Projects
Deliverables and methods
This page is the contained-work lane. It links focused deliverables and methods back to the larger experiences they came from, so projects do not repeat the parent case studies with different labels.
Contained lane
Focused project work
Each card is a deliverable, method or technical workstream. The parent context is named in the card metadata.
Exploratory modelling approach
Cohort construction, ICD/HES-derived feature engineering, observability controls and LR/RF/NN model comparison under a rare-disease evidence boundary.
Health Innovation East deliverableAI Toolkit
Internal guidance-support material translating AI/MedTech governance, evidence expectations, clinical safety and data requirements into advisory questions.
Health Innovation East methodMarket intelligence and competitor analysis
Structured market, competitor and horizon-scanning work for live innovation questions, shaped around evidence quality and pathway fit.
Internship methodComputational toxicology data preparation
Dose-toxicity data mapping and structured preparation work from the ConsoneAI/DioScor research internship.
Exploratory methods
Future biological evidence methods
Exploratory methods focused on weak-signal recovery. This strand grows out of the final-year project's rare-disease limits: biologically informed, provenance-aware methods for hypothesis generation, study-design support and measurement prioritisation when the data is sparse and the next evidence decision matters.
Concept-stage methods thinking, not a validated platform or clinical tool.
- RecoverUseful signal
- PrioritiseNext measurement
- Recovering useful signal without pretending sparse data is richer than it is.
- Using biological context to prioritise what to measure next.
- Generating sharper hypotheses and follow-up study designs.
- Stress-testing assumptions with negative controls, ablations and disproof-first checks.
- Keeping observed evidence, derived features and augmented assumptions clearly separate.