RETRACTED ARTICLE: Machine intelligent diagnostic system (MIDs): an instance of medical diagnosis of tuberculosis

The article aims to review, analyze, design and implement a philosophy of medical diagnosis by artificial intelligence (AI) and soft computing techniques. The theme of the paper is that there are abundant corruptions in therapeutic judgment; in its place of appropriate diagnosis, majority practition...

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Bibliographic Details
Published in:Neural computing & applications 2020-10, Vol.32 (19), p.15585-15595
Main Authors: Das, Sumit, Sanyal, Manas Kumar
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Cost analysis
Data Mining and Knowledge Discovery
Diagnostic systems
Fuzzy logic
Image Processing and Computer Vision
Medical diagnosis
Original Article
Physicians
Probability and Statistics in Computer Science
Prototypes
Signs and symptoms
Soft computing
Citations: Items that this one cites
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Summary:The article aims to review, analyze, design and implement a philosophy of medical diagnosis by artificial intelligence (AI) and soft computing techniques. The theme of the paper is that there are abundant corruptions in therapeutic judgment; in its place of appropriate diagnosis, majority practitioners go behind the narrow path by trapping the people at a serious phase. The ordinary community suffers deficient in diagnosis for higher investigative costs as well as the lack of certified practitioners. This article proposes some AI techniques to eradicate this lacuna by designing a prototype. The proposed prototype here termed as machine intelligent diagnostic system (MIDs), which has the capability of learning, thinking, reasoning and managing uncertainty as a real-world doctor. The model structured according to AI techniques considers the different cases of the disease to implement it. This article analyzes the shortcoming of MIDs, which can perform as a doctor to serve society as regular fashion as well as at the time of crisis as a crisis-manager. The degrees of the acuteness of patients’ symptoms are perceived by a membership function, which is used to tackle the emotion of the patients, and a fuzzy logic membership function is being used to calculate probabilities of diseases. Finally, this work finds smart results of MIDs, which can serve as doctors to some extent to compensate for the crisis of doctor in the universe.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-020-04894-8