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Niels Bantilan - Augmenting Mental Health Care in the Digital Age: Machine Learning as a Therapist Assistant

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Augmenting Mental Health Care in the Digital Age: Machine Learning as a Therapist Assistant

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Niels Bantilan - Augmenting Mental Health Care in the Digital Age: Machine Learning as a Therapist Assistant

  1. 1. Augmenting Mental Healthcare in the Digital Age Machine Learning as a Therapist Assistant Niels Bantilan Machine Learning Engineer
  2. 2. 1 in 5 U.S. adults live with mental illness 2 in 5 of those adults received treatment* *Source: https://www.samhsa.gov/data/sites/default/files/NSDUH-FFR1-2016/NSDUH-FFR1-2016.htm
  3. 3. Access Stigma Therapist Fit BARRIERS TO CARE Cost 24
  4. 4. HOW IT WORKS
  5. 5. vs Traditional Therapy Online Therapy
  6. 6. Client-therapist Matching Detection & Monitoring of Potential Crisis Risk Mental Health Diagnosis Tools MACHINE LEARNING AS A THERAPIST ASSISTANT
  7. 7. Client-therapist Matching Detection & Monitoring of Potential Crisis Risk Mental Health Diagnosis Tools MACHINE LEARNING AS A THERAPIST ASSISTANT
  8. 8. Machine Learning @ Talkspace 9 TIPS FOR BOOTSTRAPPING ML MODELS UNDER CONDITIONS OF HEALTH DATA SENSITIVITY, LABEL SCARCITY, AND LABELER SCARCITY.
  9. 9. Talkspace TIP 1: BE HIPAA-COMPLIANT Covered Entity Business Associate Talkspac e Business Associate Agreement S3 EC2 ECR ECS RDS Sagemaker
  10. 10. Anonymized Data TIP 1: BE HIPAA-COMPLIANT Encrypt Raw Messages Decrypt, Scrub Messages Encrypted Data EC2 Instance Sagemaker JupyterHub AWS Me VPN, SSH, AWS Auth VPN User AWS Auth SSH 2-Factor Auth
  11. 11. Productization TIP 2: WORK WITH DOMAIN EXPERTS EARLY AND OFTEN Problem Framing Data Labeling Model Training / Evaluation
  12. 12. Crisis Risk Screening TIP 2: WORK WITH DOMAIN EXPERTS EARLY AND OFTEN Crisis Risk Assessment No Risk Potential Risk Factors Low Risk Moderate Risk High Risk Crisis Risk Alerting
  13. 13. TIP 3: GET TO KNOW YOUR DATA AT MULTIPLE LEVELS Reading Anonymized Excerpts QUALITATIVE number of occurrences the and happy anxious feelings sad friends Token Occurrence Counts tSNE dim-1 tSNEdim-2 QUANTITATIVE Document Clustering Class 1 Class 2
  14. 14. TIP 4: EMPLOY HUMAN-CENTERED DESIGN Room ML Model Crisis Risk Score = 96% ! Crisis Risk Alert Does the client need a risk assessment? Q1. Q2. Q3. Yes NoRisk AssessmentTreatment Plan Goals Objectives Interventions No Risk Low, Medium, High Threshold: > 95%
  15. 15. TIP 5: MAKE YOUR MODELS “INTERPRETABLE” Accuracy Interpretability Linear Regression Decision Tree K-nearest neighbors Random Forest Support Vector Machines Neural Nets
  16. 16. Time/Effort to Create Interpretable Artifacts Given today’s common tools and techniques TIP 5: MAKE YOUR MODELS “INTERPRETABLE” Accuracy Given enough raw data in modeling settings that benefit from non-linearities and/or distributed representations Linear Regression Decision Tree K-nearest neighbors Random Forest Support Vector Machines Neural Nets
  17. 17. TIP 6: START WITH SIMPLE MODELS AND FEATURES ... Weight Feature
  18. 18. ** https://github.com/TeamHG-Memex/eli5 TIP 6: START WITH SIMPLE MODELS AND FEATURES ModelingData Processing Metrics Visualization * https://github.com/marcotcr/lime * ** Explanations
  19. 19. TIP 6: START WITH SIMPLE MODELS AND FEATURES https://arxiv.org/pdf/1602.06979.pdf
  20. 20. TIP 7: FIND PROXY LABELS AND AUGMENTATION DATASETS SELECT * FROM anonymized_messages_table WHERE user_type = ‘therapist’ AND ( message LIKE ‘%1 (800) 233-4357%’ OR message LIKE ‘%1-800-233-4357%’ OR message LIKE ‘%18002334357%’ ) National Crisis Line, Anorexia and Bulimia +1 (800) 233-4357
  21. 21. TIP 7: FIND PROXY LABELS AND AUGMENTATION DATASETS
  22. 22. Crisis Risk Proxy Label Proxy Task ML Model Flat Vector Input (e.g. BoW) TIP 7: FIND PROXY LABELS AND AUGMENTATION DATASETS Crisis Risk Label Crisis Risk Task ML Model Flat Vector Input (e.g. BoW) prioritize training instances for obtaining ground truth labels Crisis Risk Label Augmented Crisis Risk Task ML Model Flat Vector Input (e.g. BoW) Add augmentation data to training set
  23. 23. Sequence Model Subreddit TIP 8: MAKE MODELS MULTI-TASK/TRANSFER LEARN Dataset Talkspace Data Reddit Data CrisisRisk Diagnosis Features Subreddit Label Multitask Learning ... Token Input Sequence Crisis Risk Label Primary Diagnosis
  24. 24. Sequence Model TIP 8: MAKE MODELS MULTI-TASK/TRANSFER LEARN Sequence Model ... Token Input Sequence Crisis Risk Label ... Token Input Sequence Transfer Learning ... Language Modeling Task Fine-tune pre-trained model on desired task
  25. 25. TIP 9: COMMUNICATE CAPABILITIES & LIMITATIONS OF ML Internal Stakeholders Users (Therapists) ! Crisis Risk Alert Your client has mentioned the following words/phrases indicating crisis risk factors: “panic attacks”, “really bad”, “ill”, “attacks”, “meds”. This is not uncommon in therapy and does not mean your client is currently experiencing a crisis. Please assess your client if your clinical judgment determines it is warranted. ... Weight FeatureROC Curve
  26. 26. Algorithms are Embedded in Human Systems As a prime concern, algorithms-in-the-loop should serve to enhance the relationships between people.
  27. 27. THANKS! (We’re hiring!) @cosmicbboy

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