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Design and Tuning of Fuzzy Rule-Based Systems for Medical Diagnosis
Published in Horia-Nicolai Teodorescu, Abraham Kandel, Lakhmi C. Jain, FUZZY and NEURO-FUZZY SYSTEMS in MEDICINE, 2017
If the number of input variables (xi) is higher than the “magic number 7±2” [11], it is difficult for an expert to compile all the if-then rules into a single matrix of knowledge. In such a case, it is desirable to use a hierarchical presentation of an input-output model, and to compile if-then rules for all classes of the hierarchy. According to [2] the most usual hierarchy in medical diagnosis is: (0) symptoms and signs → (1) group of symptoms → (2) disease → (3) family of diseases. An example of hierarchical presentation of some expert knowledge is shown in Section 6.
Artificial intelligence: a survey on evolution, models, applications and future trends
Published in Journal of Management Analytics, 2019
Robot is an important product of AI. It has been widely used in space exploration, warehouse management, medical diagnosis. For example, in space exploration, due to the fragility of the human body, there is a large amount of radiation in many places. People in these areas cannot enter, so robots can be used instead of humans to detect and explore. AI developed a warehouse management system in logistics warehousing applications. Warehouse management can use the camera, temperature and humidity sensors, mold sensors to obtain warehouse information, provide this information to warehouse administrators in real time, and analyze historical warehouse data to ensure warehouse operations and safety. Medical diagnosis has always been an important area of information development and application. In order to improve the level of medical diagnosis, pattern recognition technology is introduced in CT image processing, and the contours of various organs in the image are found by combining the characteristics of various organs of the human body. The introduction of AI into medical diagnosis can greatly improve the level of treatment and medical performance.
Malignant Mesothelioma Disease Diagnosis using Data Mining Techniques
Published in Applied Artificial Intelligence, 2018
Diagnosis usually appears when a patient visits the doctor to have symptoms checked out. Patients may be met with shortness of breath, pain in the chest or back, painful, persistent coughing, or any number of other symptoms, none of which immediately alert the doctor to a diagnosis of mesothelioma (Mesothelioma News (accepted: June 29, 2011)). Clinically many studies were done regarding MM disease in south east of Turkey (Tanrikulu et al. 2006; Senyiğit et al. 2000(a); Senyiğit et al. 2000(b)). There are many studies on MM disease diagnosis using artificial intelligence techniques also, such as probability neural networks (PNNs), learning vector quantization (LVQ) (Orhan et al. 2011), artificial immune system (AIS) and multilayer neural network (MLNN) (Orhan, Tanrikulu, and Abakay 2015) with prognostic data. MM disease diagnosis is an important classification issue. Classification is often a very important part of process in many different fields like medicine. The use of artificial intelligence methods in medical diagnosis has been increasing gradually. There is no doubt that evaluations of data taken from patients and decisions of experts are the most important factors in diagnosis. However, sometimes different artificial intelligence techniques need for classification disease (Kadoz et al. 2008).
K–L divergence-based distance measure for Pythagorean fuzzy sets with various applications
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2023
Naveen Kumar, Anjali Patel, Juthika Mahanta
The diagnosis of a disease or condition that caused a person’s symptoms and signs is known as a medical diagnosis. It is most often referred to as a diagnosis with implicit medical context. So, in this section, we present a diagnosis problem to define which patient is suffering from which disease with the help of the proposed distance measure.