A systematic survey of computer-aided diagnosis in medicine: Past and present developments

被引:187
作者
Yanase, Juri [1 ]
Triantaphyllou, Evangelos [2 ]
机构
[1] Complete Decis LLC, Baton Rouge, LA 70810 USA
[2] Louisiana State Univ, Sch Elect Engn & Comp Sci, Div Comp Sci & Engn, Baton Rouge, LA 70803 USA
关键词
Computer-aided diagnosis; Computer-aided detection; Expert and intelligent systems; Computerized signal analysis; Segmentation; Classification; CONVOLUTIONAL NEURAL-NETWORKS; BREAST-CANCER; PULMONARY NODULES; PATTERN-CLASSIFICATION; AUTOMATED DETECTION; FEATURE-SELECTION; SEPSIS DIAGNOSIS; EXPERT-SYSTEMS; ADVERSE EVENTS; SOUND ANALYSIS;
D O I
10.1016/j.eswa.2019.112821
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort expended in the interface of medicine and computer science. As some CAD systems in medicine try to emulate the diagnostic decision-making process of medical experts, they can be considered as expert systems in medicine. Furthermore, CAD systems in medicine may process clinical data that can be complex and/or massive in size. They do so in order to infer new knowledge from data and use that knowledge to improve their diagnostic performance over time. Therefore, such systems can also be viewed as intelligent systems because they use a feedback mechanism to improve their performance over time. The main aim of the literature survey described in this paper is to provide a comprehensive overview of past and current CAD developments. This survey/review can be of significant value to researchers and professionals in medicine and computer science. There are already some reviews about specific aspects of CAD in medicine. However, this paper focuses on the entire spectrum of the capabilities of CAD systems in medicine. It also identifies the key developments that have led to today's state-of-the-art in this area. It presents an extensive and systematic literature review of CAD in medicine, based on 251 carefully selected publications. While medicine and computer science have advanced dramatically in recent years, each area has also become profoundly more complex. This paper advocates that in order to further develop and improve CAD, it is required to have well-coordinated work among researchers and professionals in these two constituent fields. Finally, this survey helps to highlight areas where there are opportunities to make significant new contributions. This may profoundly impact future research in medicine and in select areas of computer science. (C) 2019 Elsevier Ltd. All rights reserved.
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页数:25
相关论文
共 250 条
[1]  
Abbas A. K., 2009, SYNTHESIS LECT BIOME, V4, P1
[2]   Computer-aided pattern classification system for dermoscopy images [J].
Abbas, Qaisar ;
Celebi, M. Emre ;
Fondon, Irene .
SKIN RESEARCH AND TECHNOLOGY, 2012, 18 (03) :278-289
[3]  
ACCEPTED, 2020, US NEWS REL 2021 RAN
[4]   Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network [J].
Acharya, U. Rajendra ;
Fujita, Hamido ;
Lih, Oh Shu ;
Hagiwara, Yuki ;
Tan, Jen Hong ;
Adam, Muhammad .
INFORMATION SCIENCES, 2017, 405 :81-90
[5]  
Aggarwal C.C., 2015, The Data Mining, P237
[6]   Wavelet-Synchronization Methodology: A New Approach for EEG-Based Diagnosis of ADHD [J].
Ahmadlou, Mehran ;
Adeli, Hojjat .
CLINICAL EEG AND NEUROSCIENCE, 2010, 41 (01) :1-10
[7]   DIAGNOSTIC-TESTS-2 - PREDICTIVE VALUES .4. [J].
ALTMAN, DG ;
BLAND, JM .
BRITISH MEDICAL JOURNAL, 1994, 309 (6947) :102-102
[8]  
Ang KK, 2010, IEEE ENG MED BIO, P5549, DOI 10.1109/IEMBS.2010.5626782
[9]   Computerised Analysis of Telemonitored Respiratory Sounds for Predicting Acute Exacerbations of COPD [J].
Angel Fernandez-Granero, Miguel ;
Sanchez-Morillo, Daniel ;
Leon-Jimenez, Antonio .
SENSORS, 2015, 15 (10) :26978-26996
[10]  
[Anonymous], FDN ARTIFICIAL INTEL