Jiseki Health, Palo Alto, California  

November 2017 – Present

Informatics Consultant

  • Developed algorithms, workflows and care plans for chatbot-driven clinical services (Flu, UTI, Mental health, etc.), improving access to basic clinical care for over 300,000 low-income users across the US.
  • Created the Jiseki Visual Care Plan™, a new approach to physician instruction delivery that improves patient compliance and clinical outcomes. This IP is to be licensed to health systems.
  • Led nationwide Telehealth strategy and policy research to identify business opportunities and regulatory barriers
  • Facilitated physician-engineer communication and data-driven decision making through analytics and visualizations

 

Insight Data Science, San Francisco, California

September 2017 – December 2017

Health Data Science Fellow

  • Combined patient data from multiple sources (imaging, genomic, clinical) to build Breast Cancer staging model that helps health plans identify and care for high-risk cancer patients faster and easier.
  • Combined Tensorflow 3D Convolutional Neural Net (>120,000 breast MRI slices) with high-dimensional NGS data (RNASeq read counts with >23,000 genes) and clinical data to predict breast cancer stage with 78% Recall.
  • Deployed models (written in Python) on Flask web app hosted on Amazon Web Services (AWS) EC2 for user access.
  • Created SQL database using Postgres to store risk scores and query user data
  • Coached non-healthcare teammates (engineers) on clinical concepts like ICDs, HL7, SNPs, CNVs, EKG and lab results.

 

CEP/MedAmerica, Emeryville, California

May 2017– August 2017

Data Science Summer Intern

  • Discovered manual/time-consuming Readmission prediction process and pitched automated ML-driven alternative.
  • Built 30-day Readmission Risk Prediction models using Gradient Boosting Machines (AUC 0.86) and Deep Learning (AUC 0.83) using the h2o platform in R that outperformed industry standard (0.68 AUC) by 18%.
  • Leveraged in-depth understanding of clinical features to engineer >150 features in SQL (SSMS) using entire patient visit history, proprietary comorbidity flags and comorbidity scoring from over 23 million EMR and claims data.
  • Upgraded proprietary STATA scripts for deriving CMS quality metrics (QCDR) to production-level R code for Inpatient and Emergency Department practice lines using over 62 million records of CMS HCUPS and client data.

 

University of San Francisco, San Francisco, California

November 2015–April 2017

Graduate Assistant

  • Analyzed over 4TB of RNASeq data using several Bioconductor packages in R to discover groups of differentially expressed cytokines with potential for drug development in ER-positive vs ER-negative breast cancer.
  • Predicted the risk of Hepatocellular carcinoma in Python using cellular markers and alcohol consumption (91% Accuracy). Random Forest feature importance showed GGT and alcohol consumption were among top predictors.
  • Evaluated n-grams of surveys responses in Python and R using NLP and queried PostgreSQL Medicare database to gain insight into patient pain points. The top 3 areas of concern were cost, service delays and mismanagement.

 

One Medix Health, Ibadan, Nigeria

September 2012 – April 2016

Co-Founder/Informatics Director

  • Consulted with leading Health Systems and Medical schools to develop telehealth programs, learning management systems, increase provider efficiency, improve navigation, block revenue leaks and improve patient experience.
  • Designed new registration and payment systems that cut queues and patient wait-times by 68%.
  • Grew the team from 3 to 13 people and scaled customer-base nationwide increasing revenue by over 430%

 

University College Hospital, Ibadan, Nigeria

March 2012 – August 2014

House Physician

  • Rotated through Neurology, Surgical Oncology, Endocrinology, Hematology, Obstetrics, and Pediatric Oncology, getting a broader sense of the care continuum and compelling opportunities to improve quality of care through technology.
  • Initiated 6 landmark projects to increase quality of care and clinical education including the patient Navigation map, Tele-surgery for medical education, the Clinical Simulation Center, and the Medical Student Mobile Companion App.