Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2312.11569 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866910394760560640 |
|---|---|
| author | Ramakrishnan, Ritu Xing, Tianxiang Chen, Tianfeng Lee, Ming-Hao Gao, Jinzhu |
| author_facet | Ramakrishnan, Ritu Xing, Tianxiang Chen, Tianfeng Lee, Ming-Hao Gao, Jinzhu |
| contents | In healthcare, artificial intelligence (AI) has been changing the way doctors and health experts take care of people. This paper will cover how AI is making major changes in the health care system, especially with nutrition. Various machine learning and deep learning algorithms have been developed to extract valuable information from healthcare data which help doctors, nutritionists, and health experts to make better decisions and make our lifestyle healthy. This paper provides an overview of the current state of AI applications in healthcare with a focus on the utilization of AI-driven recommender systems in nutrition. It will discuss the positive outcomes and challenges that arise when AI is used in this field. This paper addresses the challenges to develop AI recommender systems in healthcare, providing a well-rounded perspective on the complexities. Real-world examples and research findings are presented to underscore the tangible and significant impact AI recommender systems have in the field of healthcare, particularly in nutrition. The ongoing efforts of applying AI in nutrition lay the groundwork for a future where personalized recommendations play a pivotal role in guiding individuals toward healthier lifestyles. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_11569 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Application of AI in Nutrition Ramakrishnan, Ritu Xing, Tianxiang Chen, Tianfeng Lee, Ming-Hao Gao, Jinzhu Human-Computer Interaction Information Retrieval In healthcare, artificial intelligence (AI) has been changing the way doctors and health experts take care of people. This paper will cover how AI is making major changes in the health care system, especially with nutrition. Various machine learning and deep learning algorithms have been developed to extract valuable information from healthcare data which help doctors, nutritionists, and health experts to make better decisions and make our lifestyle healthy. This paper provides an overview of the current state of AI applications in healthcare with a focus on the utilization of AI-driven recommender systems in nutrition. It will discuss the positive outcomes and challenges that arise when AI is used in this field. This paper addresses the challenges to develop AI recommender systems in healthcare, providing a well-rounded perspective on the complexities. Real-world examples and research findings are presented to underscore the tangible and significant impact AI recommender systems have in the field of healthcare, particularly in nutrition. The ongoing efforts of applying AI in nutrition lay the groundwork for a future where personalized recommendations play a pivotal role in guiding individuals toward healthier lifestyles. |
| title | Application of AI in Nutrition |
| topic | Human-Computer Interaction Information Retrieval |
| url | https://arxiv.org/abs/2312.11569 |