Visualizing the Yield Pattern Outcome for Automatic Data Exploration

2008 ◽  
Author(s):  
Megat Norulazmi Megat Mohamed Noor ◽  
Shaidah Jusoh
Keyword(s):  
Data Exploration ◽  
Automatic Data

Instrumentation For Quantitative Microscopy

1977 ◽  
Vol 35 ◽  
pp. 206-209
Author(s):  
B. Ralph ◽  
A.R. Jones
Keyword(s):  
Volume Fraction ◽  
Three Dimensional ◽  
Two Dimensional ◽  
Automatic Data ◽  
Phase Volume Fraction ◽  
Statistical Confidence ◽  
Resultant Data ◽  
Automatic Data Collection ◽  
Third Dimension ◽  
Evolution Of Microstructure

In all fields of microscopy there is an increasing interest in the quantification of microstructure. This interest may stem from a desire to establish quality control parameters or may have a more fundamental requirement involving the derivation of parameters which partially or completely define the three dimensional nature of the microstructure. This latter categorey of study may arise from an interest in the evolution of microstructure or from a desire to generate detailed property/microstructure relationships. In the more fundamental studies some convolution of two-dimensional data into the third dimension (stereological analysis) will be necessary.In some cases the two-dimensional data may be acquired relatively easily without recourse to automatic data collection and further, it may prove possible to perform the data reduction and analysis relatively easily. In such cases the only recourse to machines may well be in establishing the statistical confidence of the resultant data. Such relatively straightforward studies tend to result from acquiring data on the whole assemblage of features making up the microstructure. In this field data mode, when parameters such as phase volume fraction, mean size etc. are sought, the main case for resorting to automation is in order to perform repetitive analyses since each analysis is relatively easily performed.

Data Screening Methods – Application to Differential Diagnosis in Pancreatic Pathology from Radiological Signs

1978 ◽  
Vol 17 (01) ◽  
pp. 36-40 ◽  
Author(s):  
J.-P. Durbec ◽  
Jaqueline Cornée ◽  
P. Berthezene
Keyword(s):  
Differential Diagnosis ◽  
Mutual Information ◽  
Data Processing ◽  
Screening Methods ◽  
Automatic Data ◽  
Chronic Calcifying Pancreatitis ◽  
Number Of Patients ◽  
Calcifying Pancreatitis ◽  
Pancreatic Pathology ◽  
Data Screening

The practice of systematic examinations in hospitals and the increasing development of automatic data processing permits the storing of a great deal of information about a large number of patients belonging to different diagnosis groups.To predict or to characterize these diagnosis groups some descriptors are particularly useful, others carry no information. Data screening based on the properties of mutual information and on the log cross products ratios in contingency tables is developed. The most useful descriptors are selected. For each one the characterized groups are specified.This approach has been performed on a set of binary (presence—absence) radiological variables. Four diagnoses groups are concerned: cancer of pancreas, chronic calcifying pancreatitis, non-calcifying pancreatitis and probable pancreatitis. Only twenty of the three hundred and forty initial radiological variables are selected. The presence of each corresponding sign is associated with one or more diagnosis groups.

Habits-GDM mobile application in managing gestational diabetes in Singapore: A mixed-methods study (Preprint)

2020 ◽  
Author(s):  
Shilpa Surendran ◽  
Chang Siang Lim ◽  
Gerald Choon Huat Koh ◽  
Tong Wei Yew ◽  
E Shyong Tai ◽  
...  
Keyword(s):  
Mixed Methods ◽  
Randomised Controlled Trial ◽  
Gestational Diabetes ◽  
Healthcare Professionals ◽  
Controlled Trial ◽  
Perceived Usefulness ◽  
Mixed Methods Study ◽  
Automatic Data ◽  
Glucose Testing ◽  
Randomised Controlled

BACKGROUND The prevalence of gestational diabetes mellitus (GDM) is increasing in Singapore and the cost of providing traditional care for GDM is high. Mobile health (mHealth) applications may act as useful tools in the management of GDM. OBJECTIVE The objective of this mixed-methods study was to measure the usage behaviour and explore users’ perceived usefulness of the Habits-GDM application when managing GDM in a randomised controlled trial. METHODS We conducted a quantitative analysis of the application usage behaviour in 170 Habits-GDM application users and 14 semi-structured interviews with users from a randomised controlled trial. RESULTS The convenience of automatic data transfer of weight values to the Habits-GDM application helped users (116/170, 68%) log their weight at least once a week. However, when the application had usability challenges, users avoided using that feature, i.e. users logged only an average of less than one meal/week out of the recommended six meals/week. Of the usability challenges, many users (12/14, 85.7%) mentioned food items not worded in the commonly known way and limited ethnic food database as the primary barriers. Only half of the users (84/170, 49.4%) accessed the educational lessons, but many (9/14, 64%) identified the provision of always available, valuable health-related information as an advantage of the educational lessons. ‘Healthy eating’ and ‘Why exercise’ were the most (56/84, 66.67%) and least (38/84, 45.24%) frequently accessed educational lessons, respectively. Users (10/14, 71.4%) reported sending messages to the coach via the chat interface only when they faced logistic issues and 86.45% of all the coach messages were replies typed by the research coordinator in response to the logistics issues (i.e. a request for blood glucose testing strips and appointment confirmation) raised by the users. Healthcare professionals lack of access to the coach’s dashboard discouraged users from asking queries related to GDM via the e-coaching feature. CONCLUSIONS The findings suggest that mHealth application acts as a useful tool in managing GDM. Culturally sensitive mHealth applications with a provision for women to interact with healthcare professionals should be developed in cooperation with the users. CLINICALTRIAL Not applicable.

An Internet-based health gateway device for interactive communication and automatic data uploading: Clinical efficacy for type 2 diabetes in a multi-centre trial

2016 ◽  
Vol 23 (6) ◽  
pp. 595-604 ◽  
Author(s):  
Jae Hyoung Cho ◽  
Hun-Sung Kim ◽  
Seung Hyun Yoo ◽  
Chang Hee Jung ◽  
Woo Je Lee ◽  
...  
Keyword(s):  
Adverse Events ◽  
Healthcare System ◽  
Glucose Control ◽  
Large Scale ◽  
Diabetes Management ◽  
Intervention Group ◽  
Diabetes Control ◽  
Control Group ◽  
Anthropometric Parameters ◽  
Automatic Data

Introduction The aim of this study was to improve the quality of diabetes control and evaluate the efficacy of an Internet-based integrated healthcare system for diabetes management and safety. Methods We conducted a large-scale, multi-centre, randomized clinical trial involving 484 patients. Patients in the intervention group ( n = 244) were treated with the Internet-based system for six months, while the control group ( n = 240) received the usual outpatient management over the same period. HbA1c, blood chemistries, anthropometric parameters, and adverse events were assessed at the beginning of the study, after three months, and the end of the study. Results There were no initial significant differences between the groups with respect to demographics and clinical parameters. Upon six-month follow-up, HbA1c levels were significantly decreased from 7.86 ± 0.69% to 7.55 ± 0.86% within the intervention group ( p < 0.001) compared to 7.81 ± 0.66% to 7.70 ± 0.88% within the control group. Postprandial glucose reduction was predominant. A subgroup with baseline HbA1c higher than 8% and good compliance achieved a reduction of HbA1c by 0.8 ± 1.05%. Glucose control and waist circumference reduction were more effective in females and subjects older than 40 years of age. There were no adverse events associated with the intervention. Discussion This e-healthcare system was effective for glucose control and body composition improvement without associated adverse events in a multi-centre trial. This system may be effective in improving diabetes control in the general population.

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