Services offered at BOLD

I provide consulting services to startups seeking insights and guidance from a clinical technologist specializing in data/ML/AI and decision-related domains. I am as happy to talk strategy as doing data modelling. Especially if we can talk about ethics and risk upfront.

Contact me if you would like to work on applied machine learning /AI in healthcare or really anything ML. Email, Mastodon, Linkedin are all good ways to get in touch. Details below.

I am mostly located in Bengaluru, India.

Modelling

  1. Data Analysis and Statistical Modeling

    • Service Description: Analyzing complex data sets to identify patterns, trends, and relationships using statistical methods.
    • Examples: Using regression analysis to predict patient readmission rates based on historical health data. Analyzing customer behavior and sales data to forecast demand for different product lines.
    • Options: Customized statistical models tailored to specific health outcomes or business or research questions. Development of predictive models for customer lifetime value, market segmentation, and inventory management.

  2. Machine Learning Modeling

    • Service Description: Developing predictive and prescriptive models using machine learning algorithms to automate decision-making.
    • Example: Creating a machine learning model to classify different types of mammogram results as benign or malignant.
    • Options: Selection from a variety of ML algorithms (e.g., decision trees, neural networks, support vector machines) based on data characteristics and objectives.

  3. Model Improvement & Refinement

    • Service Description: Enhancing the performance of existing models through techniques like hyperparameter tuning and feature engineering.
    • Example: Improving the accuracy of a diabetes risk prediction model by optimizing its algorithms and incorporating additional patient data.
    • Options: Iterative model refinement cycles, performance benchmarking against industry standards.

Strategic AI Use

  1. Strategic Guidance on AI/ML Implementation within Healthcare Contexts
    • Service Description: Consulting on the strategic integration of AI and machine learning technologies into healthcare organizations.
    • Example: Advising on the development of an AI-driven patient triage system in a hospital setting.
    • Options: Roadmap development, resource planning, risk assessment.
  2. Feasibility Studies for AI Applications
    • Service Description: Assessing the viability and potential impact of AI applications within specific healthcare domains.
    • Example: Evaluating the feasibility of using AI for real-time monitoring and intervention in critical care units.
    • Options: Cost-benefit analysis, market analysis, technical feasibility assessment.
  3. Evaluation of Existing AI Products
    • Service Description: Assessing the effectiveness, reliability, and ethical implications of existing AI products in healthcare.
    • Example: Reviewing an AI-powered tool for automated diagnosis of skin conditions.
    • Options: Performance testing, user experience evaluation, ethical impact analysis.

Ethics & Law

  1. Designing Policies and Practical Guidelines for High-Quality ML Products and Research
    • Service Description: Developing ethical frameworks and operational guidelines to ensure the integrity and reliability of machine learning initiatives.
    • Example: Establishing data privacy policies and bias mitigation strategies for an AI-powered diagnostic tool.
    • Options: Compliance with international standards and regulations (e.g., DISHA, GDPR, HIPAA).
  2. Workshops on Figuring Out Ethical Issues and Designing an Ethical Approach
    • Service Description: Interactive sessions to help organizations identify and address ethical challenges in AI and machine learning projects.
    • Example: A workshop on ethical considerations in using genetic data for predictive health analytics.
    • Options: Tailored workshops for different stakeholder groups (e.g., developers, executives, ethicists).

Teaching

  1. Basics of ML/DL/AI for Health Professionals
    • Service Description: Introducing fundamental concepts of machine learning, deep learning, and artificial intelligence to healthcare professionals.
    • Example: An introductory course on how AI can be used in patient care and clinical decision-making.
    • Options: Online courses, in-person workshops.
  2. How to Use ML in Your Research for Health/Bio Scientists
    • Service Description: Training for health and bioscience researchers on applying machine learning techniques to their research projects.
    • Example: A workshop on using machine learning for disease pattern recognition
    • Options: Hands-on projects, case study analysis, personalized mentorship.

Get in touch