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Qsar Modeling of Pancreatic Cancer Drug Combinations: A Machine and Deep Learning Study
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inferredcites →https://doi.org/10.1001/jama.2016.4324openalex-extracted
Effect of Chemoradiotherapy vs Chemotherapy on Survival in Patients With Locally Advanced Pancreatic Cancer Controlled After 4 Months of Gemcitabine With or Without Erlotinib
inferredcites →https://doi.org/10.1001/jama.2019.10232openalex-extracted
Screening for Pancreatic Cancer
inferredcites →https://doi.org/10.1001/jamaoncol.2019.1588openalex-extracted
Durvalumab With or Without Tremelimumab for Patients With Metastatic Pancreatic Ductal Adenocarcinoma
inferredcites →https://doi.org/10.1016/c2014-0-00286-9openalex-extracted
Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment
inferredcites →https://doi.org/10.1016/j.compbiomed.2024.108433openalex-extracted
Exploratory drug discovery in breast cancer patients: A multimodal deep learning approach to identify novel drug candidates targeting RTK signaling
inferredcites →https://doi.org/10.1016/j.crmeth.2023.100413openalex-extracted
Machine learning approaches to predict drug efficacy and toxicity in oncology
inferredcites →https://doi.org/10.1016/j.lungcan.2015.12.005openalex-extracted
A multicenter phase II study of sorafenib in combination with erlotinib in patients with advanced non-small cell lung cancer (KCSG-0806)
inferredcites →https://doi.org/10.1016/j.tranon.2018.11.009openalex-extracted
Cyclical Treatment of Colorectal Tumor Spheroids Induces Resistance to MEK Inhibitors
inferredcites →https://doi.org/10.1016/s0140-6736(15)00986-1openalex-extracted
Nanoliposomal irinotecan with fluorouracil and folinic acid in metastatic pancreatic cancer after previous gemcitabine-based therapy (NAPOLI-1): a global, randomised, open-label, phase 3 trial
inferredcites →https://doi.org/10.1016/s0140-6736(16)32409-6openalex-extracted
Comparison of adjuvant gemcitabine and capecitabine with gemcitabine monotherapy in patients with resected pancreatic cancer (ESPAC-4): a multicentre, open-label, randomised, phase 3 trial
inferredcites →https://doi.org/10.1021/acs.molpharmaceut.0c01013openalex-extracted
Bioactivity Comparison across Multiple Machine Learning Algorithms Using over 5000 Datasets for Drug Discovery
inferredcites →https://doi.org/10.1021/acsmedchemlett.8b00437openalex-extracted
Transforming Computational Drug Discovery with Machine Learning and AI
inferredcites →https://doi.org/10.1021/acsomega.8b03693openalex-extracted
Multicellular Target QSAR Model for Simultaneous Prediction and Design of Anti-Pancreatic Cancer Agents
inferredcites →https://doi.org/10.1021/ci500747nopenalex-extracted
Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
inferredcites →https://doi.org/10.1023/a:1008115913787openalex-extracted
Receptor-based 3D QSAR analysis of estrogen receptor ligands – merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods
inferredcites →https://doi.org/10.1038/bjc.2016.45openalex-extracted
Final analysis of a phase II study of modified FOLFIRINOX in locally advanced and metastatic pancreatic cancer
inferredcites →https://doi.org/10.1038/s41571-018-0112-1openalex-extracted
Optimizing the outcomes of pancreatic cancer surgery
inferredcites →https://doi.org/10.1038/s41575-018-0005-xopenalex-extracted
Therapeutic developments in pancreatic cancer: current and future perspectives
inferredcites →https://doi.org/10.1038/s41586-022-04437-2openalex-extracted
Effective drug combinations in breast, colon and pancreatic cancer cells
inferredcites →https://doi.org/10.1038/s41598-020-61923-1openalex-extracted
A critical evaluation of methods to interpret drug combinations
inferredcites →https://doi.org/10.1038/s41698-024-00583-0openalex-extracted
Overcoming limitations in current measures of drug response may enable AI-driven precision oncology
inferredcites →https://doi.org/10.1038/srep04668openalex-extracted
Designing of promiscuous inhibitors against pancreatic cancer cell lines
inferredcites →https://doi.org/10.1042/cs20200309openalex-extracted
Interactions between cardiology and oncology drugs in precision cardio-oncology
inferredcites →https://doi.org/10.1056/nejmoa1011923openalex-extracted
FOLFIRINOX versus Gemcitabine for Metastatic Pancreatic Cancer
inferredcites →https://doi.org/10.1056/nejmoa1304369openalex-extracted
Increased Survival in Pancreatic Cancer with nab-Paclitaxel plus Gemcitabine
inferredcites →https://doi.org/10.1056/nejmoa1903387openalex-extracted
Maintenance Olaparib for Germline BRCA -Mutated Metastatic Pancreatic Cancer
inferredcites →https://doi.org/10.1093/bib/bbaa321openalex-extracted
Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets
inferredcites →https://doi.org/10.1136/ijgc-2022-igcs.430openalex-extracted
EP341/#510 Exploratory results of a phase IB trial of paclitaxel and carboplatin + galunisertib in patients with uterine and ovarian carcinosarcoma
inferredcites →https://doi.org/10.1158/1535-7163.mct-17-1142openalex-extracted
Concurrent HER or PI3K Inhibition Potentiates the Antitumor Effect of the ERK Inhibitor Ulixertinib in Preclinical Pancreatic Cancer Models
inferredcites →https://doi.org/10.1177/1533033820962117openalex-extracted
Pancreatic Cancer: A Review of Risk Factors, Diagnosis, and Treatment
inferredcites →https://doi.org/10.1200/jco.2005.05.1490openalex-extracted
Randomized Phase III Trial of Gemcitabine Plus Cisplatin Compared With Gemcitabine Alone in Advanced Pancreatic Cancer
inferredcites →https://doi.org/10.1200/jco.2006.07.9525openalex-extracted
Erlotinib Plus Gemcitabine Compared With Gemcitabine Alone in Patients With Advanced Pancreatic Cancer: A Phase III Trial of the National Cancer Institute of Canada Clinical Trials Group
inferredcites →https://doi.org/10.1200/jco.2009.27.15_suppl.2500openalex-extracted
Interaction between sorafenib and erlotinib
inferredcites →https://doi.org/10.26434/chemrxiv-2024-zv92kopenalex-extracted
AI-driven discovery of synergistic drug combinations against pancreatic cancer
inferredcites →https://doi.org/10.3389/fbinf.2023.1328262openalex-extracted
A breast cancer-specific combinational QSAR model development using machine learning and deep learning approaches
inferredcites →https://doi.org/10.3389/fmed.2023.1086097openalex-extracted
Deep learning methods for drug response prediction in cancer: Predominant and emerging trends
inferredcites →https://doi.org/10.3389/fonc.2020.00041openalex-extracted
Neoadjuvant Treatment in Patients With Resectable and Borderline Resectable Pancreatic Cancer
inferredcites →https://doi.org/10.3390/ijms22105212openalex-extracted
Two Decades of 4D-QSAR: A Dying Art or Staging a Comeback?
inferredcites →https://doi.org/10.3390/life12081258openalex-extracted
Studies on Biological and Molecular Effects of Small-Molecule Kinase Inhibitors on Human Glioblastoma Cells and Organotypic Brain Slices
inferredcites →https://doi.org/10.3390/ph16020253openalex-extracted
Advances of Artificial Intelligence in Anti-Cancer Drug Design: A Review of the Past Decade
inferredcites →https://doi.org/10.6004/jnccn.2017.0131openalex-extracted
Pancreatic Adenocarcinoma, Version 2.2017, NCCN Clinical Practice Guidelines in Oncology
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