scholarly journals Evaluation of a Novel Artificial Intelligence System to Monitor and Assess Energy and Macronutrient Intake in Hospitalised Older Patients

Nutrients ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 4539
Author(s):  
Ioannis Papathanail ◽  
Jana Brühlmann ◽  
Maria F. Vasiloglou ◽  
Thomai Stathopoulou ◽  
Aristomenis K. Exadaktylos ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Positive Impact ◽  
Standard Procedure ◽  
Dietary Assessment ◽  
Fine Tuning ◽  
Macronutrient Intake ◽  
Intelligence System ◽  
Clinical Procedures ◽  
Hospitalised Patients ◽  
Before And After

Malnutrition is common, especially among older, hospitalised patients, and is associated with higher mortality, longer hospitalisation stays, infections, and loss of muscle mass. It is therefore of utmost importance to employ a proper method for dietary assessment that can be used for the identification and management of malnourished hospitalised patients. In this study, we propose an automated Artificial Intelligence (AI)-based system that receives input images of the meals before and after their consumption and is able to estimate the patient’s energy, carbohydrate, protein, fat, and fatty acids intake. The system jointly segments the images into the different food components and plate types, estimates the volume of each component before and after consumption, and calculates the energy and macronutrient intake for every meal, based on the kitchen’s menu database. Data acquired from an acute geriatric hospital as well as from our previous study were used for the fine-tuning and evaluation of the system. The results from both our system and the hospital’s standard procedure were compared to the estimations of experts. Agreement was better with the system, suggesting that it has the potential to replace standard clinical procedures with a positive impact on time spent directly with the patients.

scholarly journals goFOODTM: An Artificial Intelligence System for Dietary Assessment

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4283 ◽  
Author(s):  
Ya Lu ◽  
Thomai Stathopoulou ◽  
Maria F. Vasiloglou ◽  
Lillian F. Pinault ◽  
Colleen Kiley ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Fast Food ◽  
Dietary Assessment ◽  
Reconstruction Algorithm ◽  
Multimedia Databases ◽  
Assessment System ◽  
Accurate Estimation ◽  
Food Category ◽  
Intelligence System ◽  
Macronutrient Content

Accurate estimation of nutritional information may lead to healthier diets and better clinical outcomes. We propose a dietary assessment system based on artificial intelligence (AI), named goFOODTM. The system can estimate the calorie and macronutrient content of a meal, on the sole basis of food images captured by a smartphone. goFOODTM requires an input of two meal images or a short video. For conventional single-camera smartphones, the images must be captured from two different viewing angles; smartphones equipped with two rear cameras require only a single press of the shutter button. The deep neural networks are used to process the two images and implements food detection, segmentation and recognition, while a 3D reconstruction algorithm estimates the food’s volume. Each meal’s calorie and macronutrient content is calculated from the food category, volume and the nutrient database. goFOODTM supports 319 fine-grained food categories, and has been validated on two multimedia databases that contain non-standardized and fast food meals. The experimental results demonstrate that goFOODTM performed better than experienced dietitians on the non-standardized meal database, and was comparable to them on the fast food database. goFOODTM provides a simple and efficient solution to the end-user for dietary assessment.

scholarly journals Use of an artificial intelligence program in radiation therapy

2020 ◽  
Vol 58 (4) ◽  
pp. 41-43
Author(s):  
Y.I. ISHKININ ◽  
K. DATBAYEV ◽  
R. RAIMBEKOV ◽  
R. IBRAYEV ◽  
R. AKHUNOVA ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Radiation Therapy ◽  
Positive Impact ◽  
Organs At Risk ◽  
Intelligence System ◽  
Patient Registration ◽  
Patient Preparation ◽  
Workflow Efficiency ◽  
Survey Results ◽  
The Impact

Relevance: Since 01 January 2020, the provision of radiation therapy (RT) at Almaty Oncology Center was optimized using the Visual Care Path (VCP) tool of the ARIA 15.6 oncology system, which supports the implementation of sequential and parallel mandatory procedures – from patient registration to completion of treatment. The purpose was to study the impact of the implemented artificial intelligence system on RT effectiveness, safety, the share of complex RT techniques, and measure staff satisfaction and proficiency. Results: The share of intensive modulated radiation therapy sessions changed from 39.3% in 2019 to 46.6% in 2020. After the implementation of VCP, timely pre-irradiation preparation of patients (centering, delineation, dose prescription) by department doctors increased from 76% to 91%, OR = 3.2; timely measurements of plans increased from 85% to 96%, OR = 4.7; the frequency of major events (the ratio of plans with errors or unsuccessful plans to the total number of plans, delineation of organs at risk and targets, dose prescription) decreased from 12% to 3%, OR = 4.5; the frequency of minor events (late notification of the patient of the treatment commencement, timely transition to the next stage of patient preparation for treatment decreased from 32% to 10%, OR = 4.5. Staff proficiency in VCP has increased by 75%. Following the anonymous survey results, 85% of staff reported a positive impact of VCP on the workflow. Conclusion: The share of complex methods of RT has increased by 7.3%. The implementation of VCP significantly increased the workflow efficiency – by 3.9 times, reduced the number of major and minor events by 4.4 times. It allowed using a paperless communication with the executor’s identification at each stage of RT. The new technique was also quickly adopted and favorably accepted by the staff.

scholarly journals Artificial Intelligence in Orthodontic Smart Application for Treatment Coaching and Its Impact on Clinical Performance of Patients Monitored with AI-TeleHealth System

Healthcare ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1695
Author(s):  
Andrej Thurzo ◽  
Veronika Kurilová ◽  
Ivan Varga
Keyword(s):  
Artificial Intelligence ◽  
Decision Tree ◽  
Patient Compliance ◽  
Clinical Performance ◽  
Treatment Efficiency ◽  
Intelligence System ◽  
Before And After ◽  
Health Care Applications ◽  
Removable Appliances ◽  
The Impact

Background: Treatment of malocclusion with clear removable appliances like Invisalign® or Spark™, require considerable higher level of patient compliance when compared to conventional fixed braces. The clinical outcomes and treatment efficiency strongly depend on the patient’s discipline. Smart treatment coaching applications, like strojCHECK® are efficient for improving patient compliance. Purpose: To evaluate the impact of computerized personalized decision algorithms responding to observed and anticipated patient behavior implemented as an update of an existing clinical orthodontic application (app). Materials and Methods: Variables such as (1) patient app interaction, (2) patient app discipline and (3) clinical aligner tracking evaluated by artificial intelligence system (AI) system—Dental monitoring® were observed on the set of 86 patients. Two 60-day periods were evaluated; before and after the app was updated with decision tree processes. Results: All variables showed significant improvement after the update except for the manifestation of clinical non-tracking in men, evaluated by artificial intelligence from video scans. Conclusions: Implementation of application update including computerized decision processes can significantly enhance clinical performance of existing health care applications and improve patients’ compliance. Using the algorithm with decision tree architecture could create a baseline for further machine learning optimization.

Strategic Role of Zakat in Multidimensional Quality of Life in Sijunjung, Indonesia

2018 ◽  
Vol 15 (1) ◽  
pp. 55-72
Author(s):  
Herlin Hamimi ◽  
Abdul Ghafar Ismail ◽  
Muhammad Hasbi Zaenal
Keyword(s):  
Quality Of Life ◽  
Positive Impact ◽  
Wealth Distribution ◽  
Absolute Poverty ◽  
Before And After ◽  
The Status ◽  
Being There ◽  
The Impact

Zakat is one of the five pillars of Islam which has a function of faith, social and economic functions. Muslims who can pay zakat are required to give at least 2.5 per cent of their wealth. The problem of poverty prevalent in disadvantaged regions because of the difficulty of access to information and communication led to a gap that is so high in wealth and resources. The instrument of zakat provides a paradigm in the achievement of equitable wealth distribution and healthy circulation. Zakat potentially offers a better life and improves the quality of human being. There is a human quality improvement not only in economic terms but also in spiritual terms such as improving religiousity. This study aims to examine the role of zakat to alleviate humanitarian issues in disadvantaged regions such as Sijunjung, one of zakat beneficiaries and impoverished areas in Indonesia. The researcher attempted a Cibest method to capture the impact of zakat beneficiaries before and after becoming a member of Zakat Community Development (ZCD) Program in material and spiritual value. The overall analysis shows that zakat has a positive impact on disadvantaged regions development and enhance the quality of life of the community. There is an improvement in the average of mustahik household incomes after becoming a member of ZCD Program. Cibest model demonstrates that material, spiritual, and absolute poverty index decreased by 10, 5, and 6 per cent. Meanwhile, the welfare index is increased by 21 per cent. These findings have significant implications for developing the quality of life in disadvantaged regions in Sijunjung. Therefore, zakat is one of the instruments to change the status of disadvantaged areas to be equivalent to other areas.

scholarly journals A Study of Automatic Judgment of Food Color and Cooking Conditions with Artificial Intelligence Technology

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1128
Author(s):  
Chern-Sheng Lin ◽  
Yu-Ching Pan ◽  
Yu-Xin Kuo ◽  
Ching-Kun Chen ◽  
Chuen-Lin Tien
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Color Space ◽  
Color Difference ◽  
Color Space Conversion ◽  
Before And After ◽  
Artificial Intelligence Technology ◽  
Artificial Intelligence Algorithm ◽  
Time Image ◽  
Cooking Conditions

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.

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