BME5150 Chap.7 Project Design, Critique and Reporting
Project Design, Critique and Reporting
One claim should organise the report
The project guidance asks for the importance of the prediction problem, relevant prior models, adopted methods, comprehensive evaluation, justified selection and criticism of clinical limitations. These are links in one evidence chain rather than separate sections to fill.
The question determines the useful metric; the method creates the evidence; the limitation states where that evidence stops.
Use literature to justify decisions
Compare prior work on data source, representation, algorithm, validation and outcome. A catalogue of paper summaries does not explain your design.
Select literature that helps defend a split, feature strategy, model family, evaluation rule or expected limitation, and cite it where that decision is made.
Describe modifications as tests of weaknesses
The guidance asks what was changed from provided practice code. Name the modification and the problem it targets. A site-held-out split addresses transport. Nested feature selection addresses leakage.
Class weighting addresses ignored minority errors. A change is not an improvement until held-out evidence shows what it altered.
Choose the model from the intended use
The largest isolated number is not a justification. Define performance from the clinical decision, compare candidate pipelines on the same cases, report uncertainty or fold variation and consider complexity, stability and interpretability.
State the nearest alternative and why the chosen trade-off is preferable.
Criticism should end in a test
Replace “more data are needed” with a named shift and evaluation. A scanner limitation needs a new acquisition setting. Annotation uncertainty needs additional readers or a reference process. Prevalence change needs recalculated precision and workload.
The report then proposes a feasible next study rather than a ceremonial weakness.
What this chapter covers
- 01
Prediction question and clinical importance
- 02
Comparative literature review
- 03
Method modifications and reproducibility
- 04
Comprehensive model evaluation
- 05
Best-performing model justification
- 06
Clinical limitations and future tests
Worked example · free
Select a model from a screening objective
- 3Name the metric aligned with the use case.
- 4Quantify the operating-point trade-off.
- 3State the condition that could reverse the choice.
Key terms
- Prediction Target
- A prediction target is the defined outcome and time point a model is intended to estimate.
- Model Comparison
- Model comparison evaluates candidate pipelines on the same cases with a task-aligned criterion.
- Clinical Limitation
- A clinical limitation names a mechanism that restricts use and an evaluation that could test it.
- Reproducibility
- Reproducibility is the ability to regenerate reported outputs from documented data, code and settings.
- Reference Standard
- A reference standard is the procedure used to define the outcome or annotation against which predictions are judged.
- Similarity Check
- A similarity check compares submitted text with existing material and does not replace proper authorship and citation.
Project Design, Critique and Reporting FAQ
How should I organise a short project report?
Use the evidence chain: clinical question, comparative literature, reproducible method, held-out results, model choice and testable limitation. Let tables compress repeated numbers and use prose for reasoning. Remove background that does not change a method or interpretation.
What counts as comprehensive model evaluation?
Cover the distinct properties needed by the intended use rather than listing every metric. This may include discrimination, threshold-specific errors, calibration, stability and external evidence. State how the chosen set supports the decision the model is meant to inform.
How do I criticise a model without undermining the whole project?
Name the boundary precisely and propose a feasible check. A limitation narrows the claim; it does not erase the work. Explaining a scanner shift, annotation uncertainty or prevalence change shows professional judgement and provides the next validation step.
Assessment move
Build the report outline from one sentence per scoring move: why the problem matters, what earlier work establishes, what your pipeline changes, how candidates are compared, why one is selected and what external test remains. Keep a claim sheet beside the code with the outcome, split, transformations, models, criterion, held-out result and limitation. Run the code cleanly and trace every table value to output.
Check the stated page limit and submission requirements in the current course site. During editing, cut repeated background before cutting evidence. Read the final conclusion without the results table and confirm that it still names the population, selected pipeline, metric, threshold or evaluation rule and external boundary.
Ask a classmate to point to the code output behind one table row and to the sentence that justifies the chosen model. Any broken link between those surfaces is a higher priority than stylistic polish. Recalculate one reported metric directly from saved predictions as a final numerical cross-check.
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