An Advanced Conceptual Diagnostic Healthcare Framework for Diabetes and Cardiovascular Disorders

Sharma, Manik; Singh, Gurvinder; Singh, Rohan

doi:10.4108/eai.19-6-2018.154828

Cited by 20 publications

(11 citation statements)

References 25 publications

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“…A forecast states that in 2019, approximately 26.66 billion IoT devices will be active; by 2025, 75 Billion IoT devices worldwide will be available and wirelessly connected to the Internet [7], [8]. Among these connected devices, millions of wearable sensors are widely used in healthcare applications [9]. The total global spending on the IoT in 2016 was 737 billion dollars and was projected to reach 1.29 trillion dollars in 2020.…”

Section: Introductionmentioning

confidence: 99%

IoT-BBMS: Internet of Things-Based Baby Monitoring System for Smart Cradle

et al. 2019

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The current number of working mothers has greatly increased. Subsequently, baby care has become a daily challenge for many families. Thus, most parents send their babies to their grandparents' house or to baby care houses. However, the parents cannot continuously monitor their babies' conditions either in normal or abnormal situations. Therefore, an Internet of Things-based Baby Monitoring System (IoT-BBMS) is proposed as an efficient and low-cost IoT-based system for monitoring in real time. We also proposed a new algorithm for our system that plays a key role in providing better baby care while parents are away. In the designed system, Node Micro-Controller Unit (NodeMCU) Controller Board is exploited to gather the data read by the sensors and uploaded via Wi-Fi to the AdaFruit MQTT server. The proposed system exploits sensors to monitor the baby's vital parameters, such as ambient temperature, moisture, and crying. A prototype of the proposed baby cradle has been designed using Nx Siemens software, and a red meranti wood is used as the material for the cradle. The system architecture consists of a baby cradle that will automatically swing using a motor when the baby cries. Parents can also monitor their babies' condition through an external web camera and switch on the lullaby toy located on the baby cradle remotely via the MQTT server to entertain the baby. The proposed system prototype is fabricated and tested to prove its effectiveness in terms of cost and simplicity and to ensure safe operation to enable the baby-parenting anywhere and anytime through the network. Finally, the baby monitoring system is proven to work effectively in monitoring the baby's situation and surrounding conditions according to the prototype.

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Section: Introductionmentioning

confidence: 99%

IoT-BBMS: Internet of Things-Based Baby Monitoring System for Smart Cradle

et al. 2019

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“…Indeterminacy is the common issue in real scenarios. Recently, neutrosophy technique is used by many researchers for various applications in medical science such as noise reduction and segmentation, image retrieval disease diagnosis like detecting tumours, diagnosis of human disorders like psychological , chronic, cardiovascular [14], [15], [16] and also fatal diseases [17]. This shows that good execution in terms of indeterminacy and performance is provided by neutrosophy.…”

Section: Introductionmentioning

confidence: 99%

An Ideal Technique for Decision-Making Problems for Uncertain Data and Its Application In Medical Science

Arora¹

2019

IJITEE

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For representing and manipulating uncertain information like fuzzy, incomplete, inconsistent or imprecise, Neutrosophic relation database model is a more general platform, in the human decision-making process. Neutrosophic sets can easily handle real world problems. A new correlation method is introduced in this paper to construct similarity measure, by which decision making problem that exist in real world situation can be easily handled in regard of multiple existing criteria’s or incomplete or inconsistent information. The selection of the best option of alternative can be done by ranking all the other options as per similarity measure depending on concept of similarity. Later in this paper, an explanatory example is given of the proposed method and the comparison results are also presented to show the effective output.. The application in certain domains of medical diagnosis problems having multiple criteria’s in decision making are also discussed in the end of the proposed method.

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“…In other words, the use of data mining techniques assists in extracting precise and significant insights from the deluge of data that have been collected from several manual and digital data sources [4,7]. Data mining has been used in several domains such as agriculture [7][8][9], finance [4,[10][11][12], medical science [13][14][15][16][17], and bio-informatics [18,19].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Statistical and Supervised Learning Techniques in Stock Data Mining

Sharma

Singh

2018

Data

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Nowadays, overwhelming stock data is available, which areonly of use if it is properly examined and mined. In this paper, the last twelve years of ICICI Bank’s stock data have been extensively examined using statistical and supervised learning techniques. This study may be of great interest for those who wish to mine or study the stock data of banks or any financial organization. Different statistical measures have been computed to explore the nature, range, distribution, and deviation of data. The different descriptive statistical measures assist in finding different valuable metrics such as mean, variance, skewness, kurtosis, p-value, a-squared, and 95% confidence mean interval level of ICICI Bank’s stock data. Moreover, daily percentage changes occurring over the last 12 years have also been recorded and examined. Additionally, the intraday stock status has been mined using ten different classifiers. The performance of different classifiers has been evaluated on the basis of various parameters such as accuracy, misclassification rate, precision, recall, specificity, and sensitivity. Based upon different parameters, the predictive results obtained using logistic regression are more acceptable than the outcomes of other classifiers, whereas naïve Bayes, C4.5, random forest, linear discriminant, and cubic support vector machine (SVM) merely act as a random guessing machine. The outstanding performance of logistic regression has been validated using TOPSIS (technique for order preference by similarity to ideal solution) and WSA (weighted sum approach).

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An Advanced Conceptual Diagnostic Healthcare Framework for Diabetes and Cardiovascular Disorders

Cited by 20 publications

References 25 publications

IoT-BBMS: Internet of Things-Based Baby Monitoring System for Smart Cradle

IoT-BBMS: Internet of Things-Based Baby Monitoring System for Smart Cradle

An Ideal Technique for Decision-Making Problems for Uncertain Data and Its Application In Medical Science

Performance Analysis of Statistical and Supervised Learning Techniques in Stock Data Mining

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