Healthcare
Optimized Cancer TreatmentMaturity: concept
Personalised treatment planning, scheduling and dose/therapy optimisation concepts.
concept — An idea we find credible. Nothing has been built or measured.
What this is
The problem
Radiotherapy planning balances dose to the tumour against dose to everything around it, under constraints from the delivery hardware. Scheduling across a department adds another layer: machines, staff and patient availability.
Where the current approach strains
Treatment planning is a genuine constrained optimisation problem and is already solved with real optimisers. The scheduling layer above it is often handled manually, and that is where slack accumulates.
What we are exploring
The scheduling and resource-allocation layer, which is a well-posed combinatorial problem, and where an improvement is measurable without touching clinical decision-making at all.
What would have to be true
A department willing to compare against their current schedule, measured on throughput and patient waiting time. Deliberately, this concerns logistics rather than dosimetry — the clinical layer is not ours to optimise.
No clinical claims. This concerns scheduling, not treatment decisions.
Where it applies
Related
Personalized Medicine
Multi-omics, clinical data and patient stratification for personalised decisions.
Rapid Genomic Sequencing
Sequencing itself is fast and cheap now; interpretation is not. Alignment and variant calling dominate the timeline, but deciding which of thousands of variants actually matters is a knowledge problem more than a compute one. Before optimising anything we would want an end-to-end timing breakdown on a real pipeline — speeding up a stage that is not the bottleneck is a common and expensive mistake.
Advanced Medical Imaging
Image reconstruction, denoising, classification and diagnostic assistance.