AIMC Topic: Docetaxel

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Exploration of Predictive Potential of AI-enabled Portable System in Anticancer Drug Delivery: A Comparative Study with Modified Gompertz like Biphasic Response Model.

AAPS PharmSciTech Jul 16, 2025
Mathematical models are conventionally used to understand the of tumor behaviors, but they generally lack in precisely correlating drug efficacy with tumor response. Artificial intelligence (AI) has forged a new avenue in cancer management, but requi...
Humans Artificial Intelligence Algorithms Female Mice Breast Neoplasms Nanoparticles Drug Delivery Systems Lipids Animals Models, Biological Antineoplastic Agents Docetaxel Cell Line, Tumor
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Developing a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer.

Scientific reports Jul 15, 2025
Although neoadjuvant chemotherapy with docetaxel + cisplatin + 5-fluorouracil (CF) has been the standard treatment for stage II and III esophageal cancers, it is associated with severe adverse events caused by docetaxel. Consequently, this study aime...
Chemotherapy, Adjuvant Esophageal Neoplasms Cisplatin Fluorouracil Docetaxel Machine Learning Middle Aged Prognosis Humans Polymorphism, Single Nucleotide Female Antineoplastic Combined Chemotherapy Protocols Aged Neoadjuvant Therapy Male Neoplasm Recurrence, Local
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Medication Prescription Policy for US Veterans With Metastatic Castration-Resistant Prostate Cancer: Causal Machine Learning Approach.

JMIR medical informatics Nov 19, 2024
BACKGROUND: Prostate cancer is the second leading cause of death among American men. If detected and treated at an early stage, prostate cancer is often curable. However, an advanced stage such as metastatic castration-resistant prostate cancer (mCRP...
Humans Machine Learning Docetaxel Prostatic Neoplasms, Castration-Resistant Nitriles Veterans Benzamides Aged Male Middle Aged Antineoplastic Agents United States Androstenes Phenylthiohydantoin
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Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers.

BMC cancer Oct 30, 2021
OBJECTIVES: To develop and validate a radiomics model for evaluating treatment response to immune-checkpoint inhibitor plus chemotherapy (ICI + CT) in patients with advanced esophageal squamous cell carcinoma (ESCC).
Carboplatin Docetaxel Esophageal Squamous Cell Carcinoma Support Vector Machine Bias Esophageal Neoplasms Combined Modality Therapy Tomography, X-Ray Computed Female Biomarkers, Tumor Male Middle Aged Immune Checkpoint Inhibitors Nomograms Antineoplastic Combined Chemotherapy Protocols Treatment Outcome Antibodies, Monoclonal, Humanized Humans
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Molecular imaging and deep learning analysis of uMUC1 expression in response to chemotherapy in an orthotopic model of ovarian cancer.

Scientific reports Sep 10, 2020
Artificial Intelligence (AI) algorithms including deep learning have recently demonstrated remarkable progress in image-recognition tasks. Here, we utilized AI for monitoring the expression of underglycosylated mucin 1 (uMUC1) tumor antigen, a biomar...
Molecular Imaging Xenograft Model Antitumor Assays Mucin-1 Tumor Cells, Cultured Mice, Nude Humans Apoptosis Artificial Intelligence Ovarian Neoplasms Female Docetaxel Animals Antineoplastic Agents Deep Learning Mice Cell Proliferation
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Identification of Non-Small Cell Lung Cancer Sensitive to Systemic Cancer Therapies Using Radiomics.

Clinical cancer research : an official journal of the American Association for Cancer Research Mar 20, 2020
PURPOSE: Using standard-of-care CT images obtained from patients with a diagnosis of non-small cell lung cancer (NSCLC), we defined radiomics signatures predicting the sensitivity of tumors to nivolumab, docetaxel, and gefitinib.
Humans Machine Learning Prognosis Retrospective Studies Tomography, X-Ray Computed Female Survival Rate Clinical Trials, Phase III as Topic Gefitinib Carcinoma, Non-Small-Cell Lung Randomized Controlled Trials as Topic Male Clinical Trials, Phase II as Topic Disease Progression Nivolumab Lung Neoplasms Docetaxel Antineoplastic Combined Chemotherapy Protocols
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Predicting drug response of tumors from integrated genomic profiles by deep neural networks.

BMC medical genomics Jan 31, 2019
BACKGROUND: The study of high-throughput genomic profiles from a pharmacogenomics viewpoint has provided unprecedented insights into the oncogenic features modulating drug response. A recent study screened for the response of a thousand human cancer ...
Docetaxel Benzothiazoles Naphthyridines Transcriptome Deep Learning Cell Line, Tumor Genomics Mutation Humans Antineoplastic Agents
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Predicting chemo-brain in breast cancer survivors using multiple MRI features and machine-learning.

Magnetic resonance in medicine Nov 12, 2018
PURPOSE: Breast cancer (BC) is the most common cancer in women worldwide. There exist various advanced chemotherapy drugs for BC; however, chemotherapy drugs may result in brain damage during treatment. When a patient's brain is changed in response t...
Cancer Survivors Anisotropy Brain Female Brain Mapping Young Adult Middle Aged Humans Docetaxel Adult Antineoplastic Agents Machine Learning Cognition Disorders Breast Neoplasms Algorithms Case-Control Studies Epirubicin Magnetic Resonance Imaging Fourier Analysis Regression Analysis
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Seven-Month Prostate-Specific Antigen Is Prognostic in Metastatic Hormone-Sensitive Prostate Cancer Treated With Androgen Deprivation With or Without Docetaxel.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology Dec 20, 2017
Purpose We evaluated the relationship between prostate-specific antigen (PSA) and overall survival in the context of a prospectively randomized clinical trial comparing androgen-deprivation therapy (ADT) plus docetaxel with ADT alone for initial meta...
Antineoplastic Combined Chemotherapy Protocols Neoplasms, Hormone-Dependent Treatment Outcome Randomized Controlled Trials as Topic Prostate-Specific Antigen Aged, 80 and over Humans Prostatic Neoplasms Androgen Antagonists Adult Databases, Factual Docetaxel Male Retrospective Studies Neoplasm Metastasis Middle Aged Aged Kallikreins Time Factors
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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...
Antineoplastic Agents Nanoparticles Docetaxel Doxorubicin Humans Machine Learning
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