BACKGROUND: The role of retrospective analysis has been evolved greatly in cancer research. We undertook this meta-analysis to evaluate the diagnostic value of Neural networks (NNs) in Fine needle aspiration cytological (FNAC) image of cancer.
OBJECTIVE: Early disease screening and diagnosis are important for improving patient survival. Thus, identifying early predictive features of disease is necessary. This paper presents a comprehensive comparative analysis of different Machine Learning...
Computer-aided diagnosis systems have been developed to assist doctors in diagnosing thyroid nodules to reduce errors made by traditional diagnosis methods, which are mainly based on the experiences of doctors. Therefore, the performance of such syst...
The current standard for evaluating axillary nodal burden in clinically node negative breast cancer is sentinel lymph node biopsy (SLNB). However, the accuracy of SLNB to detect nodal stage N2-3 remains debatable. Nomograms can help the decision-mak...
BACKGROUND: The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) comprises 6 categories used for the diagnosis of thyroid fine-needle aspiration biopsy (FNAB). Each category has an associated risk of malignancy, which is important in the ...
PURPOSE: To determine whether deep learning-based algorithms applied to breast MR images can aid in the prediction of occult invasive disease following the diagnosis of ductal carcinoma in situ (DCIS) by core needle biopsy.
Nowadays, the most frequent cancer in women is breast cancer (malignant tumor). If breast cancer is detected at the beginning stage, it can often be cured. Many researchers proposed numerous methods for early prediction of this Cancer. In this paper,...
Journal of the American Society of Cytopathology
Mar 25, 2019
Artificial intelligence (AI) has made impressive strides recently in interpreting complex images, thanks to improvements in deep learning techniques and increasing computational power. Researchers have started applying these advanced techniques to pa...
Fine needle aspiration cytology (FNAC) entails using a narrow gauge (25-22 G) needle to collect a sample of a lesion for microscopic examination. It allows a minimally invasive, rapid diagnosis of tissue but does not preserve its histological archite...
Deep learning neural network models such as multilayer perceptron (MLP) and convolutional neural network (CNN) are novel and attractive artificial intelligence computing tools. However, evaluation of the performance of these methods is not readily av...
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