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In this section, we discuss two basic protocols used for transforming the process into AI-based [11].

1 (i) Expert system

2 (ii) ANN-based model

The expert system is a technique that is followed for transforming the conventional diagnosis process into an AI-assisted. It outlines the step by step process involved from input to output by framing conditional protocols. The protocols are developed in domain wise by the clinician’s experience and knowledge. Artificial Neural Networks (ANNs) are a parallel processing technique or model which consists of neurons as processing elements, wherein neurons are linked and arranged layer-wise. Layers are also connected. The neurons are assigned with a functional unit and weight value based on the type of application. Weights of the processing could be varied to reach the specified result by applying a backpropagation algorithm. The parallel processing capability of ANN makes it more convenient method for medical applications. ANN-based model is illustrated in Figure 1.4.

Other than a medical diagnosis, ANN is used for analyzing the radiographs in radiology. Gamma, CT, ultrasound, and MRI images are manipulated using ANN. The digitized inputs are given to ANN, processed by inner layers of ANN, and produce appropriate outputs. Orthopedic injuries are successfully identified by trained ANN. In cytology, ANN is used to classify or group the abnormal cells from the specimen cell. It has also been utilized for interpreting EEG and ECG signals. Accuracy of performance on waveform analysis, identification of abnormalities, and data interpretation by ANN is very much useful and reduces the human intervention.

Figure 1.4 ANN-based diagnosis model.