Case study 09 · Healthcare
Clinical suggestions.
Reviewed by the doctor.
A clinical decision-support module that drafts condition and prescription suggestions for the doctor to review.
- Sector
- Healthcare
- Purpose
- Clinical decision support
- Input
- Patient symptoms
- Review
- Doctor accepts or adjusts
01 / The challenge
Support the doctor’s review.
The project explored how a clinical decision-support tool could organize patient symptoms and prepare condition and medication suggestions for a doctor to consider.
02 / The approach
Prepare a draft from clinical inputs.
The module structured symptom information and used it to surface possible conditions. A recommendation component also used the individual doctor’s prescribing history to inform draft medication suggestions.
The doctor reviewed the output and could accept or adjust it. The system’s role was to prepare suggestions within that workflow.
03 / The outcome
A draft for clinical review.
The module connected symptom intake, condition suggestions, and prescribing-history inputs in one decision-support workflow. Clinical review remained central to deciding what to use.
What we built
The system, in parts.
- 01
Symptom intake
Organizes the symptoms a patient presents into structured input.
- 02
Condition suggestions
Surfaces possible conditions for the doctor to review.
- 03
Medication suggestions
Uses prescribing history to inform draft suggestions for clinical review.
Technology used
- NLP
- Recommendation engine
- Python
Selected work delivered across GOT AI, Rocket Farm Studios, and Full Cortex in engineering, technical leadership, and advisory roles. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc. Logos identify technology the project used and link to their makers; no endorsement is implied.
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