AIMC Topic: Drug Resistance, Neoplasm
Clear Filters Showing 21 to 30 of 84 articles
Artificial Intelligence-Driven Multiomics Network Analysis Reveals Resistance Mechanisms in Oral Cancer.
International dental journal
Aug 2, 2024
Comprehensive Bioinformatics Analysis and Machine Learning of TTK as a Transhepatic Arterial Chemoembolization Resistance Target in Hepatocellular Carcinoma.
Molecular biotechnology
Jul 2, 2024
Transhepatic arterial chemoembolization (TACE) is the standard treatment for intermediate-stage hepatocellular carcinoma (HCC). However, a significant proportion of patients are non-responders or poor responders to TACE. Therefore, our aim is to iden...
Gene Expression Profiling
Liver Neoplasms
Carcinoma, Hepatocellular
Protein Interaction Maps
Humans
Machine Learning
Prognosis
Computational Biology
Biomarkers, Tumor
Kaplan-Meier Estimate
Drug Resistance, Neoplasm
Gene Expression Regulation, Neoplastic
Cell Cycle Proteins
Chemoembolization, Therapeutic
Databases, Genetic
Artificial intelligence for small molecule anticancer drug discovery.
Expert opinion on drug discovery
Jun 18, 2024
INTRODUCTION: The transition from conventional cytotoxic chemotherapy to targeted cancer therapy with small-molecule anticancer drugs has enhanced treatment outcomes. This approach, which now dominates cancer treatment, has its advantages. Despite th...
Harnessing machine learning potential for personalised drug design and overcoming drug resistance.
Journal of drug targeting
Jun 13, 2024
Drug resistance in cancer treatment presents a significant challenge, necessitating innovative approaches to improve therapeutic efficacy. Integrating machine learning (ML) in cancer research is promising as ML algorithms outrival in analysing comple...
Particle uptake in cancer cells can predict malignancy and drug resistance using machine learning.
Science advances
May 29, 2024
Tumor heterogeneity is a primary factor that contributes to treatment failure. Predictive tools, capable of classifying cancer cells based on their functions, may substantially enhance therapy and extend patient life span. The connection between cell...
Machine learning identifies the role of SMAD6 in the prognosis and drug susceptibility in bladder cancer.
Journal of cancer research and clinical oncology
May 20, 2024
BACKGROUND: Bladder cancer (BCa) is among the most prevalent malignant tumors affecting the urinary system. Due to its highly recurrent nature, standard treatments such as surgery often fail to significantly improve patient prognosis. Our research ai...
Integrated multi-omics analysis and machine learning identify hub genes and potential mechanisms of resistance to immunotherapy in gastric cancer.
Aging
Apr 22, 2024
BACKGROUND: Patients with gastric cancer respond poorly to immunotherapy. There are still unknowns about the biomarkers associated with immunotherapy sensitivity and their underlying molecular mechanisms.
Identification and validation of an immune-derived multiple programmed cell death index for predicting clinical outcomes, molecular subtyping, and drug sensitivity in lung adenocarcinoma.
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Apr 2, 2024
OBJECTIVES: Comprehensive cross-interaction of multiple programmed cell death (PCD) patterns in the patients with lung adenocarcinoma (LUAD) have not yet been thoroughly investigated.
Empowering Graph Neural Networks with Block-Based Dual Adaptive Deep Adjustment for Drug Resistance-Related NcRNA Discovery.
Journal of chemical information and modeling
Mar 24, 2024
Drug resistance to chemotherapeutic agents remains a formidable challenge in cancer treatment, significantly impacting treatment efficacy. Extensive research has exposed the intimate involvement of noncoding RNAs (ncRNAs) in conferring resistance to ...
A deep learning model of tumor cell architecture elucidates response and resistance to CDK4/6 inhibitors.
Nature cancer
Mar 5, 2024
Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6is) have revolutionized breast cancer therapy. However, <50% of patients have an objective response, and nearly all patients develop resistance during therapy. To elucidate the underlying mechanisms, ...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823