Big data breakthroughs in healthcare: from re-active to pro-active care
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1. The document discusses how analyzing unstructured healthcare data through techniques like iKnow text analysis can help drive more proactive care by enabling early detection of conditions like hepatitis C, sepsis, and delirium from nursing notes. 2. Results show the approach achieved AUC scores of 0.801-0.823 for detecting delirium and 0.809-0.823 for detecting sudden patient deterioration using nursing notes, outperforming traditional bag-of-words methods. 3. Further research opportunities include analyzing more data, reducing the number of features through techniques like latent semantic indexing and autoencoders, and combining structured data with current prediction methods to improve early detection of conditions from clinical notes.
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An ancient System for holistic health (mental and physical) and wellbeing, is a scientific art of living with harmony (connecting) of mind and body. Although much more ancient than Patanjali, who documented yoga systematically about 2000 years ago, Patanjali is often referred to as the "father of modern yoga."
Yoga postures are commonly depicted in ancient paintings, carvings, and sculptures in almost all civilizations and religions, thus Yoga cant be described as an act of Hinduism. It originated long before any religion on Earth, with the emergence of life on the Planet. All yoga poses are natural, and what is not natural is not yoga; it is油Viyoga.
Besides Vedic Yoga, Hatha, Vinyasa, Ashtanga, Iyengar, Yin, Restorative, Kundalini, Bikram, Sahaj, and Power yoga are some popular types.
Vinyasa油Yoga is the closest form to Vedic Yoga; it is known for its flowing movements, not very rigorous, not too much straining, actions flow with the breath.
Though all yoga may lead to meditation (Dhyan) for your inner upliftment, it is not the same as described in Hinduism for self-liberation.
In Hinduism, different paths of life looking distinct but can be practiced all together, they are: Karma Yoga (selfless action and service), Bhakti Yoga (devotion and love for God or Godly power), Jnana (Gyan) Yoga (gaining knowledge for self-realization through wisdom), Dhyan Yoga (meditation) and Kriya Yoga (optimum utilization of your vital and muscular energy).油
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This presentation is for educational purposes only. Coarse Dispersion, Physical Pharmaceutics
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Big data breakthroughs in healthcare: from re-active to pro-active care
- 1. Big Data breakthroughs in HealthCare: from re-active to pro-active care Dirk Van Hyfte MD, PhD
- 3. Upwards of 80 95% of Healthcare Data Is Unstructured Patient complaints Notes, observations Theories, opinions Conclusions Unstructured Data Coded fields Values Lab results Structured Data
- 4. Classical Text Analysis Top Down Approach
- 6. Examples of the iKnow Text Analysis Breakthroughs in Action Intelligent EHR Navigation Patient Cohort ID Driving Actions with Real World Predictive Models Breakthrough Population Screening Finding Elusive Unknowns
- 7. Driving actions with real world predictve models Early detection of Hepatitis C Seculsion Sepsis Delirium
- 8. Early detection of Hepatitis C Injecting drug user Hiv Lft Acupuncture PiercingTattoo Prison stay Men having sex with men Household & sex partners of hep carriers Country of origin Transfusion before 1992
- 9. Early detection of Seclusion
- 11. HealthCare Journey Prevention of Hepatitis C Seculsion Sepsis Delirium Personalised Medicine Cancer therapy
- 12. HealthCare Journey Prevention of Hepatitis C Seculsion Sepsis Delirium Personalised Medicine Cancer therapy proactivereactive
- 13. Protocol design based on How long will the trial take? Will we be able to recruit the necessary volume of patients in order to collect data with sufficient statistical power to meet regulatory requirements? Where will we find sufficient numbers of the right patients? Do the inclusion/ex clusion criteria make sense?
- 14. Protocol design based on How long will the trial take? Will we be able to recruit the necessary volume of patients in order to collect data with sufficient statistical power to meet regulatory requirements? Where will we find sufficient numbers of the right patients? Do the inclusion/ex clusion criteria make sense? Real World Clinical Data: both structured fields and clinical notes
- 15. Healthcare & Life Science Journey Expert
- 16. Healthcare & Life Science Journey ExpertData
- 17. Healthcare & Life Science Journey ExpertData
- 19. Overview Problem description Data Methods Results & conclusion Further Research
- 20. Problem Is it possible to detect early: sudden patient deterioration or a delirium using nursing notes ?
- 21. Data Delirium 3534 patients 1044 positive ( 29,54 %) Maximum of 4 days ahead / 4 consecutive days Sudden deterioration 1141 patients 391 positive ( 34,27 %) Maximum of 3 days ahead / 3 consecutive days
- 22. Method (Anonymization) Feature extraction Document vector Classification
- 23. Feature extraction I The old method: A bag-of-words Used in spam-filters Each occurring word is a feature A text is represented by tallying each word in that particular text
- 24. Feature extraction II Using iKnow concepts (and relations)
- 25. Document vector Feature - value matrix similar to the bag-of-words model (but smaller) Value = concept frequency - inverse document frequency Conce pt 1 Concept 2 Conc ept 3 <CRC> 1 (60k- 80k) Patient #1 0 1 1 / 3 0 Patient #2 0.5 0 1 / 3 1 Patient #3 0.5 0 1 / 3 0 Deterioration: 59590 distinct features Delirium: 80220 distinct features
- 26. Classification Na誰eve Bayes Classificator (similar to spam-filtering) Support Vector Machines maximum margin separation
- 27. Results I Delirium R1: AUC: 0.801 Prec: 0.769 R2: AUC: 0.784 Prec: 0.703 Deterioration R1: AUC: 0.823 Prec: 0.770 R2: AUC: 0.809 Prec: 0.764 Pos 0.578 Neg 0.849 Pos 0.758 Neg 0.681 Pos 0.476 Neg 0.923 Pos 0.627 Neg 0.836
- 28. Results II (Dutch) Delirium 1. Erg gedesorienteerd 2. inco verschoond 3. dement 4. Heel onrustig 5. avond erg onrustig 6. onrustig dochter 7. alle tijden 8. iedere controle 9. helemaal duidelijk 10. vanavond onrustig 11. gedesorienteerd 12. vannacht onrustig 13. avond rustig aanwezig Deterioration 1. 60% Kapje 2. 100% Kapje 3. zieke indruk 4. 10 liter 5. spoed-ok 6. regelmatig uitgezogen 7. doorgebeld 8. 15 ltr 02 9. mayo tube 10. ademhalingsoefeningen 11. gespannen 12. hoge ademfrequentie 13. goed plat
- 29. Further research More data! Less features by: - Latent semantic indexing - Autoencoders Adding structured data / other data / current prediction methods
- 30. Questions ?