AIMC Topic: Antineoplastic Combined Chemotherapy Protocols

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Deep learning pathological microscopic features in endemic nasopharyngeal cancer: Prognostic value and protentional role for individual induction chemotherapy.

Cancer medicine Dec 20, 2019
BACKGROUND: To explore the prognostic value and the role for treatment decision of pathological microscopic features in patients with nasopharyngeal carcinoma (NPC) using the method of deep learning.
Adult Male Middle Aged Risk Assessment Deep Learning China Humans Prognosis Retrospective Studies Female Radiotherapy, Intensity-Modulated Kaplan-Meier Estimate Chemoradiotherapy Nasopharyngeal Neoplasms Endemic Diseases Nasopharynx Induction Chemotherapy Image Processing, Computer-Assisted Antineoplastic Combined Chemotherapy Protocols Neoplasm Staging Cisplatin Fluorouracil Progression-Free Survival
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Artificial intelligence-guided tissue analysis combined with immune infiltrate assessment predicts stage III colon cancer outcomes in PETACC08 study.

Gut Nov 28, 2019
OBJECTIVE: Diagnostic tests, such as Immunoscore, predict prognosis in patients with colon cancer. However, additional prognostic markers could be detected on pathological slides using artificial intelligence tools.
Humans Disease-Free Survival Artificial Intelligence Image Interpretation, Computer-Assisted Prognosis Antineoplastic Combined Chemotherapy Protocols Adenocarcinoma Lymphocytes, Tumor-Infiltrating Neoplasm Invasiveness Neoplasm Staging Colonic Neoplasms
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Novel approaches for glioblastoma treatment: Focus on tumor heterogeneity, treatment resistance, and computational tools.

Cancer reports (Hoboken, N.J.) Nov 11, 2019
BACKGROUND: Glioblastoma (GBM) is a highly aggressive primary brain tumor. Currently, the suggested line of action is the surgical resection followed by radiotherapy and treatment with the adjuvant temozolomide, a DNA alkylating agent. However, the a...
Glioblastoma Mutation Genetic Heterogeneity Chemoradiotherapy, Adjuvant Brain Neoplasms Clonal Evolution Humans DNA Mutational Analysis Immune Checkpoint Inhibitors Machine Learning DNA Modification Methylases Computational Biology Brain DNA Repair Enzymes Cancer Vaccines Precision Medicine Drug Resistance, Neoplasm Models, Genetic Prognosis Microtubules Antineoplastic Combined Chemotherapy Protocols Tumor Microenvironment Tumor Suppressor Protein p53 Tumor Suppressor Proteins
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[Prediction of chemotherapy response in primary osteosarcoma using the machine learning technique on radiomic data].

Bulletin du cancer Oct 3, 2019
INTRODUCTION: Osteosarcoma is the most common malignant bone tumor before 25 years of age. Response to neoadjuvant chemotherapy determines continuation of treatment and is also a powerful prognostic factor. There are currently no reliable ways to eva...
Humans Machine Learning Retrospective Studies Female Infant, Newborn Young Adult Predictive Value of Tests France Analysis of Variance Chemotherapy, Adjuvant Antineoplastic Combined Chemotherapy Protocols Sensitivity and Specificity Treatment Outcome Male Neoadjuvant Therapy Infant Magnetic Resonance Imaging Adolescent Osteosarcoma Child, Preschool Bone Neoplasms Child
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A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy.

PloS one Oct 2, 2019
PURPOSE: Development of a supervised machine-learning model capable of predicting clinically relevant molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) from diffusion-weighted-imaging-derived radiomic features.
Pancreatic Neoplasms Neoplasm Proteins Fluorouracil Carcinoma, Pancreatic Ductal Disease-Free Survival Deoxycytidine Gemcitabine Irinotecan Keratins, Hair-Specific Keratins, Type II Leucovorin Survival Rate Sensitivity and Specificity Male Middle Aged Antineoplastic Combined Chemotherapy Protocols Oxaliplatin Humans Machine Learning Retrospective Studies Female Adult
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Prediction of irinotecan toxicity in metastatic colorectal cancer patients based on machine learning models with pharmacokinetic parameters.

Journal of pharmacological sciences May 4, 2019
Irinotecan (CPT-11) is a drug used against a wide variety of tumors, which can cause severe toxicity, possibly leading to the delay or suspension of the cycle, with the consequent impact on the prognosis of survival. The main goal of this work is to ...
Middle Aged Diarrhea Antineoplastic Combined Chemotherapy Protocols Oxaliplatin Models, Biological Fluorouracil Machine Learning Forecasting Female Aged Colorectal Neoplasms Male Neutropenia Leukopenia Camptothecin Topoisomerase I Inhibitors Irinotecan Leucovorin Glucuronates Humans
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Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set.

Breast cancer research and treatment Oct 16, 2018
PURPOSE: To determine whether a multivariate machine learning-based model using computer-extracted features of pre-treatment dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can predict pathologic complete response (pCR) to neoadjuvant ...
Mastectomy, Segmental Adult Middle Aged ROC Curve Image Processing, Computer-Assisted Triple Negative Breast Neoplasms Treatment Outcome Antineoplastic Combined Chemotherapy Protocols Humans Neoadjuvant Therapy Machine Learning Magnetic Resonance Imaging Retrospective Studies Neoplasm Staging Female Breast Aged Feasibility Studies Receptor, ErbB-2
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Predict effective drug combination by deep belief network and ontology fingerprints.

Journal of biomedical informatics Aug 3, 2018
The synergistic effect of drug combination is one of the most desirable properties for treating cancer. However, systematically predicting effective drug combination is a significant challenge. We report here a novel method based on deep belief netwo...
Humans Neoplasms Gene Expression Profiling Deep Learning Cell Line, Tumor Databases, Pharmaceutical Gene Regulatory Networks Computational Biology Antineoplastic Combined Chemotherapy Protocols Drug Combinations Drug Synergism Gene Ontology
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Immunomarker Support Vector Machine Classifier for Prediction of Gastric Cancer Survival and Adjuvant Chemotherapeutic Benefit.

Clinical cancer research : an official journal of the American Association for Cancer Research Jul 24, 2018
Current tumor-node-metastasis (TNM) staging system cannot provide adequate information for prediction of prognosis and chemotherapeutic benefits. We constructed a classifier to predict prognosis and identify a subset of patients who can benefit from...
Male Middle Aged ROC Curve Antineoplastic Combined Chemotherapy Protocols Treatment Outcome Support Vector Machine Humans Prognosis Female Aged Stomach Neoplasms Neoplasm Staging Biomarkers, Tumor Neoplasm Grading Survival Analysis Tumor Burden Immunohistochemistry Chemotherapy, Adjuvant
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Predicting Post Neoadjuvant Axillary Response Using a Novel Convolutional Neural Network Algorithm.

Annals of surgical oncology Jul 5, 2018
OBJECTIVES: In the postneoadjuvant chemotherapy (NAC) setting, conventional radiographic complete response (rCR) is a poor predictor of pathologic complete response (pCR) of the axilla. We developed a convolutional neural network (CNN) algorithm to b...
Neoplasm Invasiveness Axilla Receptor, ErbB-2 Carcinoma, Ductal, Breast Receptors, Estrogen Chemotherapy, Adjuvant Carcinoma, Lobular Middle Aged ROC Curve Antineoplastic Combined Chemotherapy Protocols Neoadjuvant Therapy Follow-Up Studies Magnetic Resonance Imaging Humans Aged, 80 and over Neural Networks, Computer Young Adult Algorithms Adult Prognosis Survival Rate Retrospective Studies Breast Neoplasms Female Biomarkers, Tumor Aged
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