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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...
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Article
Achieving highly efficient breast ultrasound tumor classification with deep convolutional neural networks
Ultrasound imaging is one of the common modalities used nowadays during radiological screening of breast cancer. A novel residual deep convolutional neural network (DCNN) is proposed in this work to perform au...
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Article
Feature fusion based machine learning pipeline to improve breast cancer prediction
Early detection of malignant breast cancer can significantly improve the survival chances of the involved patients. Analysis of a non-invasive and non-radioactive modality like ultrasound imaging with the help...
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Chapter and Conference Paper
Pre-trained EfficientNet-B0 with Adjusted Optimizer, Learning Rate and Image Size to Improve Diabetic Foot Ulcers Diagnosis
Diabetic Foot Ulcers (DFUs) are a major complication encountered by diabetic patients. The timely diagnosis of it helps in avoiding lower limbs or foot amputation. However, the traditional diagnosis process of...
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Chapter and Conference Paper
Machine Learning Based Automatic Prediction of Parkinson’s Disease Using Speech Features
Parkinson’s disease is a severe neurodegenerative disease where primarily the motor system of the human body gets affected. It is currently one of the leading causes of disability around the world. Although cu...
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Chapter and Conference Paper
Binary Particle Swarm Optimization Based Feature Selection (BPSO-FS) for Improving Breast Cancer Prediction
Breast cancer is currently one of the leading causes of cancer-related deaths among women around the world. Although the severity of the disease is undeniable, an efficient early diagnosis of the disease can l...
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Chapter
Deep Learning Techniques Dealing with Diabetes Mellitus: A Comprehensive Study
Deep learning (DL) is an emerging technology in solving various real-life problems in the most efficient way. The increasing computational power makes it capable to handle large amounts of data without much hu...
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Article
Intelligent Local Search for Test Case Minimization
For performing efficient regression testing, minimization of test suites is one of the primary approaches. Various kinds of test case minimization techniques have been proposed in the past, in order to do this...
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Chapter and Conference Paper
Genetic Algorithm Based Selection of Appropriate Biomarkers for Improved Breast Cancer Prediction
One of the most common types of cancer among women is Breast Cancer which amounts to a staggeringly high number of deaths every year. According to the World Health Organization (WHO), the projected number of B...
