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Field: AI in cancer detection

Federated Machine Learning for Detection of Skin Diseases and Enhancement of Internet of Medical Things (IoMT) Security

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Md. Nazmul Hossen, Vijayakumari Panneerselvam, Deepika Koundal, Kawsar Ahmed et al.

Journal: IEEE Journal of Biomedical and Health Informatics
Year: 2022
Citations: 154

Human skin disease, the most infectious dermatological ailment globally, is initially diagnosed by sight. Some clinical screening and dermoscopic analysis of skin biopsies and scrapings for accurate classification are medically compulsory. Classification of skin diseases using medical images is more...

Health SciencesMedicineOncology
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Transfer learning with fine-tuned deep CNN ResNet50 model for classifying COVID-19 from chest X-ray images

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Md. Belal Hossain, Shahriar Iqbal, Md. Monirul Islam, Md. Nasim Akhtar et al.

Journal: Informatics in Medicine UnlockedYear: 2022Citations: 153

COVID-19 cases are putting pressure on healthcare systems all around the world. Due to the lack of available testing kits, it is impractical for screening every patient with a respiratory ailment using traditional methods (RT-PCR). In addition, the tests have a high turn-around time and low sensitiv...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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An approach for multiclass skin lesion classification based on ensemble learning

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Zillur Rahman, Md. Sabir Hossain, Md. Rabiul Islam, Md. Mynul Hasan et al.

Journal: Informatics in Medicine UnlockedYear: 2021Citations: 151

Skin cancer is recognized as the most common kind of cancer in the world. It could be deadly if not identified at the primary stage, which makes early detection very crucial. It is possible to identify it with the naked eye, but high inter-class similarity and intra-class variations make it too hard...

Health SciencesMedicineOncologyOpen Access
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A Hybrid Dependable Deep Feature Extraction and Ensemble-Based Machine Learning Approach for Breast Cancer Detection

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Selina Sharmin, Tanvir Ahammad, Md. Alamin Talukder, Partho Ghose

Journal: IEEE AccessYear: 2023Citations: 146

Breast cancer is a prevalent and life-threatening disease that requires effective detection and diagnosis methods to improve patient outcomes. Deep learning (DL) and machine learning (ML) techniques have emerged as powerful tools in breast cancer detection, offering benefits such as improved accurac...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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A systematic review of deep learning data augmentation in medical imaging: Recent advances and future research directions

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Tauhidul Islam, Md Sadman Hafiz, Jamin Rahman Jim, Md. Mohsin Kabir et al.

Journal: Healthcare AnalyticsYear: 2024Citations: 144

Data augmentation involves artificially expanding a dataset by applying various transformations to the existing data. Recent developments in deep learning have advanced data augmentation, enabling more complex transformations. Especially vital in the medical domain, deep learning-based data augmenta...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Malignant and Benign Breast Cancer Classification using Machine Learning Algorithms

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Sharmin Ara, Annesha Das, Ashim Dey

Year: 2021Citations: 140

At the moment, the most prevalent form of cancer diagnosed in women across the globe is breast cancer. It develops in the breast tissue and is one of the most frequent causes of women's death. This cancer can be cured if it is diagnosed at preliminary stage. Malignant and benign are two types of tum...

Physical SciencesComputer ScienceArtificial Intelligence
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Breast Cancer Risk Prediction using XGBoost and Random Forest Algorithm

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Sajib Kabiraj, M. Raihan, Nasif Alvi, Marina Afrin et al.

Year: 2020Citations: 140

Breast cancer is as one of the common and serious cause of death among women globally. This is a disease where the cells grow out of control inside the breast. Family History of cancer disease, physical inactivity, psychological stress, increase in breast size are the risk factors of breast cancer. ...

Health SciencesMedicineRadiology, Nuclear Medicine and Imaging
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A survey, review, and future trends of skin lesion segmentation and classification

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Md. Kamrul Hasan, Md. Asif Ahamad, Choon Hwai Yap, Guang Yang

Journal: Computers in Biology and MedicineYear: 2023Citations: 139

The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion analysis is an emerging field of research that has the potential to alleviate the burden and cost of skin cancer screening. Researchers have recently indicated increasing interest in developing such CAD systems, with the intent...

Health SciencesMedicineOncologyOpen Access
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A Current Review of Machine Learning and Deep Learning Models in Oral Cancer Diagnosis: Recent Technologies, Open Challenges, and Future Research Directions

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Shriniket Dixit, Anant Kumar, Kathiravan Srinivasan

Journal: DiagnosticsYear: 2023Citations: 137

Cancer is a problematic global health issue with an extremely high fatality rate throughout the world. The application of various machine learning techniques that have appeared in the field of cancer diagnosis in recent years has provided meaningful insights into efficient and precise treatment deci...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Skin Cancer Detection Using Convolutional Neural Network

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Mahamudul Hasan, Surajit Das Barman, Samia Islam, Ahmed Wasif Reza

Year: 2019Citations: 137

Skin cancer is an alarming disease for mankind. The necessity of early diagnosis of the skin cancer have been increased because of the rapid growth rate of Melanoma skin cancer, itś high treatment costs, and death rate. This cancer cells are detected manually and it takes time to cure in most of the...

Health SciencesMedicineOncology
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Generative Adversarial Networks (GANs) in Medical Imaging: Advancements, Applications, and Challenges

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Showrov Islam, M Aziz, Hadiur Rahman Nabil, Jamin Rahman Jim et al.

Journal: IEEE AccessYear: 2024Citations: 132

Generative Adversarial Networks are a class of artificial intelligence algorithms that consist of a generator and a discriminator trained simultaneously through adversarial training. GANs have found crucial applications in various fields, including medical imaging. In healthcare, GANs contribute by ...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Detection of lung cancer from CT image using image processing and neural network

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Mohammad Badrul Alam Miah, Mohammad Abu Yousuf

Year: 2015Citations: 130

Detection of lung cancer is the most interesting research area of researcher's in early stages. The proposed system is designed to detect lung cancer in premature stage in two stages. The proposed system consists of many steps such as image acquisition, preprocessing, binarization, thresholding, seg...

Health SciencesMedicinePulmonary and Respiratory Medicine
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Alzheimer’s Patient Analysis Using Image and Gene Expression Data and Explainable-AI to Present Associated Genes

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Md. Sarwar Kamal, Aden Northcote, Linkon Chowdhury, Nilanjan Dey et al.

Journal: IEEE Transactions on Instrumentation and MeasurementYear: 2021Citations: 127

There are more than 10 million new cases of Alzheimer's patients worldwide each year, which means there is a new case every 3.2 s. Alzheimer's disease (AD) is a progressive neurodegenerative disease and various machine learning (ML) and image processing methods have been used to detect it. In this s...

Life SciencesNeuroscienceNeurology
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Complex features extraction with deep learning model for the detection of COVID19 from CT scan images using ensemble based machine learning approach

Verified

Md. Robiul Islam, Md. Nahiduzzaman

Journal: Expert Systems with ApplicationsYear: 2022Citations: 124

Recently the most infectious disease is the novel Coronavirus disease (COVID 19) creates a devastating effect on public health in more than 200 countries in the world. Since the detection of COVID19 using reverse transcription-polymerase chain reaction (RT-PCR) is time-consuming and error-prone, the...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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An Explainable AI Paradigm for Alzheimer’s Diagnosis Using Deep Transfer Learning

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Tanjim Mahmud, Koushick Barua, Sultana Umme Habiba, Nahed Sharmen et al.

Journal: DiagnosticsYear: 2024Citations: 121

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects millions of individuals worldwide, causing severe cognitive decline and memory impairment. The early and accurate diagnosis of AD is crucial for effective intervention and disease management. In recent years, deep lear...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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