scholarly journals Nutrient profiling: comparison and critical analysis of existing systems

2006 ◽  
Vol 9 (5) ◽  
pp. 613-622 ◽  
Author(s):  
V Azaïs-Braesco ◽  
C Goffi ◽  
E Labouze

AbstractBackgroundNutrient profiling systems aim at positioning foodstuffs relative to each other according to their contribution to a balanced diet. The accuracy and performance of methodologies are still debated. We present here a critical analysis of the structure and efficiency of the current schemes.MethodsThe literature survey detected only four systems addressing the issue on an ‘across the board’ approach and with enough detail to enable analysis. The building principles of these systems were compared and their performance was estimated via their classification of a series of 125 foodstuffs on the basis of nutritional composition. These classifications were compared with one another and with an empirical classification by expert nutritionists.ResultsAll systems gave a similar overview, with fruits and vegetables ranked as the most favourable foods and fatty and sugary foods as the least favourable ones, but numerous discrepancies existed in every system, mainly related to their choice of nutrients and thresholds. The FSA scoring system seemed the most consistent approach, although it still generated some questionable rankings. Expert classification did not clearly validate any scheme, and cannot be considered as a true reference.ConclusionNutrient profiling systems are confirmed to be powerful tools to translate nutritional information related to the whole diet into the level of individual foods. However, the performance of the existing schemes remains moderate. Alternative approaches, such as considering food categories or introducing more stringent validation steps by a panel of expert nutritionists, could be ways to reach more efficient and consensual tools.

Author(s):  
Dr. Vijeet Meshram ◽  
Dr. A.B. Sasankar

Out of the many authentication schemes in this paper we are trying to focus on the performance and classification of one of the techniques of authentication that is the biometric authentication. Although efforts of the entire international biometric community, the measurement of accuracy of a biometric system is far to be completely investigated and, eventually, standardized. The paper presents a critical analysis of the measurement of an accuracy and performance of a biometric system.


Author(s):  
Zia Parveen ◽  
Sunita Mishra

The main objective of the study is to evaluate the nutritional composition of orange peel and tomato for the development of natural colour to increase the awareness about the use of natural food colour which reduces the risk assessment of artificial colour. Fruits are very important constituents of the diet and provide nutrients such as, vitamin, minerals, and fibre etc. Orange is one of the most popular fruits in the world. It is rich in nutrient like vitamin C, folic acid, carotenoids, flavonoids etc. These nutrients are very useful for boosting immunity. In this study we discus about nutritional composition of orange peel and tomato. Proximate analysis of each sample was conducted to evaluate the moisture, fat, protein, ash etc. The morphological analysis of the samples was done by using scanning electron microscope which helps in identifying the different structural forms of the samples. Results of the study suggest that orange peel and tomato both have a good nutritional property. The fat, protein, ash and fibre content in orange peel was found to be 3.4, 4.8, 4.2 and 8.3 respectively while in tomato the values are 0.24, 2.26, 0.18 and 1.19 respectively. Orange peel removed the amount of cholesterol and fight against heart diseases in your body because orange peel contains pectin and natural fibre, it controls our blood pressure and helpful for weight loss. Tomato is an edible, red berry types of fruits. Tomatoes contribute to a healthy well-balanced diet. Because they are rich in nutrients like minerals, vitamins (B and C), sugar and dietary fibre. Tomato is a good source of lycopene; it is a red colour pigment present in high amount (2573 μg) per 100 tomatoes is a very good sources of raw materials for fruits and vegetables industry.


Author(s):  
Saliha Zahoor ◽  
Ikram Ullah Lali ◽  
Muhammad Attique Khan ◽  
Kashif Javed ◽  
Waqar Mehmood

: Breast Cancer is a common dangerous disease for women. In the world, many women died due to Breast cancer. However, in the initial stage, the diagnosis of breast cancer can save women's life. To diagnose cancer in the breast tissues there are several techniques and methods. The image processing, machine learning and deep learning methods and techniques are presented in this paper to diagnose the breast cancer. This work will be helpful to adopt better choices and reliable methods to diagnose breast cancer in an initial stage to survive the women's life. To detect the breast masses, microcalcifications, malignant cells the different techniques are used in the Computer-Aided Diagnosis (CAD) systems phases like preprocessing, segmentation, feature extraction, and classification. We have been reported a detailed analysis of different techniques or methods with their usage and performance measurement. From the reported results, it is concluded that for the survival of women’s life it is essential to improve the methods or techniques to diagnose breast cancer at an initial stage by improving the results of the Computer-Aided Diagnosis systems. Furthermore, segmentation and classification phases are challenging for researchers for the diagnosis of breast cancer accurately. Therefore, more advanced tools and techniques are still essential for the accurate diagnosis and classification of breast cancer.


Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2648
Author(s):  
Muhammad Aamir ◽  
Tariq Ali ◽  
Muhammad Irfan ◽  
Ahmad Shaf ◽  
Muhammad Zeeshan Azam ◽  
...  

Natural disasters not only disturb the human ecological system but also destroy the properties and critical infrastructures of human societies and even lead to permanent change in the ecosystem. Disaster can be caused by naturally occurring events such as earthquakes, cyclones, floods, and wildfires. Many deep learning techniques have been applied by various researchers to detect and classify natural disasters to overcome losses in ecosystems, but detection of natural disasters still faces issues due to the complex and imbalanced structures of images. To tackle this problem, we propose a multilayered deep convolutional neural network. The proposed model works in two blocks: Block-I convolutional neural network (B-I CNN), for detection and occurrence of disasters, and Block-II convolutional neural network (B-II CNN), for classification of natural disaster intensity types with different filters and parameters. The model is tested on 4428 natural images and performance is calculated and expressed as different statistical values: sensitivity (SE), 97.54%; specificity (SP), 98.22%; accuracy rate (AR), 99.92%; precision (PRE), 97.79%; and F1-score (F1), 97.97%. The overall accuracy for the whole model is 99.92%, which is competitive and comparable with state-of-the-art algorithms.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 861-862
Author(s):  
Z. Izadi ◽  
T. Johansson ◽  
J. LI ◽  
G. Schmajuk ◽  
J. Yazdany

Background:The Rheumatology Informatics System for Effectiveness (RISE) Registry was developed by the ACR to help rheumatologists improve quality of care and meet federal reporting requirements. In the current quality program administered by the U.S. Centers for Medicare and Medicaid services, rheumatologists are scored on quality measures, and performance is tied to financial incentives or penalties. Rheumatoid arthritis (RA)-specific quality measures can only be submitted through RISE to federal programs.Objectives:This study used data from the RISE registry to investigate rheumatologists’ federal reporting patterns on five RA-specific quality measures in 2018 and investigated the effect of practice characteristics on federal reporting of these measures.Methods:We analyzed data on all rheumatologists who continuously participated in RISE between Jan 2017 to Dec 2018 and who had patients eligible for at least one RA-specific measure. Five measures were examined: tuberculosis screening before biologic use, disease activity assessment, functional status assessment, assessment and classification of disease prognosis, and glucocorticoid management. We assessed whether or not rheumatologists reported specific quality measures via RISE. We investigated the effect of practice characteristics (practice structure; number of providers; geographic region) on the likelihood of reporting using adjusted analyses that controlled for measure performance (performance in 2018; change in performance from 2017; and performance relative to national average performance). Analyses accounted for clustering by practice.Results:Data from 799 providers from 207 practices managing 213,757 RA patients was examined. The most common practice structure was a single-specialty group practice (53%), followed by solo (28%) and multi-specialty group practice (12%). Most providers (73%) had patients eligible for all five RA quality measures. Federal reporting of quality measures through RISE varied significantly by provider, ranging from no reporting (60%) to reporting all eligible RA measures (12.2%). Reporting through RISE also varied significantly by quality measure and was highest for functional status assessment (36%) and lowest for assessment and classification of disease prognosis (20%). Small practices (1-4 providers) were more likely to report all eligible RA quality measures compared to larger practices (21%, 6%; p<0.001). In adjusted analyses, solo practices were more likely than single-specialty group practices to report RA measures (42%, 31%; p<0.027) while multispecialty group practices were less likely (18%, 31%; p<0.001). Additionally, higher performance in 2018 and performance ≥ the national average performance was associated with federal reporting of the measures through RISE (p≤0.004).Conclusion:Forty percent of U.S. rheumatologists participating in RISE used the registry for federal quality reporting. Physicians using RISE for reporting were disproportionately in small and solo practices, suggesting that the registry is fulfilling an important role in helping these practices participate in national quality reporting programs. Supporting small practices is especially important given the workforce shortages in rheumatology. We observed that practices reporting through RISE had higher measure performance than other participating practices, which suggests that the registry is facilitating quality improvement. Studies are ongoing to further investigate the impact of federal quality reporting programs and RISE participation on the quality of rheumatologic care in the United States.Disclaimer: This data was supported by the ACR’s RISE Registry. However, the views expressed represent those of the authors, not necessarily those of the ACR.Disclosure of Interests:Zara Izadi: None declared, Tracy Johansson: None declared, Jing Li: None declared, Gabriela Schmajuk Grant/research support from: Pfizer, Jinoos Yazdany Grant/research support from: Pfizer


Author(s):  
V. Vijaya Kishore ◽  
R.V.S. Satyanarayana

A vital necessity for clinical determination and treatment is an opportunity to prepare a procedure that is universally adaptable. Computer aided diagnosis (CAD) of various medical conditions has seen a tremendous growth in recent years. The frameworks combined with expanding capacity, the coliseum of CAD is touching new spaces. The goal of proposed work is to build an easy to understand multifunctional GUI Device for CAD that performs intelligent preparing of lung CT images. Functions implemented are to achieve region of interest (ROI) segmentation for nodule detection. The nodule extraction from ROI is implemented by morphological operations, reducing the complexity and making the system suitable for real-time applications. In addition, an interactive 3D viewer and performance measure tool that quantifies and measures the nodules is integrated. The results are validated through clinical expert. This serves as a foundation to determine, the decision of treatment and the prospect of recovery.


Author(s):  
E.V. Titov ◽  

The purpose of the article is a critical assessment of the established in the legal literature and practice the concept and characteristics of a legal action and criteria for distinguishing legal actions and events. The main problem identified by the author is that, despite the huge number of sources on this subject, jurisprudence has not progressed in the study of this phenomenon since the early 19th century. The definition and characteristics of a legal action «migrate» from one work to another, as a rule, without any critical analysis at all and are taken by lawyers as a given, which leads to stagnation in the development of the relevant field. At the same time, studies of specific varieties of legal actions often reach a deadlock precisely because of the incorrectly defined general characteristics of a legal action. The author defines the classification criterion of differentiation of legal facts, and argues the necessity of two-member division of legal facts into events and actions. It is proved that facts-states cannot be distinguished within the classification of legal facts on the volitional ground and they are not legal facts at all. The concept of legal action and its characteristics are given. The concept of will as a key element of legal action is discussed in the article and it is substantiated that «involuntary» actions are not legal facts. The author analyzes the classification of events into absolute and relative, and offers an algorithm for determining whether a certain legal fact refers to events or actions.


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