Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence
This article finds a multitude of developments underway, which include the use of AI for malnutrition screening; predicting clinical outcomes, such as disease onset, and clinical risks, such as drug interactions; aiding interventions, such as estimating nutrient intake; applying precision nutrition, such as measuring postprandial glycemic response; and supporting workflow through chatbots trained on natural language models. Although the opportunity and scalability of AI is incalculably attractive, especially in the face of poor healthcare resources, the threat cannot be ignored. The risk of malpractice and lack of accounta...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Kiranjit Atwal Source Type: research
Emergence of imaging technology beyond the clinical setting: Utilization of mobile health tools for at-home testing
Nutr Clin Pract. 2024 Apr 9. doi: 10.1002/ncp.11151. Online ahead of print.ABSTRACTBody composition assessment plays a pivotal role in understanding health, disease risk, and treatment efficacy. This narrative review explores two primary aspects: imaging techniques, namely ultrasound (US) and dual-energy x-ray absorptiometry (DXA), and the emergence of artificial intelligence (AI) and mobile health apps in telehealth for body composition. Although US is valuable for assessing subcutaneous fat and muscle thickness, DXA accurately quantifies bone mineral content, fat mass, and lean mass. Despite their effectiveness, accessib...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Brooke E Starkoff Brett S Nickerson Source Type: research
Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence
This article finds a multitude of developments underway, which include the use of AI for malnutrition screening; predicting clinical outcomes, such as disease onset, and clinical risks, such as drug interactions; aiding interventions, such as estimating nutrient intake; applying precision nutrition, such as measuring postprandial glycemic response; and supporting workflow through chatbots trained on natural language models. Although the opportunity and scalability of AI is incalculably attractive, especially in the face of poor healthcare resources, the threat cannot be ignored. The risk of malpractice and lack of accounta...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Kiranjit Atwal Source Type: research
Emergence of imaging technology beyond the clinical setting: Utilization of mobile health tools for at-home testing
Nutr Clin Pract. 2024 Apr 9. doi: 10.1002/ncp.11151. Online ahead of print.ABSTRACTBody composition assessment plays a pivotal role in understanding health, disease risk, and treatment efficacy. This narrative review explores two primary aspects: imaging techniques, namely ultrasound (US) and dual-energy x-ray absorptiometry (DXA), and the emergence of artificial intelligence (AI) and mobile health apps in telehealth for body composition. Although US is valuable for assessing subcutaneous fat and muscle thickness, DXA accurately quantifies bone mineral content, fat mass, and lean mass. Despite their effectiveness, accessib...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Brooke E Starkoff Brett S Nickerson Source Type: research
Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence
This article finds a multitude of developments underway, which include the use of AI for malnutrition screening; predicting clinical outcomes, such as disease onset, and clinical risks, such as drug interactions; aiding interventions, such as estimating nutrient intake; applying precision nutrition, such as measuring postprandial glycemic response; and supporting workflow through chatbots trained on natural language models. Although the opportunity and scalability of AI is incalculably attractive, especially in the face of poor healthcare resources, the threat cannot be ignored. The risk of malpractice and lack of accounta...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Kiranjit Atwal Source Type: research
Emergence of imaging technology beyond the clinical setting: Utilization of mobile health tools for at-home testing
Nutr Clin Pract. 2024 Apr 9. doi: 10.1002/ncp.11151. Online ahead of print.ABSTRACTBody composition assessment plays a pivotal role in understanding health, disease risk, and treatment efficacy. This narrative review explores two primary aspects: imaging techniques, namely ultrasound (US) and dual-energy x-ray absorptiometry (DXA), and the emergence of artificial intelligence (AI) and mobile health apps in telehealth for body composition. Although US is valuable for assessing subcutaneous fat and muscle thickness, DXA accurately quantifies bone mineral content, fat mass, and lean mass. Despite their effectiveness, accessib...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Brooke E Starkoff Brett S Nickerson Source Type: research
Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence
This article finds a multitude of developments underway, which include the use of AI for malnutrition screening; predicting clinical outcomes, such as disease onset, and clinical risks, such as drug interactions; aiding interventions, such as estimating nutrient intake; applying precision nutrition, such as measuring postprandial glycemic response; and supporting workflow through chatbots trained on natural language models. Although the opportunity and scalability of AI is incalculably attractive, especially in the face of poor healthcare resources, the threat cannot be ignored. The risk of malpractice and lack of accounta...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Kiranjit Atwal Source Type: research
Emergence of imaging technology beyond the clinical setting: Utilization of mobile health tools for at-home testing
Nutr Clin Pract. 2024 Apr 9. doi: 10.1002/ncp.11151. Online ahead of print.ABSTRACTBody composition assessment plays a pivotal role in understanding health, disease risk, and treatment efficacy. This narrative review explores two primary aspects: imaging techniques, namely ultrasound (US) and dual-energy x-ray absorptiometry (DXA), and the emergence of artificial intelligence (AI) and mobile health apps in telehealth for body composition. Although US is valuable for assessing subcutaneous fat and muscle thickness, DXA accurately quantifies bone mineral content, fat mass, and lean mass. Despite their effectiveness, accessib...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Brooke E Starkoff Brett S Nickerson Source Type: research
Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence
This article finds a multitude of developments underway, which include the use of AI for malnutrition screening; predicting clinical outcomes, such as disease onset, and clinical risks, such as drug interactions; aiding interventions, such as estimating nutrient intake; applying precision nutrition, such as measuring postprandial glycemic response; and supporting workflow through chatbots trained on natural language models. Although the opportunity and scalability of AI is incalculably attractive, especially in the face of poor healthcare resources, the threat cannot be ignored. The risk of malpractice and lack of accounta...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Kiranjit Atwal Source Type: research
Emergence of imaging technology beyond the clinical setting: Utilization of mobile health tools for at-home testing
Nutr Clin Pract. 2024 Apr 9. doi: 10.1002/ncp.11151. Online ahead of print.ABSTRACTBody composition assessment plays a pivotal role in understanding health, disease risk, and treatment efficacy. This narrative review explores two primary aspects: imaging techniques, namely ultrasound (US) and dual-energy x-ray absorptiometry (DXA), and the emergence of artificial intelligence (AI) and mobile health apps in telehealth for body composition. Although US is valuable for assessing subcutaneous fat and muscle thickness, DXA accurately quantifies bone mineral content, fat mass, and lean mass. Despite their effectiveness, accessib...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Brooke E Starkoff Brett S Nickerson Source Type: research
Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence
This article finds a multitude of developments underway, which include the use of AI for malnutrition screening; predicting clinical outcomes, such as disease onset, and clinical risks, such as drug interactions; aiding interventions, such as estimating nutrient intake; applying precision nutrition, such as measuring postprandial glycemic response; and supporting workflow through chatbots trained on natural language models. Although the opportunity and scalability of AI is incalculably attractive, especially in the face of poor healthcare resources, the threat cannot be ignored. The risk of malpractice and lack of accounta...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Kiranjit Atwal Source Type: research
Emergence of imaging technology beyond the clinical setting: Utilization of mobile health tools for at-home testing
Nutr Clin Pract. 2024 Apr 9. doi: 10.1002/ncp.11151. Online ahead of print.ABSTRACTBody composition assessment plays a pivotal role in understanding health, disease risk, and treatment efficacy. This narrative review explores two primary aspects: imaging techniques, namely ultrasound (US) and dual-energy x-ray absorptiometry (DXA), and the emergence of artificial intelligence (AI) and mobile health apps in telehealth for body composition. Although US is valuable for assessing subcutaneous fat and muscle thickness, DXA accurately quantifies bone mineral content, fat mass, and lean mass. Despite their effectiveness, accessib...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Brooke E Starkoff Brett S Nickerson Source Type: research
Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence
This article finds a multitude of developments underway, which include the use of AI for malnutrition screening; predicting clinical outcomes, such as disease onset, and clinical risks, such as drug interactions; aiding interventions, such as estimating nutrient intake; applying precision nutrition, such as measuring postprandial glycemic response; and supporting workflow through chatbots trained on natural language models. Although the opportunity and scalability of AI is incalculably attractive, especially in the face of poor healthcare resources, the threat cannot be ignored. The risk of malpractice and lack of accounta...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Kiranjit Atwal Source Type: research
Emergence of imaging technology beyond the clinical setting: Utilization of mobile health tools for at-home testing
Nutr Clin Pract. 2024 Apr 9. doi: 10.1002/ncp.11151. Online ahead of print.ABSTRACTBody composition assessment plays a pivotal role in understanding health, disease risk, and treatment efficacy. This narrative review explores two primary aspects: imaging techniques, namely ultrasound (US) and dual-energy x-ray absorptiometry (DXA), and the emergence of artificial intelligence (AI) and mobile health apps in telehealth for body composition. Although US is valuable for assessing subcutaneous fat and muscle thickness, DXA accurately quantifies bone mineral content, fat mass, and lean mass. Despite their effectiveness, accessib...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Brooke E Starkoff Brett S Nickerson Source Type: research
Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence
This article finds a multitude of developments underway, which include the use of AI for malnutrition screening; predicting clinical outcomes, such as disease onset, and clinical risks, such as drug interactions; aiding interventions, such as estimating nutrient intake; applying precision nutrition, such as measuring postprandial glycemic response; and supporting workflow through chatbots trained on natural language models. Although the opportunity and scalability of AI is incalculably attractive, especially in the face of poor healthcare resources, the threat cannot be ignored. The risk of malpractice and lack of accounta...
Source: Nutrition in Clinical Practice - April 9, 2024 Category: Nutrition Authors: Kiranjit Atwal Source Type: research
