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Introduction to machine learning: k-nearest neighbors

Zhongheng Zhang • Annals of Translational Medicine (2016)

Machine learning techniques have been widely used in many scientific fields, but its use in medical literature is limited partly because of technical difficulties. k-nearest neighbors (kNN) is a simple method of machine learning. The articl...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.21037/atm.2016.03.37 PMC: 4916348

The challenge of studying perovskite solar cells’ stability with machine learning

Paolo Graniero, Paolo Graniero, Mark Khenkin, Hans Köbler et al. • Frontiers in Energy Research (2023)

Perovskite solar cells are the most dynamic emerging photovoltaic technology and attracts the attention of thousands of researchers worldwide. Recently, many of them are targeting device stability issues–the key challenge for this technolog...

DOAJ Open Access (DOAJ) DOI: 10.3389/fenrg.2023.1118654

Introduction to Machine Learning

Arvind Kumar Tiwari • IGI Global eBooks (2019)

Machine learning refers to the changes in systems that perform tasks associated with artificial intelligence. This chapter presents introduction types and application of machine learning. This chapter also presents the basic concepts relate...

OPENALEX DOI: https://doi.org/10.4018/978-1-7998-0414-7.ch003

Leveraging Cloud Technology for Personalized Multiple Sclerosis Care: A Comprehensive Data Management and Visualization Approach

Jose Manuel PINILLOS RUBIO, Minerva VIGUERA MORENO • Applied Medical Informatics (2024)

This project develops a cloud-based solution for securely managing clinical data and patient-reported outcomes (PROMs) for multiple sclerosis (MS) patients. Utilizing REDCap for data collection, we incorporated clinical outcomes and PROMs f...

DOAJ Open Access (DOAJ)

Machine Learning

Stephen Marsland • Chapman & Hall/CRC eBooks (2011)

Traditional books on machine learning can be divided into two groups- those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is re...

OPENALEX DOI: https://doi.org/10.1201/9781420067194

Machine Learning from Theory to Algorithms: An Overview

Jafar Ahmad Abed Alzubi, Anand Nayyar, Akshi Kumar • Journal of Physics Conference Series (2018)

The current SMAC (Social, Mobile, Analytic, Cloud) technology trend paves the way to a future in which intelligent machines, networked processes and big data are brought together. This virtual world has generated vast amount of data which i...

OPENALEX cc-by DOI: https://doi.org/10.1088/1742-6596/1142/1/012012

Machine learning in manufacturing: advantages, challenges, and applications

Thorsten Wuest, Daniel Weimer, Christopher Irgens, Klaus‐Dieter Thoben • Production & Manufacturing Research (2016)

The nature of manufacturing systems faces ever more complex, dynamic and at times even chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an efficient manner, it is essential to utilize all means av...

OPENALEX cc-by DOI: https://doi.org/10.1080/21693277.2016.1192517

Interactive machine learning

Jerry Alan Fails, Dan R. Olsen • ACM International Conference on Intelligent User Interfaces (IUI) (2003)

Perceptual user interfaces (PUIs) are an important part of ubiquitous computing. Creating such interfaces is difficult because of the image and signal processing knowledge required for creating classifiers. We propose an interactive machine...

OPENALEX DOI: https://doi.org/10.1145/604045.604056

Trinity: In-Database Near-Data Machine Learning Acceleration Platform for Advanced Data Analytics

Ji-Hoon Kim, Seunghee Han, Kwanghyun Park, Soo-Young Ji et al. • IEEE Access (2024)

The ability to perform machine learning (ML) tasks in a database management system (DBMS) is a new paradigm for conventional database systems as it enables advanced data analytics on top of well-established capabilities of DBMSs. However, t...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3347725