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Chapter and Conference Paper
Artificial Intelligence in Radiological COVID-19 Detection: A State-of-the-Art Review
The requirement for the fast and accurate detection of COVID-19 is of high importance to control the spread of the disease. Recently, Artificial Intelligence and Deep Learning-based techniques have shown great...
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Chapter and Conference Paper
Analysis of Synthetic Data Generation Techniques in Diabetes Prediction
The problem of inadequate and class imbalanced data is one of the major problems in the classification tasks. Therefore applying synthetic data generation (SDG) approaches to handle class imbalances can be use...
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Chapter and Conference Paper
ADASemSeg: An Active Learning Based Data Adaptation Strategy for Improving Cross Dataset Breast Tumor Segmentation
Highly efficient breast ultrasound (BUS) segmentation models trained and tested on samples from one dataset do not usually have a high performance when inference is done on samples from other datasets. The sol...