Machine learning and deep learning-based approach in smart healthcare: Recent advances, applications, challenges and opportunities

Подходы на основе машинного и глубокого обучения в интеллектуальном здравоохранении: последние достижения, приложения, проблемы и перспективы
Md. Saikat Islam Khan, Shahab S. Band, Anichur Rahman, Dipanjali Kundu, Tanoy Debnath, Airin Afroj Aishi, Sadia Sazzad, Mohammad Sayduzzaman
2024-01-01

deep learningdrug discoverymachine learningmedical image analysissmart healthcare
In recent years, machine learning (ML) and deep learning (DL) have been the leading approaches to solving various challenges, such as disease predictions, drug discovery, medical image analysis, etc., in intelligent healthcare applications. Further, given the current progress in the fields of ML and DL, there exists the promising potential for both to provide support in the realm of healthcare. This study offered an exhaustive survey on ML and DL for the healthcare system, concentrating on vital state of the art features, integration benefits, applications, prospects and future guidelines. To conduct the research, we found the most prominent journal and conference databases using distinct keywords to discover scholarly consequences. First, we furnished the most current along with cutting-edge progress in ML-DL-based analysis in smart healthcare in a compendious manner. Next, we integrated the advancement of various services for ML and DL, including ML-healthcare, DL-healthcare, and ML-DL-healthcare. We then offered ML and DL-based applications in the healthcare industry. Eventually, we emphasized the research disputes and recommendations for further studies based on our observations.
1
It identifies research challenges and proposes future directions for advancing machine learning and deep learning in smart healthcare.
2
It reviews recent state-of-the-art progress in ML- and DL-based healthcare analysis, including disease prediction, drug discovery, and medical image analysis.
3
The paper provides a comprehensive survey of machine learning and deep learning applications across intelligent healthcare systems.
4
The study examines the integration and benefits of ML-healthcare, DL-healthcare, and combined ML-DL-healthcare services.
5
The survey highlights the potential of ML and DL to support diverse healthcare services as these fields continue to progress.

machine learning and deep learning in smart healthcare systems

recent advances, applications, benefits, challenges, prospects, and future research directions of machine learning and deep learning for healthcare

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Publication Date
2024-01-01
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Md. Saikat Islam Khan
Shahab S. Band
Anichur Rahman
Dipanjali Kundu
Tanoy Debnath
Airin Afroj Aishi
Sadia Sazzad
Mohammad Sayduzzaman
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