Deep Learning Applications for Healthcare Risk Assessment

Deep Learning Applications for Healthcare Risk Assessment

Sana Fateh (Lyari General Hospital, Pakistan), Imdad Ali Shah (Faculty of Engineering Science and Technology, Iqra University, Karachi, Pakistan), Quratulain Sial (Emergency Department, Aga Khan University Hospital, Karachi, Pakistan), and N. Z. Jhanjhi (School of Computer Science, Taylor's University, Malaysia)
Copyright: © 2025 |Pages: 18
DOI: 10.4018/979-8-3693-6577-9.ch004
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Abstract

The primary object of this chapter is to focus on deep learning and how it is useful for healthcare risk assessment. A healthcare potential risk, mitigate and weaknesses assessment is important for early detection through the analysis to guarantee patient and staff safety. The approach to tackling everyday problems has radically changed in the age of artificial intelligence (AI), machine learning, and deep learning. We are now concentrating on developing technology that is specific to specific fields. Deep learning techniques offer a wide range of applications in health care, even though it is still in its early phases. From keeping an individual's universal health record to emerging technologies enabled by deep learning, we will see many upgrades that will fundamentally change the healthcare industry scenario in the coming years. Deep learning can evaluate organized or unstructured data at a high rate.
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