Academia.edu no longer supports Internet Explorer.
To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser.
2011 24th International Symposium on Computer-Based Medical Systems (CBMS)
Proceedings of the 24th International Symposium on Computer-Based Medical Systems — CBMS 2011 Bristol, UK2011 •
Extensive amounts of data stored in medical databases require the development of dedicated tools for accessing the data, data analysis, knowledge discovery, and effective use of sloretl knowledge and data. Widespread use of medical information systems and explosive enlargement of medical databases require conventional manual data analysis to be coupled with methods for competent computer-assisted analysis. In this paper, I use Data Mining techniques for the data analysis, data accessing and knowledge discovery procedure to show experimentally and practically that how consistent, able and fast are these techniques for the study in the particular field? A solid mathematical threshold (0 to 1) is set to analyze the data. The obtained outcome will be tested by applying the approach to the databases, data warehouses and any data storage of different sizes with different entry values. The results shaped will be of different level from short to the largest sets of tuple. By this, we may take the results formed for different use e.g. Patient investigation, frequency of different disease.
2013 24th International Workshop on Database and Expert Systems Applications
Clinical Data Mining: Problems, Pitfalls and Solutions2013 •
International Journal of Engineering Research and Technology (IJERT)
IJERT-A Review on Data Mining Techniques and Challenges in Medical Field2020 •
https://www.ijert.org/a-review-on-data-mining-techniques-and-challenges-in-medical-field https://www.ijert.org/research/a-review-on-data-mining-techniques-and-challenges-in-medical-field-IJERTV9IS080143.pdf The healthcare industry has witnessed an enormous evolution in producing huge amounts of medical data that have given rise to research in multiple areas. Many researchers reviewed and surveyed the healthcare, which is an active interdisciplinary field of data mining. Technological advances in information on health care, digitizing health records, have resulted in rapid growth of the healthcare sector. Electronic Health Record Systems (EHRs) are the data repositories which are the digitized format for the medical data storage. Healthcare sector manages enormous amounts of data that needs to be analyzed to provide a better solution for better decision making. The main challenge is how to use the data mining techniques to effectively discover useful and important information among the massive amount of data available. It plays a major role in the advancement and development of new techniques that work effectively for the huge data in healthcare. The related information is collected that demonstrates the importance of data mining in health care. This paper mainly focuses on the necessity of data mining in medical field, its applications in health sector, different predictive and descriptive data mining techniques that can be used in various applications of healthcare sector and challenges that are involved in mining the health data.
International Statistical Review
Data Science and Predictive Analytics: Biomedical and Health Applications Using RIvo D.DinovSpringer, 2018, xxxiv + 832 pages, $89.99, hardcover ISBN: 978‐3‐319‐72346‐42019 •
Journal of health informatics
Association and Classification Data Mining Algorithms Comparison over Medical Datasets2013 •
International Journal of Engineering Research and Technology (IJERT)
IJERT-Survey on Predictive Medical Data Analysis2014 •
https://www.ijert.org/survey-on-predictive-medical-data-analysis https://www.ijert.org/research/survey-on-predictive-medical-data-analysis-IJERTV3IS042253.pdf The medical field is one of the most important industries that can benefit vastly from the many advantages of Cloud Computing and data mining tools. The system we propose combines both domains by enabling doctors, patients, pharmacists, pharmaceutical companies to find hidden trends in medical data (EMRs) stored on a cloud and thus, predict trends for the future. The system is to be supported by a knowledge base that will store recorded data and enhance predictions. The dataset consists of the attributes namely: age, gender, region, climate, time period, diseases and respective diagnosis. A user of the system can find patterns of diseases under one of the categories: age, gender, region and time period. The proposed system explores the application of the k-means algorithm to cluster the data and tests for any modification of the algorithm that maybe required for producing more efficient and accurate results..
2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM)
A Machine Learning View for Health Data Mining Emphasizes on The Decision Trees2020 •
Health data analysis can discover the secret trends in health field variables with enormous promise. Such variations can also be used to identify medically. Furthermore, unprocessed, large-scale, disparate, and weighty clinical data can be found. The information must be compiled in a systematic way. Such information can be further merged into a patient data system. Big data software presents a user-focused appearance to fresh including unknown information trends. The processing of statistical information is targeted at processing the information and mechanisms of software. The results are diverse, while the big data system is monolithic. They describe a variety of fields in which these methods can be used for information exploration of health systems. Throughout this article, we discuss momentarily the effect of data analysis methods to clinical imaging, like computational models.
dialnet.unirioja.es
MASONERÍA Y SOCIEDADES SECRETAS DE LA GRANDE ARMÉE HACIA EL NUEVO MUNDOThe Breakup of India and Palestine: The Causes and Legacies of Partition
"Civil War, Total War, or a War of Partition? Reassessing the 1948 War in Palestine from a Global Perspective."2023 •
А.В.Циммерлинг. Идиомы и синтаксис предложения: к диагностике подъема в русском языке // VII международная конференция "Культура Речи" (Гротовские чтения). Москва, Институт русского языка им. В.В.Виноградова РАН, 05-07.03.2024.
Idioms and Clausal Syntax: on the Diagnostics of Raising in Russian2024 •
International Labor and Working-class History
Geoff Eley, ed., Society, Culture, and the State in Germany, 1870–1930. Ann Arbor: University of Michigan Press, 1996. viii + 522 pp. $59.50 cloth1998 •
Biología pesquera
Determinación de edad y crecimiento de Seriolella caerulea GUICHENOT, 1848 de la zona Sur-Austral de Chile2024 •
European Heart Journal
High-sensitivity troponin T is predictive of adverse outcome after acute ischemic stroke2013 •
2021 •
2011 •
Jurnal Pengembangan Penyuluhan Pertanian
Pengaruh Pemberian Bungkil Kedelai Dan Suplementasi Zinc, Selenium Dan Vitamin E Terhadap Penampilan Estrus Pada Kambing Peranakan Etawah (The Effect Of Supplementation With Soybean Meal, Minerals And Vitamins On Estrus Performance Of Etawah Crossbreed Goats)2019 •
Journal of Agriculture, Science and Technology
Pyrethrum marc rates and intra-row spacing influence on selected soil chemical parameters and yield of bush bean (Phaseolus Vulgaris L.) grown on andosol under rainfed conditionsOsmanli Mirasi Arastirmalari Dergisi
Sultan II. Abdülhami̇d İn Ai̇le Albümünde Bulunan Erkek Çocuklarin Kiyafetleri̇ni̇n İncelenmesi̇2018 •
IAES International Journal of Artificial Intelligence
A systematic review on research trends, datasets, algorithms, and frameworks of children’s nutritional status prediction2024 •