Issue 1. When Alpha Go beat Lee Sedol in a five-game match, it was the first time that a computer Go program was able to beat a 9-dan professional without handicaps. This was simultaneously met by reactions of enthusiasm and horror regarding artificial intelligence. In particular, the fear that doctors will be replaced by artificial intelligence is rampant in among doctors. The role of WATSON, designed by IBM for application in the medical area, has led to fear that there is a real threat to doctors.
Issue 2. Telemedicine, telehealth, m-Health, u-Health, etc., are other sources of fear as telemedicine is becoming more widespread in medical practice. If telemedicine is widely implemented, it is widely predicted that big facilities will replace private clinics.
Issue 3. The big data originating from health insurance claim data and a platform like that of the OHDSI project [1] is obtained from multiple medical facilities, and it includes prescribing data, laboratory data, etc. The availability of big data is changing the pattern of clinical research from small studies to a greater emphasis on very large-scale studies.
Issue 4. Since the human genome project in the 1990s, with advances in DNA sequencing techniques, the sequencing of data has increased exponentially. Because of these advances, bioinformatics has also been making remarkable advances. Unlike in the past, many researchers of biotechnology are spending more time in front of computers rather than workbenches; thus, bioinformatics is increasingly moving towards the center of research, rather than playing an axillary role [23].
Issue 5. With advances in mobile networks and devices, users are moving from passive lifelogging through SNSs to active lifelogging through wearable devices; thus, lifelogging is becoming increasingly popular, and the biological signals generated by wearable devices are beginning to be used widely in the place of direct healthcare.
These changes are beginning to transform the healthcare fields. In the future of healthcare, these areas of change will be very significant. But, the majority of professionals in healthcare fields think these issues are not related to them.
However, there are no specific references available for people who want to learn more about these subjects. In many cases, these subjects deal with very different concepts, and a concept is not made out by understanding some references.
This book, edited by Al-Jumeily et al. comprises 14 chapters. Each chapter is organized as a review article dealing with a specific topic on applied computing in medicine and health.
The 14 chapters were written by researchers working in specific fields; some chapters include general contents in these fields, and a few chapters include very specific contents. One chapter reports on research carried out using a device developed by the authors for their own research; others report on studies carried out using existing mobile devices, wearable devices, and apps; others report on research about big data and machine learning; and another reports on a telemedicine project that is a subject of controversy in Korea. The cases referenced in each chapter were taken from the United States, the UK, and France as examples from developed countries, while cases from India, Pakistan, Malaysia, Indonesia, Malta, the UAE and Saudi Arabia were referenced as examples from developing countries in healthcare fields.
When the development of healthcare IT is restricted by many stakeholders, many countries' achievements in healthcare IT fields have been very notable, even in developing countries. I strongly recommend this book not only to professionals in healthcare IT fields but to stakeholders as leaders of physicians' communities, senior officials, and other interested parties.