e-Doctor: A Web based Support Vector Machine for Automatic Medical Diagnosis

Kampouraki, A.; Vassis, Dimitris; Belsis, Petros; Skourlas, Christos

doi:10.1016/j.sbspro.2013.02.078

Cited by 17 publications

(3 citation statements)

References 4 publications

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“…Kampourakia et al [11] have introduced a web-based application that is based on SVMs to makes automatic diagnoses about health problems. Razzaghi et al [12] have proposed multilevel SVM-based algorithms.…”

Section: Related Workmentioning

confidence: 99%

“…The Women Tobacco Smoking Questionnaire (WTSQ): developed by the Principle Investigator, which is designed as a single measure to assess pattern of tobacco smoking among women. The questionnaire consist of four sections: (1) Demographics which includes age, educational level, marital status, etc., (2) tobacco smoking status asking about history of smoking habits, waterpipe smoking habits, (3) depression symptoms scale [15], this scale includes 6 items that assess the presence of depression, (4) Waterpipe Nicotine Dependence Scale [11], this scale measures level of nicotine dependence among waterpipe smokers, (5) waterpipe smoking during Ramadan, this part ask participants about their waterpipe smoking during Ramadan. Response options in the questionnaire vary based on the construct and items measuring that construct.…”

Section: A Studied Datasetmentioning

confidence: 99%

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A Machine Learning Approach for Predicting Nicotine Dependence

Kharabsheh¹,

Meqdadi²,

Al-Abed³

et al. 2019

ijacsa

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An examination of the ability of machine learning methodologies in classifying women Waterpipe (WP) smoker's level of nicotine dependence is proposed in this work. In this study, we developed a classifier that predicts the level of nicotine dependence for WP tobacco female smokers using a set of novel features relevant to smokers including age, residency, and educational level. The evaluation results show that our approach achieves a recall of 82% when applied on a dataset of female WP smokers in Jordan.

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Section: Related Workmentioning

confidence: 99%

Section: A Studied Datasetmentioning

confidence: 99%

A Machine Learning Approach for Predicting Nicotine Dependence

Kharabsheh¹,

Meqdadi²,

Al-Abed³

et al. 2019

ijacsa

View full text Add to dashboard Cite

show abstract

“…In the end, they are asked a few questions and according to their answers, the expert system diagnosis diseases based on its knowledge base. Finally, the algorithm ranks the results and display them in a fuzzy form [10,11,12]. Another approach to achieve an automatic medical diagnosis system is e-Doctor.…”

Section: Related Workmentioning

confidence: 99%

Web application for self-diagnosis and drug recommendation based on user symptoms

2019

J. adv. tec. eng. res.

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Throughout the evolution of the Internet and social networks, forums and online platforms have a vital role in sharing information, along with the creation and engagement of virtual communities. Such websites represent great resources, and they are the irst step in the adoption of e-health services. When the persons are ill, many of them use search engines for self-diagnosis and gather possible treatment ideas before asking for a doctor's opinion. This takes a lot of time because the information is scattered across various forums and websites. In this paper is presented an application that aims to provide an online self-diagnosis and drug recommendation tool based on natural language processing of the symptoms described by the user. Over 2,200 medicines are stored in the database, each having a set of keywords according to their usage. Thus, the platform automates the search process, and provides the user with the most relevant information, eliminating the need for manual data interpretation. The results are ranked according to the con idence score obtained after the execution of the fuzzy search algorithm. The platform does not provide medical advice. Thus it is intended for informational purposes only. The developed platform is not a substitute for professional medical advice, diagnosis or treatment. Another feature of the platform is that it enables users to ind hospitals and clinics around them, so that they can receive professional healthcare service. The ield of medicine is a sensitive topic due to the fact that one mistake could lead to the loss of countless human lives. It was a long and dif icult journey to reach the current state of medicine, but technology was and will remain essential to the evolution of the healthcare system. The proposed solution of this paper is customized for Romania but it can be adapted for other countries by replacing the drug database.

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