胶质母细胞瘤的相关论文研究

1. 胶质母细胞瘤的相关的论文

1. Natural Small Molecules Targeting NF-κB Signaling in Glioblastoma:
   • This review discusses the role of NF-κB signaling in glioblastoma and highlights natural small molecules that can interfere with this pathway, potentially influencing tumor and cell apoptosis.
   • Read the full article here.
2. Gather Wisdom to Overcome Barriers: Well-Designed Nano-Drug Delivery Systems for Treating Gliomas:
   • This study addresses drug delivery systems in glioma treatment, focusing on overcoming the blood-brain barrier and targeting glioma cells specifically.
   • Read the full article here.
3. Network Pharmacology-Based Screening of the Active Ingredients and Mechanisms of Evodiae Fructus Against Glioblastoma Multiforme:
   • Utilizing network pharmacology, this study screens for active ingredients in Evodiae Fructus that may inhibit glioblastoma, providing a preliminary understanding of its mechanisms.
   • Read the full article here.
4. Paving the Way for Small-Molecule Drug Discovery:
   • This article explores the pathway for developing new drugs with a focus on increasing the role of in silico methods for a faster and more efficient drug development process.
   • Read the full article here.
5. A System Bioinformatics Approach Predicts the Molecular Mechanism Underlying the Course of Action of Radix Salviae Reverses GBM Effects:
   • This study uses a bioinformatics approach to analyze the potential effects of Radix Salviae on glioblastoma, including molecular docking to predict interactions.
   • Read the full article here.
6. Artificial Intelligence to Deep Learning: Machine Intelligence Approach for Drug Discovery
   • This article explores how AI and machine learning technologies, including deep learning, enhance rational drug design and discovery, focusing on glioblastoma.
   • Read the article here.
7. Deep Neural Networks for Neuro-Oncology: Towards Patient Individualized Design of Chemo-Radiation Therapy for Glioblastoma Patients
   • Discusses the application of deep reinforcement learning (RL) for personalized design of treatment schedules in glioblastoma.
   • Read the article here.
8. Advances of Artificial Intelligence in Anti-Cancer Drug Design: A Review of the Past Decade
   • Reviews the advancements in AI for drug design, particularly focusing on cancer therapies, and their implications for glioblastoma treatment.
   • Read the article here.
9. Predicting Cell Behaviour Parameters from Glioblastoma on a Chip Images: A Deep Learning Approach
   • This study uses machine learning methods to analyze images from glioblastoma cultures, illustrating the use of AI in understanding cell behavior in glioblastoma.
   • Read the article here.
10. Next Generation Sequencing and Machine Learning Technologies are Painting the Epigenetic Portrait of Glioblastoma
    • Highlights how machine learning and next-generation sequencing are used to advance the understanding of glioblastoma’s epigenetic landscape.
    • Read the article here.

2. 人工智能药物设计AIDD-相关的论文

1. Artificial intelligence to deep learning: machine intelligence approach for drug discovery - This article discusses the integration of AI and machine learning technologies, particularly deep learning, in drug discovery, providing an overview of the advancements and opportunities in rational drug design.
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2. Artificial intelligence in drug design - This review highlights the role of AI, including deep neural networks, in the drug design process, emphasizing its impact on enhancing drug discovery efficiency.
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3. Advances and perspectives in applying deep learning for drug design and discovery - This article explores the application of deep learning models in drug design, discussing how these models improve the prediction and optimization processes in the discovery of new drugs.
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4. Artificial intelligence in chemistry and drug design - This paper reviews the use of AI and machine learning in drug discovery and design, focusing on their application across various stages of the drug development process.
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5. Artificial intelligence and machine learning technology driven modern drug discovery and development - This review provides insights into the latest developments in AI-driven drug discovery, detailing the technologies and methodologies that are shaping the future of pharmaceutical research.
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3. 胶质母细胞瘤与人工智能结合-相关的论文

1. Advances of Artificial Intelligence in Anti-Cancer Drug Design: A Review of the Past Decade
   • This review discusses significant advancements in anti-cancer drug design, facilitated by artificial intelligence, focusing on techniques that have been applied to glioblastoma.
   • Read the article here.
2. An Overview of Targets and Therapies for Glioblastoma Multiforme
   • This paper provides a comprehensive overview of therapeutic targets and current treatment strategies for glioblastoma, highlighting the role of AI in advancing drug design.
   • Read the article here.
3. Imaging Biomarkers and Artificial Intelligence in Glioblastoma Patients Treated with Immune Checkpoint Modulators
   • This research explores the integration of artificial intelligence with imaging techniques to better understand and treat glioblastoma.
   • Read the article here.
4. A Fully Automated Artificial Intelligence Method for Non-Invasive, Imaging-Based Identification of Genetic Alterations in Glioblastomas
   • Discusses a deep learning approach to predict glioblastoma genetic alterations through non-invasive imaging techniques.
   • Read the article here.
5. Artificial Intelligence in the Radiomic Analysis of Glioblastomas: A Review, Taxonomy, and Perspective
   • This article reviews the application of machine learning techniques in the radiomic analysis of glioblastoma, focusing on the use of AI to enhance diagnostic and therapeutic strategies.
   • Read the article here.