Topics

Machine Learning Applications in Endocrinology and Metabolism Research: An Overview.

07:00 EST 1st March 2020 | BioPortfolio

Summary of "Machine Learning Applications in Endocrinology and Metabolism Research: An Overview."

Machine learning (ML) applications have received extensive attention in endocrinology research during the last decade. This review summarizes the basic concepts of ML and certain research topics in endocrinology and metabolism where ML principles have been actively deployed. Relevant studies are discussed to provide an overview of the methodology, main findings, and limitations of ML, with the goal of stimulating insights into future research directions. Clear, testable study hypotheses stem from unmet clinical needs, and the management of data quality (beyond a focus on quantity alone), open collaboration between clinical experts and ML engineers, the development of interpretable high-performance ML models beyond the black-box nature of some algorithms, and a creative environment are the core prerequisites for the foreseeable changes expected to be brought about by ML and artificial intelligence in the field of endocrinology and metabolism, with actual improvements in clinical practice beyond hype. Of note, endocrinologists will continue to play a central role in these developments as domain experts who can properly generate, refine, analyze, and interpret data with a combination of clinical expertise and scientific rigor.

Affiliation

Journal Details

This article was published in the following journal.

Name: Endocrinology and metabolism (Seoul, Korea)
ISSN: 2093-5978
Pages: 71-84

Links

DeepDyve research library

PubMed Articles [25302 Associated PubMed Articles listed on BioPortfolio]

What Is Machine Learning: a Primer for the Epidemiologist.

Machine learning is a branch of computer science that has the potential to transform epidemiological sciences. Amid a growing focus on "Big Data," it offers epidemiologists new tools to tackle problem...

Applications of Machine Learning Using Electronic Medical Records in Spine Surgery.

Developments in machine learning in recent years have precipitated a surge in research on the applications of artificial intelligence within medicine. Machine learning algorithms are beginning to impa...

Machine Learning for Analysis of Microscopy Images: A Practical Guide.

The explosive growth of machine learning has provided scientists with insights into data in ways unattainable using prior research techniques. It has allowed the detection of biological features that ...

A Survey of Optimization Methods From a Machine Learning Perspective.

Machine learning develops rapidly, which has made many theoretical breakthroughs and is widely applied in various fields. Optimization, as an important part of machine learning, has attracted much att...

How Machine Learning Will Transform Biomedicine.

This Perspective explores the application of machine learning toward improved diagnosis and treatment. We outline a vision for how machine learning can transform three broad areas of biomedicine: clin...

Clinical Trials [6462 Associated Clinical Trials listed on BioPortfolio]

Lung Nodule Imaging Biobank for Radiomics and AI Research

This study will collect retrospective CT scan images and clinical data from patients with incidental lung nodules seen in hospitals across London. We will research whether we can use machi...

Test-enhanced Learning to Prepare for Future Learning in Endocrinology

The use of test-enhanced learning with causal connection and in preparation for future learning has been used in health educational setting with positive results. However, most studies wer...

Heuristics, Algorithms and Machine Learning: Evaluation & Testing in Radiation Therapy

The Hamlet.rt study is a prospective data collection and patient questionnaire study for patients undergoing image-guided radiotherapy with curative intent. The aim of the study is to use...

The HEADWIND-Study

To analyse driving behavior of individuals with type 1 diabetes in eu- and progressive hypoglycaemia using a validated research driving simulator. Based on the driving variables provided b...

Machine Learning From Fetal Flow Waveforms to Predict Adverse Perinatal Outcomes

The aim of this study is to get a proof of concept for using a computational model of fetal haemodynamics, combined with machine learning based on Doppler patterns of the fetal cardiovascu...

Medical and Biotech [MESH] Definitions

A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of unlabeled paired input-output training (sample) data.

A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of labeled paired input-output training (sample) data.

SUPERVISED MACHINE LEARNING algorithm which learns to assign labels to objects from a set of training examples. Examples are learning to recognize fraudulent credit card activity by examining hundreds or thousands of fraudulent and non-fraudulent credit card activity, or learning to make disease diagnosis or prognosis based on automatic classification of microarray gene expression profiles drawn from hundreds or thousands of samples.

A type of ARTIFICIAL INTELLIGENCE that enable COMPUTERS to independently initiate and execute LEARNING when exposed to new data.

Process in which individuals take the initiative, in diagnosing their learning needs, formulating learning goals, identifying resources for learning, choosing and implementing learning strategies and evaluating learning outcomes (Knowles, 1975)

Quick Search


DeepDyve research library

Relevant Topics

Endocrinology
Diabetes Diabetes Endocrine Disorders Obesity Oxycontin Renal Disease Thyroid Disorders Endocrinology is the study of the endocrine glands and the hormones that they secrete (Oxford Medical Dictionary). There are several g...

Collaborations in biotechnology
Commercial and academic collaborations are used throughout the biotechnology and pharmaceutical sector to enhance research and product development. Collaborations can take the form of research and evaluation agreements, licensing, partnerships etc. ...


Searches Linking to this Article