Search Result "Machine-to-Machine interaction."


Review Article

Recent Advances in the Machine Learning-Based Drug-Target Interaction Prediction

Journal: Current Drug Metabolism
Volume: 20 Issue: 3 Year: 2019 Page: 194-202
Author(s): Wen Zhang,Weiran Lin,Ding Zhang,Siman Wang,Jingwen Shi,Yanqing Niu

Review Article

Recent Advances in Predicting ncRNA-Protein Interactions Based on Machine Learning

Journal: Current Chinese Science
Volume: 1 Issue: 5 Year: 2021 Page: 513-522
Author(s): Jingjing Wang,Yanpeng Zhao,Xiaoqian Huang,Yi Shi,Jianjun Tan

Machine Learning in Health Care

Ebook: Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare
Volume: 1 Year: 2021
Author(s): Ilker Ozsahin,Dilber Uzun Ozsahin,Basil Bartholomew Duwa
Doi: 10.2174/9781681088716121010004

Review Article

Application of Machine Learning Approaches for Protein-protein Interactions Prediction

Journal: Medicinal Chemistry
Volume: 13 Issue: 6 Year: 2017 Page: 506-514
Author(s): Mengying Zhang,Qiang Su,Yi Lu,Manman Zhao,Bing Niu

Support Vector Machine

Ebook: Introduction to Machine Learning with Python
Volume: 1 Year: 2023
Author(s):
Doi: 10.2174/9789815124422123010006

Review Article

Predicting lncRNA-protein Interactions by Machine Learning Methods: A Review

Journal: Current Bioinformatics
Volume: 15 Issue: 8 Year: 2020 Page: 831-840
Author(s): Zhi-Ping Liu

Analysis of Machine Learning Algorithms in Healthcare

Ebook: Intelligent Technologies for Automated Electronic Systems
Volume: 1 Year: 2024
Author(s):
Doi: 10.2174/9789815179514124010018

Revolutionizing Healthcare: The Power of Machine Learning

Ebook: Prediction in Medicine: The Impact of Machine Learning on Healthcare
Volume: 1 Year: 2024
Author(s):
Doi: 10.2174/9789815305128124010015

Machine Learning Techniques and their Applications: Survey

Ebook: Handbook of Artificial Intelligence
Volume: 1 Year: 2023
Author(s):
Doi: 10.2174/9789815124514123010003

Prediction using Machine Learning

Ebook: Handbook of Artificial Intelligence
Volume: 1 Year: 2023
Author(s):
Doi: 10.2174/9789815124514123010005

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