ex...
Inhibition of CDC27 O-GlcNAcylation coordinates the antitumor efficacy in multiple myeloma through the autophagy-lysosome pathway.
Acta pharmacologica Sinica
Feb 21, 2025
Multiple myeloma (MM) is a prevalent hematologic malignancy characterized by abnormal proliferation of cloned plasma cells. Given the aggressive nature and drug resistance of MM cells, identification of novel genes could provide valuable insights for...
Using mathematical modelling and AI to improve delivery and efficacy of therapies in cancer.
Nature reviews. Cancer
Feb 19, 2025
Mathematical modelling has proven to be a valuable tool in predicting the delivery and efficacy of molecular, antibody-based, nano and cellular therapy in solid tumours. Mathematical models based on our understanding of the biological processes at su...
A series of natural language processing for predicting tumor response evaluation and survival curve from electronic health records.
BMC medical informatics and decision making
Feb 17, 2025
BACKGROUND: The clinical information housed within unstructured electronic health records (EHRs) has the potential to promote cancer research. The National Cancer Center Hospital (NCCH) is widely recognized as a leading institution for the treatment ...
Use of machine learning algorithms to construct models of symptom burden cluster risk in breast cancer patients undergoing chemotherapy.
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Feb 13, 2025
PURPOSE: To develop models using different machine learning algorithms to predict high-risk symptom burden clusters in breast cancer patients undergoing chemotherapy, and to determine an optimal model.
Single-Cell Array Enhanced Cell Damage Recognition Using Artificial Intelligence for Anticancer Drug Discovery.
Analytical chemistry
Feb 10, 2025
This work developed a cell damage recognition method based on single-cell arrays using an artificial intelligence tool. The method uses micropatterns (single-cell micropatches and microwells) to isolate each cell in an ordered array to minimize cell ...
Interpretable Dynamic Directed Graph Convolutional Network for Multi-Relational Prediction of Missense Mutation and Drug Response.
IEEE journal of biomedical and health informatics
Feb 10, 2025
Tumor heterogeneity presents a significant challenge in predicting drug responses, especially as missense mutations within the same gene can lead to varied outcomes such as drug resistance, enhanced sensitivity, or therapeutic ineffectiveness. These ...
Predicting Clinical Anticancer Drug Response of Patients by Using Domain Alignment and Prototypical Learning.
IEEE journal of biomedical and health informatics
Feb 10, 2025
Anticancer drug response prediction is crucial in developing personalized treatment plans for cancer patients. However, High-quality patient anticancer drug response data are scarce and cell line data and patient data have different distributions, mo...
Revolutionizing prostate cancer therapy: Artificial intelligence - Based nanocarriers for precision diagnosis and treatment.
Critical reviews in oncology/hematology
Feb 7, 2025
Prostate cancer is one of the major health challenges in the world and needs novel therapeutic approaches to overcome the limitations of conventional treatment. This review delineates the transformative potential of artificial intelligence (AL) in en...
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