Artificial intelligence, machine learning and deep learning in biomedical fields: A prospect in improvising medical healthcare systems

Artificial intelligence (AI), machine learning (ML) and deep learning (DL) have become important tools for the biomedical research community in recent years. Nonetheless, they first emerged in the 1950s, but their application in medical care was limited due to a lack of exposure to the field and in-depth knowledge. They are now used extensively in the analysis of medical images and genetic sequences, that have the potential to provide insights useful information in the diagnosis, treatment, and prevention. Machine learning can be used to dramatically enhance non-invasive early detection of various types of cancer through training of a predictive model utilizing diagnostic reports of samples of urine, blood, sweat, X-rays, and CT scans. AI, ML and DL have considerable potential to strengthen the healthcare system by improving diagnosis, accelerating pharmaceutical research, and individualizing treatment options. This book chapter provides an overview of the AI, ML and DL and its use across the number of biomedical domains, such as diagnostic imaging, an electronic health record (EHRs), drug development, genomics, and other domains of the biomedical fields. Future possibilities and problems of AI, ML and DL in biomedicine are also discussed. In the ensuing decades, these will be an active study fields for both engineering and biomedical science.