Timna: Bridging the Gap Between Ideas and Implementation in AI-Driven Medical Research

Eli Melul, Ministry of Health, Head of Innovation Department, AI and BIG DATA Technology Leader in the Technology and Data Division , Jerusalem, Israel (eli.melul@moh.gov.il )

Introduction to Timna (Big Data Research Infrastructure):

o The vision and inspiration behind the initiative.

o The mission: accelerating medical research with AI and big data.

2. From Concept to Implementation:

o The Idea: Identifying the gap between the current state and the desired state.

o Using Timna to evaluate solutions for bridging this gap.

3. Key Steps in the Research Process:

1. Navigating Bureaucracy:

▪ Approvals: Ethics committees, Helsinki, Sections 7A and 7B.

2. Research Team Organization:

▪ Assembling domain experts (SMEs), data scientists, research managers, and epidemiologists.

3. Research Protocol Development.

4. Budget Estimation and Allocation.

5. Global and Local Context:

▪ Reviewing existing research in the field.

6. Data Availability Assessment:

▪ Ensuring data is reliable, high-quality, well-labeled, and capable of addressing the research question.

7. Potential Impact Assessment:

▪ Evaluating the significance of the research for the healthcare system.

8. Feasibility Study:

▪ Can the idea be realistically implemented?


Timna: Bridging the Gap Between Ideas and Implementation in AI-Driven Medical Research Eli Melul, Ministry of Health, Head of Innovation Department, AI and BIG DATA Technology Leader in the Technology and Data Division , Jerusalem, Israel (eli.melul@moh.gov.il ) Introduction to Timna (Big Data Research Infrastructure): o The vision and inspiration behind the initiative. o The mission: accelerating medical research with AI and big data. 2. From Concept to Implementation: o The Idea: Identifying the gap between the current state and the desired state. o Using Timna to evaluate solutions for bridging this gap. 3. Key Steps in the Research Process: 1. Navigating Bureaucracy: ▪ Approvals: Ethics committees, Helsinki, Sections 7A and 7B. 2. Research Team Organization: ▪ Assembling domain experts (SMEs), data scientists, research managers, and epidemiologists. 3. Research Protocol Development. 4. Budget Estimation and Allocation. 5. Global and Local Context: ▪ Reviewing existing research in the field. 6. Data Availability Assessment: ▪ Ensuring data is reliable, high-quality, well-labeled, and capable of addressing the research question. 7. Potential Impact Assessment: ▪ Evaluating the significance of the research for the healthcare system. 8. Feasibility Study: ▪ Can the idea be realistically implemented?

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