Optimized Predictive Models in Health Care Using Machine Learning -

Optimized Predictive Models in Health Care Using Machine Learning (eBook)

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2024 | 1. Auflage
384 Seiten
Wiley (Verlag)
978-1-394-17535-2 (ISBN)
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OPTIMIZED PREDICTIVE MODELS IN HEALTH CARE USING MACHINE LEARNING

This book is a comprehensive guide to developing and implementing optimized predictive models in healthcare using machine learning and is a required resource for researchers, healthcare professionals, and students who wish to know more about real-time applications.

The book focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity and provides content on the theory of optimized predictive model design, evaluation, and user diversity. Predictive modeling, a field of machine learning, has emerged as a powerful tool in healthcare for identifying high-risk patients, predicting disease progression, and optimizing treatment plans. By leveraging data from various sources, predictive models can help healthcare providers make informed decisions, resulting in better patient outcomes and reduced costs.

Other essential features of the book include:

  • provides detailed guidance on data collection and preprocessing, emphasizing the importance of collecting accurate and reliable data;
  • explains how to transform raw data into meaningful features that can be used to improve the accuracy of predictive models;
  • gives a detailed overview of machine learning algorithms for predictive modeling in healthcare, discussing the pros and cons of different algorithms and how to choose the best one for a specific application;
  • emphasizes validating and evaluating predictive models;
  • provides a comprehensive overview of validation and evaluation techniques and how to evaluate the performance of predictive models using a range of metrics;
  • discusses the challenges and limitations of predictive modeling in healthcare;
  • highlights the ethical and legal considerations that must be considered when developing predictive models and the potential biases that can arise in those models.

Audience

The book will be read by a wide range of professionals who are involved in healthcare, data science, and machine learning.

Sandeep Kumar, PhD, is a professor in the Department of Computer Science and Engineering, K L Deemed to be University, Vijayawada, Andhra Pradesh, India. He has been granted six patents and successfully filed another ten. He has published more than 100 research papers in various national and international journals and proceedings of reputed national and international conferences.

Anuj Sharma, PhD, is a professor at Maharshi Dayanand University, Rohtak, India. He has 19 years of teaching and administrative experience and has published more than 50 journal articles.

Navneet Kaur, PhD, is a professor in the Department of Computer Science & Engineering, Chandigarh University, India. She is the awardee of the Best Engineering College Teacher Award for Punjab State for the year 2019 and has published more than 35 research articles in reputed SCI journals and conferences.

Lokesh Pawar, PhD, is an assistant professor at Chandigarh University, India. He has filed two patents and has published multiple research articles in many SCI journals.

Rohit Bajaj, PhD, is an associate professor in the Department of Computer Science & Engineering, Chandigarh University, India. He has 12 years of teaching research experience and has published 60 papers in refereed journals and conferences.


OPTIMIZED PREDICTIVE MODELS IN HEALTH CARE USING MACHINE LEARNING This book is a comprehensive guide to developing and implementing optimized predictive models in healthcare using machine learning and is a required resource for researchers, healthcare professionals, and students who wish to know more about real-time applications. The book focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity and provides content on the theory of optimized predictive model design, evaluation, and user diversity. Predictive modeling, a field of machine learning, has emerged as a powerful tool in healthcare for identifying high-risk patients, predicting disease progression, and optimizing treatment plans. By leveraging data from various sources, predictive models can help healthcare providers make informed decisions, resulting in better patient outcomes and reduced costs. Other essential features of the book include: provides detailed guidance on data collection and preprocessing, emphasizing the importance of collecting accurate and reliable data; explains how to transform raw data into meaningful features that can be used to improve the accuracy of predictive models; gives a detailed overview of machine learning algorithms for predictive modeling in healthcare, discussing the pros and cons of different algorithms and how to choose the best one for a specific application; emphasizes validating and evaluating predictive models; provides a comprehensive overview of validation and evaluation techniques and how to evaluate the performance of predictive models using a range of metrics; discusses the challenges and limitations of predictive modeling in healthcare; highlights the ethical and legal considerations that must be considered when developing predictive models and the potential biases that can arise in those models. Audience The book will be read by a wide range of professionals who are involved in healthcare, data science, and machine learning.

1
Impact of Technology on Daily Food Habits and Their Effects on Health


Neha Tanwar1, Sandeep Kumar2* and Shilpa Choudhary3

1Department of Food Technology, Guru Jambheshwar University of Science and Technology, Hisar, India

2Department of Computer Science and Engineering, Koneru Lakshmaiah Educational Foundation, Vijayawada, India

3Department of Computer Science and Engineering, Neil Gogte Institute of Technology, Hyderabad, India

Abstract


In this modern and busy lifestyle, we all look for ready-to-eat food. Food industries turn toward full automation to provide ready food nowadays. Prepared and packed food has an impact on health in the modern lifestyle with eating habits consumers seeking the technology viz. food diets application, online food delivery systems, and robotic food making machines. In this chapter, we have discussed the impacts of technology on daily food habits. The importance of technology in the food industry and its problems are highlighted in this chapter, with a focus on artificial intelligence, bioinformatics, 3D printing, sustainable applications of functional and nutraceutical food, and the need for a coordinated regulatory framework. The natural nutrients included in food, including carbs, proteins, vitamins, fats, antioxidants, and minerals, are necessary for the body parts to work normally physiologically. Achieving good health from sustainable food systems for the people is one of the most significant issues facing our world today. This chapter also focuses on different processed foods and their health impacts.

Keywords: Technology, food habits, artificial intelligence, digitization, emerging technologies

1.1 Introduction


We truly are what we eat, as the phrase goes. In other words, nutrition is essential to our health. Food provides information to our bodies, which also require ingredients to function properly. Our metabolic processes become disrupted and our health degrades if our body doesn’t receive the proper signals [1]. If we give our bodies non-healthy foods, our bodies get the wrong information, and we have to suffer many diseases. Several exciting pieces of evidence show that dietary factor plays a vital role in maintaining the systems and mechanisms of mental function. The relative abundance or scarcity of specific nutrients can affect cognitive processes. Cognitive ability is influenced by several gut hormones which can enter the brain, and these hormones function depending on the type of food intake. Although there are definite patterns, such as the need for nutrition balancing, there is no universally accepted definition of a healthy diet. Also, this relies on the features of every person and their surroundings [2]. -Gregorio Varela, Chairman of the Spanish Nutrition Association

Our food is different from what it was 20 years ago. The soil nutrients have been depleted, and chemicals are increasingly used to get more yield. Because of the growing quantity and variety of available food products, food choices are complex and vary over a short period, influenced by many factors like social, cultural, biological, psychological, and economic factors [3]. We have a lot of food variety and approx. Seventeen thousand new products are introduced each year. So we are heavily dependent on processed foods. The examples of food tech businesses include robotics, 3D food printing, alternative proteins, and individualised nutrition. Although these technologies have a tremendous positive impact on the food business, they merely touch the surface. These technological advancements and the internet era promote new food products that give fulfillment in less time.

1.1.1 Impacts of Food on Health


Food is central to our health. The food we have gives information and materials to our bodies that we need for the proper functioning of our bodies, as shown in Figure 1.1. This information can be right and wrong, depending on our food. To sustain, prevent, and treat disease, food serves as medication. The nutrients in food give all the necessary nourishing things and information by which our cells enable them to perform their functions. The metabolic processes slow down or occasionally even cease when the amount of nutrients consumed is not appropriate for the demands of the cell’s activity [4]. A healthy and balanced diet gives us plenty of energy to work, enjoy ourselves, and keep our immune systems healthy. The both science and art concerned with maintaining health and the prevention, relief, or cure of sickness, according to Webster. Nutrients come in a wide variety of forms, and we classify them into two groups: macronutrients and micronutrients, as shown in Figure 1.2.

Figure 1.1 Role of food habits on our mental health.

Figure 1.2 Macronutrients and micronutrients.

  • Macro (big) Nutrients
    We need large amounts of carbohydrates, sugars, and dietary fiber from pieces of bread, beans, cereals and grains, pasta, fruits, and non-starchy vegetables. We obtain fats, fatty acids, and cholesterol from red palm oil, coconuts, groundnuts, soybeans, oily fish, avocados, butter, ghee, lard/cooking fat, whole milk, and cheese. We also obtain fats from meats and meat products (such as sausages) and fowl. There are many various types of proteins; some examples include those found in animal-based meals like meat, chicken, fish, eggs, and dairy products as well as those found in plant-based foods like pulses, fruits, and vegetables [5].
  • Micro (minor) Nutrients
    Minerals like iron, iodine, and zinc are among the micronutrients, or minor nutrients, which humans need in very small amounts yet are most often inadequate in our diets. Beef, liver, and other organ meats, poultry, fish, breast milk, as well as seaweed, legumes, almonds, and other foods provide us with these nutrients, vitamins, such as folate, vitamin B-group vitamins (which also contain vitamin A), and vitamin C [6].

1.1.2 Impact of Technology on Our Eating Habits


Technology changes every aspect of people’s lives and their communication, lifestyle, thinking, learning, and food habits. Food habits are changed with the rise of Internet of Things (IoT) and Artificial Intelligence (AI). Sharing food pictures on social media like WhatsApp, Facebook, Twitter, Instagram, etc., has grown globally [7]. Many people have even made their careers as food bloggers out of employing this trend on their feeds as shown in Figure 1.3. From every aspect, technology is changing our way of food habits. According to the Choosi Modern Food Trends Study, 50% of consumers get ideas for meals from others’ internet food photos. 39% of those surveyed stated that social media influenced their current eating habits.

Now, the question arises: How does technology affect our eating habits, and how will this change in the future?

1.2 Technologies, Foodies, and Consciousness


Technological influence may have both positive and negative effects. Figure 1.4 demonstrates that food is more than simply a necessity for survival.

Figure 1.3 Technological innovations in food sector.

Figure 1.4 Food on social media.

From one perspective, it increases our awareness of what we eat and current dietary trends, which develops better eating habits, at the same time, problematic internet users, uncontrollable craving habits, and eating disorders such as loss of control eating, binge eating disorders, etc. are increasing by the higher rate [8]. Problematic Internet Use (PIU) comprises passive behaviour brought on by excessive technology use as well as adverse social comparisons that may arise from exposure to and self-comparison with anything on their home feed. When it comes to teenagers, it becomes more distracting because of their undeveloped skills and the constant pressure they face through the internet world. It is important to understand online marketing and how it can be deceptive, as people can’t touch, feel or smell what’s advertised. Technology has improved accessibility—find, grab, and get. This on-demand culture has naturally shifted our food habits as well. Technology gives a faster way to get your food. Everybody likes ready to eat, ready to drink, and mull meal bars because it takes just a few minutes to prepare without effort. Technology does not affect our food habits as well as it affects the food industries [9].

According to the latest available statistics from the Australian Institute of Health and Welfare, which covered the years 2017 to 2018, 7.7% of adults and 17% of children were obese. As a result, one in four kids are at an elevated risk for physical health problems as well as greater mortality and sickness risks as adults. In order to prevent these tendencies from developing later in life, it is important to foster a positive link between food and technology from early childhood and adolescence on.

Technology has positive impacts also; like presently, so many intelligent appliances make cooking more accessible and less time-consuming, like smart cookers, electric inductions, ovens, etc. New technologies change everything from what we eat to how it to made by minimizing waste and environmental impacts. New automation raises high-skill jobs in the food sector and puts manual workers’ livelihoods at risk. So, the effect of technology is much more complicated...

Erscheint lt. Verlag 8.2.2024
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Theorie / Studium
ISBN-10 1-394-17535-3 / 1394175353
ISBN-13 978-1-394-17535-2 / 9781394175352
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