Big Data to Artificial Intelligence in Healthcare

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<p>Big Data in healthcare</p> <p>Big Data To Artificial Intelligence in healthcare</p> <p>Highlights and summarize the basic concepts of the work presented by Dr. James Tcheng and Dr. Jason Burke in previous seminar series. 1</p> <p>Agenda</p> <p>Why we study Big Data in healthcare system?</p> <p>Big Data Sources and technique</p> <p>Some Examples of Artificial Intelligence in Healthcare </p> <p>Big Data in healthcare is being used to predict epidemics, cure disease, improve quality of life and avoid preventable deaths.2</p> <p>Need for Big data?</p> <p> Electronic healthdatasets are large, continuously growing, complex, difficult to manage with traditional software</p> <p>90% Unstructured Data</p> <p>25 X as much data over coming decade(One Exabyte by 2020) -Kaiser</p> <p>Boundless data in healthcare about patient condition, procedures and drugs across multiple providers, that are stored by organizations at different locations under different formats.Subjective Decision to Evidence Based Medicine</p> <p>More incentives to professionals to use EHR</p> <p>To answer the questions preciously unanswered</p> <p>3</p> <p>4 Vs of Big data</p> <p>Pyramid for Big Data Needs</p> <p>Why we need to study big data? The answer is to achieve stage 45</p> <p>Big Data Sources &amp; Techniques </p> <p>Feature Selection is a process that chooses an optimal subset of features according to a certain criterion</p> <p>6</p> <p>Future : Artificial Intelligence</p> <p>The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.7</p> <p>Designing treatment plans:IBM Watson launched program for oncologists Provides evidence-based treatment options</p> <p>Assisting repetitive jobs:Medical Sieve : Next generation cognitive assistant with analytical, reasoning capabilities and wide range of clinical knowledge.Assist clinical decision making in radiology and cardiology. </p> <p>Analyze meaning and context of structured and unstructured data in clinical notesCombines the attributes from the patients file with clinical expertise, external research data</p> <p>It is able to analyze radiology images to spot and detect problems faster and more reliably. </p> <p>8</p> <p>Health assistance and medication management:AiCure App supported by The National Institutes of Health is a HIPAA-compliant software Use smartphones webcam and AI to autonomously confirm that patients are adhering to their prescriptions </p> <p>Precision medicine:Deep Genomics aims at identifying patterns in huge data sets of genetic information and medical recordTell doctors what will happen within a cell when DNA is altered by genetic variation</p> <p> captures evidence of medication ingestion. Real-time data are centralized for immediate intervention and longitudinal tracking of adherence patterns.</p> <p>Look for mutations and linkages to disease. </p> <p>9</p> <p>ConclusionStephen Hawking said that development of full artificial intelligence could spell the end of the human race</p> <p>Unraveling Big Data : make right decision at right time for right patients</p> <p>Healthcare is a data-rich domain. As more data is collected, there is increasing demand for big data analytics and AI</p> <p>Efficient utilization of healthcare can yield immediate returns in terms of patient outcomes and lowering cost.</p> <p>10</p>

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