Big Data to Artificial Intelligence in Healthcare

Download Big Data to Artificial Intelligence in Healthcare

Post on 15-Apr-2017

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Big Data in healthcareBig Data To Artificial Intelligence in healthcareHighlights and summarize the basic concepts of the work presented by Dr. James Tcheng and Dr. Jason Burke in previous seminar series. 1AgendaWhy we study Big Data in healthcare system?Big Data Sources and techniqueSome Examples of Artificial Intelligence in Healthcare Big Data in healthcare is being used to predict epidemics, cure disease, improve quality of life and avoid preventable deaths.2Need for Big data? Electronic healthdatasets are large, continuously growing, complex, difficult to manage with traditional software90% Unstructured Data25 X as much data over coming decade(One Exabyte by 2020) -KaiserBoundless 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 MedicineMore incentives to professionals to use EHRTo answer the questions preciously unanswered34 Vs of Big dataPyramid for Big Data NeedsWhy we need to study big data? The answer is to achieve stage 45Big Data Sources & Techniques Feature Selection is a process that chooses an optimal subset of features according to a certain criterion6Future : Artificial IntelligenceThe 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.7Designing treatment plans:IBM Watson launched program for oncologists Provides evidence-based treatment optionsAssisting 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. Analyze meaning and context of structured and unstructured data in clinical notesCombines the attributes from the patients file with clinical expertise, external research dataIt is able to analyze radiology images to spot and detect problems faster and more reliably. 8Health 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 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 captures evidence of medication ingestion. Real-time data are centralized for immediate intervention and longitudinal tracking of adherence patterns.Look for mutations and linkages to disease. 9ConclusionStephen Hawking said that development of full artificial intelligence could spell the end of the human raceUnraveling Big Data : make right decision at right time for right patientsHealthcare is a data-rich domain. As more data is collected, there is increasing demand for big data analytics and AIEfficient utilization of healthcare can yield immediate returns in terms of patient outcomes and lowering cost.10

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