AIMC Topic: Antineoplastic Agents
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Machine Learning-Driven Prediction, Preparation, and Evaluation of Functional Nanomedicines Via Drug-Drug Self-Assembly.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Jan 10, 2025
Small molecules as nanomedicine carriers offer advantages in drug loading and preparation. Selecting effective small molecules for stable nanomedicines is challenging. This study used artificial intelligence (AI) to screen drug combinations for self-...
Evaluating generalizability of oncology trial results to real-world patients using machine learning-based trial emulations.
Nature medicine
Jan 3, 2025
Randomized controlled trials (RCTs) evaluating anti-cancer agents often lack generalizability to real-world oncology patients. Although restrictive eligibility criteria contribute to this issue, the role of selection bias related to prognostic risk r...
pACP-HybDeep: predicting anticancer peptides using binary tree growth based transformer and structural feature encoding with deep-hybrid learning.
Scientific reports
Jan 2, 2025
Worldwide, Cancer remains a significant health concern due to its high mortality rates. Despite numerous traditional therapies and wet-laboratory methods for treating cancer-affected cells, these approaches often face limitations, including high cost...
Drug discovery and mechanism prediction with explainable graph neural networks.
Scientific reports
Jan 2, 2025
Apprehension of drug action mechanism is paramount for drug response prediction and precision medicine. The unprecedented development of machine learning and deep learning algorithms has expedited the drug response prediction research. However, exist...
Deep Learning for the Accurate Prediction of Triggered Drug Delivery.
IEEE transactions on nanobioscience
Jan 2, 2025
The need to mitigate the adverse effects of chemotherapy has driven the exploration of innovative drug delivery approaches. One emerging trend in cancer treatment is the utilization of Drug Delivery Systems (DDSs), facilitated by nanotechnology. Nano...
LC-MS profiling and cytotoxic activity of Angiopteris helferiana against HepG2 cell line: Molecular insight to investigate anticancer agent.
PloS one
Dec 31, 2024
Liver cancer is one of the most prevalent malignant diseases in humans and the second leading cause of cancer-related mortality globally. Angiopteris helferiana was mentioned as a possible anticancer herb according to ethnomedicinal applications. How...
Comparative evaluation of feature reduction methods for drug response prediction.
Scientific reports
Dec 28, 2024
Personalized medicine aims to tailor medical treatments to individual patients, and predicting drug responses from molecular profiles using machine learning is crucial for this goal. However, the high dimensionality of the molecular profiles compared...
Improving the prediction of chemotherapy dose-limiting toxicity in colon cancer patients using an AI-CT-based 3D body composition of the entire L1-L5 lumbar spine.
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Dec 21, 2024
PURPOSE: Chemotherapy dose-limiting toxicities (DLT) pose a significant challenge in successful colon cancer treatment. Body composition analysis may enable tailored interventions thereby supporting the mitigation of chemotherapy toxic effects. This ...
AI-based classification of anticancer drugs reveals nucleolar condensation as a predictor of immunogenicity.
Molecular cancer
Dec 20, 2024
BACKGROUND: Immunogenic cell death (ICD) inducers are often identified in phenotypic screening campaigns by the release or surface exposure of various danger-associated molecular patterns (DAMPs) from malignant cells. This study aimed to streamline t...
Machine-learning derived identification of prognostic signature to forecast head and neck squamous cell carcinoma prognosis and drug response.
Frontiers in immunology
Dec 19, 2024
INTRODUCTION: Head and neck squamous cell carcinoma (HNSCC), a highly heterogeneous malignancy is often associated with unfavorable prognosis. Due to its unique anatomical position and the absence of effective early inspection methods, surgical inter...
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