Meenakshi Sharma ¹, Himanshu Aggarwal ²

Affiliations
1 Computer Science and Engineering Department, S.S.C.E.T, Badhani - 145001, Punjab, IN
2 Computer Engineering Department, Punjabi University, Patiala - 147002, Punjab, IN

Abstract

Background/Objectives: Electronic Health Record are unique electronic documents composed of information like patient history records, demographics, prescribed medications, laboratory reports and computerized tomography etc. to pertaining the patient health care. The main objective of the paper is to review the present adoption rate of EHR in India with respect to global market. Methods/Statistical Analysis: EHR is the key component for the clinical decision support system .To review the current scenario of adaption rate of EHR, bibliographic learning was obtained from many hospital sources. In addition, contact was made with EHR vendors. Findings: During the pilot study of about seven month, around twenty major hospitals encounters in which successfully the EHR system has been implemented. Globally the adoption rate of EHR in major countries are China (96%), Brazil (92%), France (85%), and Russia (93%) in this respect. In year of 2020, globally Market of electronic health records will place at US$25.98 billion as per the reporting of CAGR. Interoperability standards issues; lack of funds; shortage of suitable governance health policies are the major barriers in adoption of EHR in India. Application/Improvements: Adoption and implementation of EHR should be made mandatory in large sized and medium sized hospitals. In upcoming years EHR system require to incorporated a framework of standards, latest tools and consolidation of system providers.

Keywords

Electronic Health Record, FHIR, HL7, Public Health, Security.

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Meenakshi Sharma ¹, Sanjay Kumar Singh ¹, Prateek Agrawal ¹, Vishu Madaan ¹

Affiliations
1 School of Computer Science Engineering, Lovely Professional University, Phagwara - 144411, Punjab, IN

Abstract

Background/Objectives: The primary objective of this paper is to classify the clinical dataset of cervical cancer to identify the stage of cancer which helps in proper treatment of patient suffering from cancer. Methods/Statistical Analysis: This research work basically moves toward the detection of cervical cancer using Pap smear images. Analysis of Pap smear of cervical region is an efficient technique to study any abnormality in cervical cells. The proposed system firstly segment the pap image using Edge Detection to separate the cell nuclei from cytoplasm and background and then extract various features of cervical pap images like area, perimeter, elongation and then these features are normalized using min-max method. After normalization KNN method is used to classify cancer according to its abnormality. Findings: The classification accuracy with 84.3% of maximum performance with no validation and classification accuracy with 82.9% of maximum performance with 5 Fold cross validation is achieved.

Keywords

Cervical Cancer, Cell Images, Classification, Pap Smear Test.

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