Literature DB >> 31601480

Machine Learning and Deep Learning in Medical Imaging: Intelligent Imaging.

Geoff Currie1, K Elizabeth Hawk2, Eric Rohren3, Alanna Vial4, Ran Klein5.   

Abstract

Artificial intelligence (AI) in medical imaging is a potentially disruptive technology. An understanding of the principles and application of radiomics, artificial neural networks, machine learning, and deep learning is an essential foundation to weave design solutions that accommodate ethical and regulatory requirements, and to craft AI-based algorithms that enhance outcomes, quality, and efficiency. Moreover, a more holistic perspective of applications, opportunities, and challenges from a programmatic perspective contributes to ethical and sustainable implementation of AI solutions.
Copyright © 2019. Published by Elsevier Inc.

Entities:  

Keywords:  Medical imaging; artificial intelligence; artificial neural network; convolutional neural network; deep learning

Year:  2019        PMID: 31601480     DOI: 10.1016/j.jmir.2019.09.005

Source DB:  PubMed          Journal:  J Med Imaging Radiat Sci        ISSN: 1876-7982


  32 in total

1.  Development of a multi-stage model for intelligent and quantitative appraising of skeletal maturity using cervical vertebras cone-beam CT images of Chinese girls.

Authors:  Lizhe Xie; Wen Tang; Iman Izadikhah; Zhenqi Zhao; Yang Zhao; Hu Li; Bin Yan
Journal:  Int J Comput Assist Radiol Surg       Date:  2022-01-04       Impact factor: 2.924

Review 2.  Radiomics: a primer on high-throughput image phenotyping.

Authors:  Kyle J Lafata; Yuqi Wang; Brandon Konkel; Fang-Fang Yin; Mustafa R Bashir
Journal:  Abdom Radiol (NY)       Date:  2021-08-25

3.  Machine Learning-Assisted Ensemble Analysis for the Prediction of Acute Pancreatitis with Acute Kidney Injury.

Authors:  Yi Yang; Wei Xiao; Xingtai Liu; Yan Zhang; Xin Jin; Xiao Li
Journal:  Int J Gen Med       Date:  2022-05-17

Review 4.  Artificial Intelligence, Healthcare, Clinical Genomics, and Pharmacogenomics Approaches in Precision Medicine.

Authors:  Habiba Abdelhalim; Asude Berber; Mudassir Lodi; Rihi Jain; Achuth Nair; Anirudh Pappu; Kush Patel; Vignesh Venkat; Cynthia Venkatesan; Raghu Wable; Matthew Dinatale; Allyson Fu; Vikram Iyer; Ishan Kalove; Marc Kleyman; Joseph Koutsoutis; David Menna; Mayank Paliwal; Nishi Patel; Thirth Patel; Zara Rafique; Rothela Samadi; Roshan Varadhan; Shreyas Bolla; Sreya Vadapalli; Zeeshan Ahmed
Journal:  Front Genet       Date:  2022-07-06       Impact factor: 4.772

5.  A multi-resolution model for histopathology image classification and localization with multiple instance learning.

Authors:  Jiayun Li; Wenyuan Li; Anthony Sisk; Huihui Ye; W Dean Wallace; William Speier; Corey W Arnold
Journal:  Comput Biol Med       Date:  2021-02-10       Impact factor: 4.589

Review 6.  Machine learning for sperm selection.

Authors:  Jae Bem You; Christopher McCallum; Yihe Wang; Jason Riordon; Reza Nosrati; David Sinton
Journal:  Nat Rev Urol       Date:  2021-05-17       Impact factor: 14.432

7.  An Application of Machine Learning That Uses the Magnetic Resonance Imaging Metric, Mean Apparent Diffusion Coefficient, to Differentiate between the Histological Types of Ovarian Cancer.

Authors:  Heekyoung Song; Seongeun Bak; Imhyeon Kim; Jae Yeon Woo; Eui Jin Cho; Youn Jin Choi; Sung Eun Rha; Shin Ah Oh; Seo Yeon Youn; Sung Jong Lee
Journal:  J Clin Med       Date:  2021-12-31       Impact factor: 4.241

Review 8.  Artificial Intelligence in Health Care: Current Applications and Issues.

Authors:  Chan Woo Park; Sung Wook Seo; Noeul Kang; BeomSeok Ko; Byung Wook Choi; Chang Min Park; Dong Kyung Chang; Hwiyoung Kim; Hyunchul Kim; Hyunna Lee; Jinhee Jang; Jong Chul Ye; Jong Hong Jeon; Joon Beom Seo; Kwang Joon Kim; Kyu Hwan Jung; Namkug Kim; Seungwook Paek; Soo Yong Shin; Soyoung Yoo; Yoon Sup Choi; Youngjun Kim; Hyung Jin Yoon
Journal:  J Korean Med Sci       Date:  2020-11-02       Impact factor: 2.153

Review 9.  Fit-for-Purpose Biometric Monitoring Technologies: Leveraging the Laboratory Biomarker Experience.

Authors:  Alan Godfrey; Benjamin Vandendriessche; Jessie P Bakker; Cheryl Fitzer-Attas; Ninad Gujar; Matthew Hobbs; Qi Liu; Carrie A Northcott; Virginia Parks; William A Wood; Vadim Zipunnikov; John A Wagner; Elena S Izmailova
Journal:  Clin Transl Sci       Date:  2020-08-25       Impact factor: 4.689

10.  Detection of Postural Control in Young and Elderly Adults Using Deep and Machine Learning Methods with Joint-Node Plots.

Authors:  Posen Lee; Tai-Been Chen; Chi-Yuan Wang; Shih-Yen Hsu; Chin-Hsuan Liu
Journal:  Sensors (Basel)       Date:  2021-05-05       Impact factor: 3.576

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