Performance Analysis Of Various Data Mining Classification Techniques On Healthcare Data

Gupta, Shelly; Kumar, D. Vimal; Sharma, Anand

doi:10.5121/ijcsit.2011.3413

Cited by 18 publications

(4 citation statements)

References 15 publications

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“…Artificial Intelligence classification algorithms are used for predicting classes from data based on supervised learning techniques. Many classification algorithms can be found in this area but in this work five different well known classification algorithms [28], [29] are introduced for being the ones applied: Logistic regression (LR), K-Nearest Neighbours (KNN), Support Vector Machine (SVM), J48 and Logistic Model Tree (LMT). LR is an statistical method used for finding the best fitting model that represents the best dependent variable (the class).…”

Section: B Artificial Intelligence-based Classifiersmentioning

confidence: 99%

Eye-based keystroke prediction for natural texts – a feasibility analysis

Cazorla

Fuentes

González-Manzano

2022

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

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The use of videoconferencing is on the rise after COVID-19, being common to look at the screen and see someone typing. A side-channel attack may be launched to infer the text written from the face image. In this paper, we analyse the feasibility of such an attack, being the first proposal which work with a complete keyset (50 keys) and natural texts. We use different scenarios, lighting conditions and natural texts to increase realism. Our study involves 30 participants, who typed 49,365 keystrokes. We characterize the effect of lighting, gender, age and use of glasses. Our results show that on average 13.71% of keystrokes are revealed without error, and up to 31.8%, 52.5% and 61.2% are guessed with a maximum error of 1, 2 and 3 keys, respectively.

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Section: B Artificial Intelligence-based Classifiersmentioning

confidence: 99%

Eye-based keystroke prediction for natural texts – a feasibility analysis

Cazorla

Fuentes

González-Manzano

2022

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

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“…This is in contrast to using an individual classifier, which may not be as effective. Diabetes is a chronic illness that affects the bodyʹs ability to produce insulin, a hormone that regulates blood sugar levels [1]. As a result, people with diabetes often have high blood sugar levels, which can lead to a number of health complications.…”

Section: Introductionmentioning

confidence: 99%

Detection of Diabetic through Micro Array Genes with enhancement of Classifiers Performance

Chellappan¹,

Rajaguru²

2023

Preprint

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Diabetes becomes a life threatening non-communicable disease in the world, according to International Diabetic Federation (IDF) in 2023, an estimated 537 million adults (20-79 years) are living with diabetes, which is equivalent to 9.3% of the global adult population. This number is predicted to rise to 643 million by 2030 and 783 million by 2045. Over 3 in 4 adults with diabetes live in low- and middle-income countries. Diabetes is a persistent metabolic condition marked by increased levels of glucose in the bloodstream. It is a significant global health concern, affecting millions of individuals worldwide. It having the symptoms of drowsiness for the whole day if not properly examined or treated well. It is targeted to spread over the younger age community and the number is growing in the exponential fashion. Even day to day many advancements have come from the researcher to diagnose, to find solutions to prevent from newer entry. Authors have taken a dataset with 57 non diabetic and 20 diabetic patients with the total 28735 micro array gene to undergone pre-processing process and reduced up to 22960 gene data using Dimensionality Reduction (DR) such as Detrend Fluctuation Analysis (DFA), Chi square probability density function (Chi2PDF), Firefly algorithm Cuckoo search were used in this research. Meta heuristic algorithms like Particle swarm Optimization (PSO) and Harmonic Search (HS) are used for feature selection. Further seven classification techniques such as Non-Linear Regression (NLR), Linear Regression (LR), Logistics Regression (LoR), Gaussian Mixture Model (GMM), Bayesian Linear Discriminant Classifier (BLDC), Softmax Discriminant Classifier (SDC), Support Vector Machine – Radial Basis Function (SVM-RBF) are using to make a decision, predictive analysis and segregate the data according to the level of blood glucose as Diabetic Patient (DP) and Non-Diabetic Patient (NDP).

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“…Other research has attempted to use machine learning algorithms to perform breast cancer diagnosis or prognosis. Diagnosis and prognosis present medical personnel with great challenges, and using statistical models to aid in these predictions has revolutionized this part of the medical field [5]. Gupta et al provide a survey on popular techniques used to diagnose cancers and cancer relapses [5].…”

Section: Related Workmentioning

confidence: 99%

An Association Analysis of Breast Cancer with Carotenoids.

Neumann¹,

El-Hajj²

EPiC Series in Computing

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The environment and the exposure individuals carry throughout their lifetime can gar- ner diverse effects on their health. This paper discusses the application of association analysis, to determine relationships between carcinogenesis and the human exposome. Human exposome data from the World Health Organization was analyzed to determine associations between human exposure and breast cancer. The discovered associations outline specific factors that may be associated with the prevention or causation of breast cancer. We discovered an association between biomarkers in specific biospecimens and breast cancer. Xanthophylls, measured in two different biospecimens, were determined to be associated with American breast cancer patients. The associations discovered may be of use in future cancer studies. This research is particularly interesting because of xanthophylls’ relationship to retinol, inhibiting oncogenesis. Providing support and data for such associations will encourage more research on the exposome’s effect on breast cancer and other conditions.

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Performance Analysis Of Various Data Mining Classification Techniques On Healthcare Data

Abstract: ABSTRACT

Cited by 18 publications

References 15 publications

Eye-based keystroke prediction for natural texts – a feasibility analysis

Eye-based keystroke prediction for natural texts – a feasibility analysis

Detection of Diabetic through Micro Array Genes with enhancement of Classifiers Performance

An Association Analysis of Breast Cancer with Carotenoids.

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