Machine Learning in Healthcare

Machine Learning in Healthcare

Debasree Mitra (JIS College of Engineering, India), Apurba Paul (JIS College of Engineering, India) and Sumanta Chatterjee (JIS College of Engineering, India)
Copyright: © 2021 |Pages: 24
DOI: 10.4018/978-1-7998-3092-4.ch002
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Abstract

Machine learning is a popular approach in the field of healthcare. Healthcare is an important industry that provides service to millions of people and as well as at the same time becoming top revenue earners in many countries. Machine learning in healthcare helps to analyze thousands of different data points and suggest outcomes, provide timely risk factors, optimize resource allocation. Machine learning is playing a critical role in patient care, billing processing to set the target to marketing and sales team, and medical records for patient monitoring and readmission, etc. Machine learning is allowing healthcare specialists to develop alternate staffing models, intellectual property management, and using the most effective way to capitalize on developed intellectual property assets. Machine learning approaches provide smart healthcare and reduce administrative and supply costs. Today healthcare industry is committed to deliver quality, value, and satisfactory outcomes.
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Introduction

What Is Machine Learning?

Machine learning (ML) explores algorithms that learn from data, builds models data and that model used for prediction, decision making or solving task. A computer program is to learn from experience E with respect to some class of task T and performance P. There are two components in ML i.e. learning module and reasoning module. Learner module takes input as experienced data and background knowledge and builds model. Models are used by reasoning module and reasoning module comes up with solution to the task and performance measure. Machine Learning algorithms can generate a mathematical model based on experience data known as training data to predict or decisions.

Figure 1.

Traditional Programming vs Machine Learning

978-1-7998-3092-4.ch002.f01

Machine learning algorithms are used in diagnose disease, banking system, healthcare, email filtering, and computer vision, data mining, robot control, Natural Language Processing, Speech Recognition, Machine Translation, Business Intelligence, Fraud Detection, Consumer sentiment etc where it is very helpful to develop an algorithm of specific instructions for performing the task. Machine learning is related to statistics and probability, which focuses on making predictions using computers.

What Is Healthcare?

Healthcare is the upgradation of health via technology for people. Health care is delivered by health professionals in allied health fields. Physicians and physician associates are a part of these health professionals. Dentistry, pharmacy, midwifery, nursing, medicine, optometry, audiology, psychology, occupational therapy, physical therapy and other health professions are all part of health care. It includes work done in providing primary care, secondary care, and tertiary care, as well as in public health.

Access to health care may vary across countries, communities, and individuals, largely influenced by social and economic conditions as well as health policies. Providing health care services means “the timely use of personal health services to achieve the best possible health outcomes” (Anthony & Bartlet, 1999). Factors to consider in terms of healthcare access include financial limitations (such as insurance coverage), geographic barriers (such as additional transportation costs, possibility to take paid time off of work to use such services), and personal limitations (lack of ability to communicate with healthcare providers, poor health literacy, low income) (Langley, 1996). Limitations to health care services affects negatively the use of medical services, efficacy of treatments, and overall outcome (well-being, mortality rates).

Health care systems are organizations established to meet the health needs of targeted populations. According to the World Health Organization (WHO), a well-functioning health care system requires a financing mechanism, a well-trained and adequately paid workforce, reliable information on which to base decisions and policies, and well maintained health facilities to deliver quality medicines and technologies (Muller & Guido, n.d.).

An efficient health care system can contribute to a significant part of a country's economy, development and industrialization. Health care is conventionally regarded as an important determinant in promoting the general physical and mental health and well-being of people around the world. An example of this was the worldwide eradication of smallpox in 1980, declared by the WHO as the first disease in human history to be completely eliminated by deliberate health care interventions.

Purpose of Machine Learning in Healthcare

Machine learning has virtually endless applications in the healthcare industry. Today, machine learning is helping to streamline administrative processes in hospitals, map and treat infectious diseases and personalize medical treatments.

The healthcare sector has long been an early adopter of and benefited greatly from technological advances. These days, machine learning (a subset of artificial intelligence) plays a key role in many health-related realms, including the development of new medical procedures, the handling of patient data and records and the treatment of chronic diseases. As computer scientist Sebastian Thrum told the New Yorker in a recent article titled “A.I. Versus M.D., “Just as machines made human muscles a thousand times stronger, machines will make the human brain a thousand times more powerful.”

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