A Fuzzy Logical Model of Computer-Assisted Medical Diagnosis

A model of a computer-assisted diagnostic system using fuzzy subsets has been developed. The physician documents symptom—diagnosis presence relationships and symptom—diagnosis conclusiveness relationships by means of labels of the fuzzy subsets never, almost never, very very seldom, very seldom, seldom, more or less seldom, not known, more or less often, often, very often, very very often, almost always, always. Symptoms are regarded as fuzzy subsets of reference sets. The reference set includes all values the symptom may assume. The degree of membership of a value in the fuzzy subset of a symptom is calculated when the patient’s symptom pattern is available. By means of compositions of fuzzy relations, four different diagnostic indications are determined for every diagnosis under consideration: presence indication, conclusiveness indication, non-presence indication and non-symptom presence indication. By performing the diagnostic process, the system provides the physician with proven diagnoses, excluded diagnoses and diagnostic hints, including reasons for the diagnoses displayed. Proposals for further investigations may also be requested.

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The Process of Medical Diagnosis: Routes of Mathematical Investigations

Methods of Information in Medicine ◽

10.1055/s-0038-1636611 ◽

1978 ◽

Vol 17 (01) ◽

pp. 1-10 ◽

Cited By ~ 7

Author(s):

P. Tautu ◽

G. Wagner

Keyword(s):

Decision Theory ◽

Medical Diagnosis ◽

Pattern Analysis ◽

Logical Probability ◽

Inquiry Process ◽

Fuzzy Subsets

This paper is an analysis of the most important mathematical aspects of medical diagnosis: logical probability, rationality and decision theory, gambling models, pattern analysis, hazy and fuzzy subsets theory and, finally, the stochastic inquiry process.

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Evaluation of automated fundus photograph analysis algorithms for detecting microaneurysms, haemorrhages and exudates, and of a computer-assisted diagnostic system for grading diabetic retinopathy

Diabetes & Metabolism ◽

10.1016/j.diabet.2010.01.002 ◽

2010 ◽

Vol 36 (3) ◽

pp. 213-220 ◽

Cited By ~ 54

Author(s):

B. Dupas ◽

T. Walter ◽

A. Erginay ◽

R. Ordonez ◽

N. Deb-Joardar ◽

...

Keyword(s):

Diabetic Retinopathy ◽

Diagnostic System ◽

Computer Assisted ◽

Fundus Photograph

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Artificial intelligence assisted electrocardiography for early diagnosis of thyrotoxic periodic paralysis

Journal of the Endocrine Society ◽

10.1210/jendso/bvab120 ◽

2021 ◽

Author(s):

Chin Lin ◽

Chin-Sheng Lin ◽

Ding-Jie Lee ◽

Chia-Cheng Lee ◽

Sy-Jou Chen ◽

...

Keyword(s):

Artificial Intelligence ◽

Early Diagnosis ◽

Validation Cohort ◽

Laboratory Data ◽

Diagnostic System ◽

Periodic Paralysis ◽

Medical Emergency ◽

Diagnostic Process ◽

Routine Laboratory ◽

Thyrotoxic Periodic Paralysis

Abstract CONTEXT Thyrotoxic periodic paralysis (TPP) characterized by acute weakness, hypokalemia and hyperthyroidism is a medical emergency with a great challenge in early diagnosis since most TPP patients do not have overt symptoms. OBJECTIVE To assess artificial intelligence (AI)-assisted electrocardiography (ECG) combined with routine laboratory data in the early diagnosis of TPP. METHODS A deep learning model (DLM) based on ECG12Net, an 82-layer convolutional neural network, was constructed to detect hypokalemia and hyperthyroidism. The development cohort consisted of 39 ECGs from patients with TPP and 502 ECGs of hypokalemic control; the validation cohort consisted of 11 ECGs of TPP and 36 ECGs of non-TPP with weakness. The AI-ECG based TPP diagnostic process was then consecutively evaluated in 22 male patients with TTP-like features. RESULTS In the validation cohort, the DLM-based ECG system detected all cases of hypokalemia in TPP patients with a mean absolute error of 0.26 mEq/L and diagnosed TPP with an area under curve (AUC) of ~80%, surpassing the best standard ECG parameter (AUC=0.7285 for the QR interval). Combining the AI predictions with the estimated glomerular filtration rate (eGFR) and serum chloride (Cl -) boosted the diagnostic accuracy of the algorithm to AUC 0.986. In the prospective study, the integrated AI and routine laboratory diagnostic system had a PPV of 100% and F-measure 87.5%. CONCLUSIONS An AI-ECG system reliably identifies hypokalemia in patients with paralysis and integration with routine blood chemistries provides valuable decision support for the early diagnosis of TPP.

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METHODOLOGICAL PLATFORM FOR DIAGNOSING ECONOMIC ACTIVITY OF TRADE ENTERPRISES

Scientific opinion Economics and Management ◽

10.32836/2521-666x/2021-73-3 ◽

2021 ◽

Author(s):

Nataliia Kashchena

Keyword(s):

Economic Activity ◽

Consumer Preferences ◽

Diagnostic System ◽

Component Composition ◽

Business Environment ◽

Information Support ◽

Diagnostic Process ◽

Practical Implementation ◽

Diagnostic Study ◽

Management Decisions

The article substantiates the theoretical and methodological principles of forming a methodological platform for diagnosing the economic activity of a trading enterprise as a basis for implementing a diagnostic process focused on the formation of special information used for making management decisions. It is noted that the diagnostics of economic activity of a trade enterprise as a component of management is a set of actions aimed at providing information support to management that requires from management staff systemic theoretical knowledge and applied skills of instrumental methods of identifying economic activity, trends, assessing causes of change, forecasting and the practical implementation of the identified opportunities to increase it, taking into account changes in the business environment and the needs of stakeholders. It is proved that the efficiency of diagnostics of economic activity is ensured by the appropriate methodology, which normalizes the organization of the diagnostic process, procedures and operations into a holistic system with clearly defined prerequisites, component composition and process of their implementation. The methodology framework is determined and the problem tree analysis of the formation of the methodological platform for diagnosing economic activity of trade enterprises is carried out. The architectural structure of the system of diagnosing economic activity of a trade enterprise through a combination of functional and support components, which are defining for productive functioning of the mechanism and efficiency of the diagnostic process, is considered. The sequence of stages of the diagnostic process and procedural aspects of verification of each of them is determined. It is proved that the efficiency of the process of diagnostics of economic activity is provided by an appropriate mechanism, which through a set of rules, special tools, methods and techniques launches and maintains a diagnostic study, thus ensuring the integrity of the diagnostic system. A conceptual model of the methodological platform for diagnosing economic activity of trade enterprises is developed, which integrates the identified preconditions and component composition of the methodology on the basis of systematicity and ensures the effectiveness of the process of obtaining information for management. The developed model allows to deepen and expand understanding of the essence of the system for diagnosing economic activity of the enterprise, its structure, regularities, the purposes and tasks of functioning, to provide high-quality instrumental support of the realization of diagnostic procedures and operations, to streamline the process of reception of the information for making management decisions focused on achieving target parameters of development of economic activity taking into account the dynamic changes in the business environment and consumer preferences.

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