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[HTML][HTML] Recent advancement in cancer detection using machine learning: Systematic survey of decades, comparisons and challenges
T Saba - Journal of infection and public health, 2020 - Elsevier
Cancer is a fatal illness often caused by genetic disorder aggregation and a variety of
pathological changes. Cancerous cells are abnormal areas often growing in any part of …
pathological changes. Cancerous cells are abnormal areas often growing in any part of …
[HTML][HTML] Facial emotion recognition using conventional machine learning and deep learning methods: current achievements, analysis and remaining challenges
AR Khan - Information, 2022 - mdpi.com
Facial emotion recognition (FER) is an emerging and significant research area in the pattern
recognition domain. In daily life, the role of non-verbal communication is significant, and in …
recognition domain. In daily life, the role of non-verbal communication is significant, and in …
Microscopic brain tumor detection and classification using 3D CNN and feature selection architecture
Brain tumor is one of the most dreadful natures of cancer and caused a huge number of
deaths among kids and adults from the past few years. According to WHO standard, the …
deaths among kids and adults from the past few years. According to WHO standard, the …
Brain tumor segmentation using K‐means clustering and deep learning with synthetic data augmentation for classification
Image processing plays a major role in neurologists' clinical diagnosis in the medical field.
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Brain tumor detection and multi‐classification using advanced deep learning techniques
A brain tumor is an uncontrolled development of brain cells in brain cancer if not detected at
an early stage. Early brain tumor diagnosis plays a crucial role in treatment planning and …
an early stage. Early brain tumor diagnosis plays a crucial role in treatment planning and …
[HTML][HTML] Ai in thyroid cancer diagnosis: Techniques, trends, and future directions
Artificial intelligence (AI) has significantly impacted thyroid cancer diagnosis in recent years,
offering advanced tools and methodologies that promise to revolutionize patient outcomes …
offering advanced tools and methodologies that promise to revolutionize patient outcomes …
Region extraction and classification of skin cancer: A heterogeneous framework of deep CNN features fusion and reduction
Cancer is one of the leading causes of deaths in the last two decades. It is either diagnosed
malignant or benign–depending upon the severity of the infection and the current stage. The …
malignant or benign–depending upon the severity of the infection and the current stage. The …
[HTML][HTML] Performance and limitation of machine learning algorithms for diabetic retinopathy screening: meta-analysis
Background Diabetic retinopathy (DR), whose standard diagnosis is performed by human
experts, has high prevalence and requires a more efficient screening method. Although …
experts, has high prevalence and requires a more efficient screening method. Although …
Deep learning model integrating features and novel classifiers fusion for brain tumor segmentation
Automatic and precise segmentation and classification of tumor area in medical images is
still a challenging task in medical research. Most of the conventional neural network based …
still a challenging task in medical research. Most of the conventional neural network based …
A comprehensive study of mobile-health based assistive technology for the healthcare of dementia and Alzheimer's disease (AD)
Assistive technology (AT) involvement in therapeutic treatment has provided simple and
efficient healthcare solutions to people. Within a short span of time, mobile health (mHealth) …
efficient healthcare solutions to people. Within a short span of time, mobile health (mHealth) …