Automated Diagnosis and Detection of Blood Cancer Using Deep Learning-Based Approaches: A Recent Study and Challenges

Singh, Jaswinder Bir; Luxmi, Vijay

doi:10.1109/ic3i59117.2023.10398153

Cited by 1 publication

(2 citation statements)

References 23 publications

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“…The study conducted by Singh and Luxmi (2023) in Paper [3] delves into the realm of blood cancer detection, recognizing the critical importance of early and accurate diagnosis for effective treatment outcomes. Focusing on the application of deep learning techniques, the paper provides a thorough examination of various deep learning architectures and frameworks utilized in blood cancer research.…”

Section: Literature Surveymentioning

confidence: 99%

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The Enigma of Blood Cancer: Advances in Detection

Jaiswal

2024

IJSREM

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Blood cancer, also called hematological malignancy, is a group of cancers that affect the blood, bone marrow and lymph nodes. Early and accurate detection of blood cancers is essential for effective treatment and improved patient outcomes. In recent time, deep-learning algorithms have become effective tools in medical image analysis and disease detection. The purpose of this paper is to provide a comprehensive overview of the application of various methods in the detection of blood cancer. The beginning of the article describes the different forms of blood cancer, the factors that lead to cancer and the difficulties in detecting them. The article discusses various techniques related to the cancer detection, various machine learning models, deep learning models and mobile nano sensors and their help in detecting blood cancer in the human body. The article ends with a discussion of the future trends and development of the industry. It highlights the importance of different cancer detection methods and how effective these methods are in helping to diagnose blood cancer at an early stage, which would reduce deaths. Keywords: Blood cancer, detection, deep learning, machine learning, medical imaging, early diagnosis, treatment, outcomes, hematological malignancy

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Section: Literature Surveymentioning

confidence: 99%

“…Paper [3] also discuss the practical aspects of blood cancer diagnosis, elucidating common symptoms and diagnostic procedures. They shed light on the diverse manifestations of blood cancer symptoms, ranging from fatigue and weight loss to swollen lymph nodes and bone pain.…”

Section: Literature Surveymentioning

confidence: 99%

The Enigma of Blood Cancer: Advances in Detection

Jaiswal

2024

IJSREM

View full text Add to dashboard Cite

show abstract

Automated Diagnosis and Detection of Blood Cancer Using Deep Learning-Based Approaches: A Recent Study and Challenges

Cited by 1 publication

References 23 publications

The Enigma of Blood Cancer: Advances in Detection

The Enigma of Blood Cancer: Advances in Detection

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