Data Science

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Data science is important to businesses, organizations, and governments, as it can be used to uncover patterns, develop predictive models, and ultimately make informed decisions. Data science has applications across a wide range of industries, from finance and healthcare to marketing and government. Examples of data science applications include stock predictions, healthcare analytics, weather forecasting, and fraud detection. Data science also offers organizations the ability to leverage big data, enabling them to use large-scale datasets to identify trends, uncover relationships, and draw conclusions.

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Related Articles

30 article(s) found

Nature Inspired Bargain Optimization Algorithm for Effective Interpretation of Geoelectrical Data

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Testing Maternal-Fetal Genotype Incompatibility with Mother-Offspring Pair Data

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Predictors of Averse Events After Total Laryngectomy: An Analysis of the 2005-2011 NSQIP Datasets

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Mental Health Promotion Through Collection of Global Opinion Data

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Supporting Quality Data Systems:  Lessons Learned from Early Implementation of Routine Viral Load Monitoring at a Large Clinic in Lilongwe, Malawi

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Hospital Episodes Due to Antidepressant Overdose: An Under-Utilised Source of Pharmacovigilance Data

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Development of a Chronic Obstructive Pulmonary Disease Severity Classification System Using A Japanese Health Insurance Claims Database

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Geoscience and Remote Sensing on Horticulture as Support for Management and Planning

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Morphological Features of Wild Mallard Ducks on Postnatal Growth Based on Functional Analysis of Capture-Recapture Data

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Ovarian Cancer Identification Based on Feature Weighting for High-Throughput Mass Spectrometry Data

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Big Data Research: Database and Computing

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Perception and Significance of Basic Sciences for Clinical Studies

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Basic Sciences. Basis of Clinical Medicine.

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Secular Trend in the Incidence of Japanese Employees with Thyroid Cancer Undergoing Thyroidectomy from 2005 to 2014: a Retrospective Descriptive Study Using an Employment-Based Insurance Claims Database

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Neuroscience Theories, Hypothesis and Approaches to ASD Physiopathology. A Review

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RESinvANFIS v1.0 - A Versatile MATLAB Tool for Inverting Geoelectrical Resistivity Sounding Data using Neuro Fuzzy Technique

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Artificial Neural Network Model for Rainfall Data Analysis During 2004-2017 in Tamil Nadu, India – Prevailing Pattern Evaluation on Climate Change

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Rate, Maternal and Fetal Outcome of Cesarean Delivery Performed by IESO at Shenen Gibe General Hospital, Jimma South West Ethiopia: A Descriptive Retrospective Data

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Models and data Analysis of the Outbreak Risk of COVID-19

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Controlling the Covid-19 Pandemic without Killing the Economy: About Data Driven Decision Making with a Data Model Assessing Local Transmission Risk

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Can Data-Driven Hypotheses Replace the Scientific Method?

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A Missing Data on Covid-19 Forecasts

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Characterizing the Dynamics of Covid-19 Based on Data

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Legal, Marketing, and Advertising Issues with Big Data

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Users Perception and Factors Affecting Data Quality in Nyarugenge Public Health Facility, Rwanda

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Clustering objects for spatial data mining: a comparative study

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Capturing School Data on Bullying and Harassment is Just the Beginning of the Story, Using the Data Can Provide Us with an Ending

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A Data Mining Methodology for Detecting Conspiracy Theories from Scientific Articles: The Covid-19 Case

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Why Do Human Body Systems Go Into Catastrophic System Failure Leading to Diseases -Is the Answer in Science or Nature?

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A Decision Tree Ensemble Approach to Diabetes Prediction using the Framingham Heart Dataset, Exploring the Role of AI-Associated Interventions in Reducing Diabetes-Related Adverse Outcomes Between Men and Women

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