Artificial intelligence (AI) systems are systems designed by humans that, given a complex goal, act in the physical or digital dimension by perceiving their environment through data acquisition, interpreting the collected structured or unstructured data, reasoning on the knowledge, or processing the information, derived from this data and deciding the best action(s) to take to achieve the given goal. It is precisely AI's ability to carry out speedy processing and analysis of datasets that is one of its key strengths. The recent renaissance in AI largely has been driven by the successful application of deep learning — which involves training an artificial neural network with many layers (that is, a ‘deep' neural network) on huge datasets. The rise and dissemination of AI in clinical medicine will refine our diagnostic accuracy and rule-out capabilities. In this Book Chapter, we focus on the AI applications that could augment or change clinical practice, identify the impact arising from the development of AI diagnostic systems and suggest future research directions.
TopIntegrating Ai In Biomedical Research To Enhance Healthcare
The primary aim of biomedical research is to supplement healthcare data with other resources by conducting required research, applying the research findings in medicine, regenerative medicine and associated areas and developing better products and services, by combining engineering, virology, and healthcare data (Javaid et al., 2020)
Be it conceptualisation and evaluation of new technologies, development of novel patient care techniques or the research of biological processes, all these require bioengineers. According to Javaid et al (2023), the primary supportive technologies of biomedical engineering are Additive Manufacturing, Artificial Intelligence, Internet of Things, Virtual Reality, Holography and other medical imaging technologies.
Several innovations and progressive journeys are observed in the broad biomedical engineering domain in the last few years as depicted in the Figure 1.
Figure 1. The journey of biomedical engineering-related development through the ages
The application of interdisciplinary research for the integration of mechanical components, electronics and biological organism parts including areas of neurology and robotics fall under Biomechatronics. Interdisciplinary collaboration led to designing of essential tools and gadgets, including Magnetic Resonance Imaging (MRI) machines, dialysis machines, diagnostic instruments, and ultrasound as depicted in Figure 2.
Figure 2. Smart integration of big data, artificial intelligence, digital methodologies and production steps