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car1
cardiac
patient
My chest feels heavy and tight when I walk up the stairs.
car2
cardiac
clinical
Patient reports exertional chest pressure radiating to the left arm.
car3
cardiac
clinical
Stable angina pectoris, Canadian Cardiovascular Society class II.
car4
cardiac
patient
I get out of breath and my heart pounds for no reason at all.
car5
cardiac
patient
The home blood pressure cuff keeps giving me a high number.
dia1
diabetes
patient
My sugar goes up after every meal even though I take the pills.
dia2
diabetes
clinical
Type 2 diabetes mellitus with suboptimal glycaemic control, A1c 9.1%.
dia3
diabetes
patient
I am up all night peeing and I can never get enough water.
dia4
diabetes
clinical
Continue metformin 1000 mg twice daily with food; recheck A1c in three months.
dia5
diabetes
patient
My feet tingle and sometimes go completely numb.
med1
medication
patient
Is it safe to take ibuprofen together with my blood thinner?
med2
medication
clinical
Contraindicated: concurrent NSAID and warfarin raises gastrointestinal bleed risk.
med3
medication
patient
I lost my insurance and I cannot afford the brand-name one.
med4
medication
clinical
Prior authorization requested for a tier 3 formulary exception.
med5
medication
patient
The pharmacy says my refill is not ready and I am down to two pills.
men1
mental health
patient
I have felt low for weeks and I cannot sleep at all.
men2
mental health
clinical
Major depressive episode, moderate, with insomnia; PHQ-9 score 14.
men3
mental health
patient
I am so worried about these results that I feel sick to my stomach.
men4
mental health
clinical
Generalised anxiety disorder, referred for cognitive behavioural therapy.
men5
mental health
patient
The next appointment you have available is six whole weeks away?

Speak the Patient's Language: semantic search vs keyword search

Completed by James Seegel for MIS 752 at UNLV.

The teaching corpus and evaluation queries were provided in Dr. Richard Young's lab notebook.

My takeaways

Sentences within the same topic averaged 0.235 cosine similarity, compared with 0.129 across topics, showing some separation between subjects. Keyword search handled “my refill is not ready at the pharmacy” because “refill,” “ready,” and “pharmacy” appear in the matching sentence. For queries without shared vocabulary, keyword MRR was 0.000 versus 0.800 for semantic search. An empty search page could leave patients without useful information even when the right material exists. Overall, semantic MRR was 0.917, compared with 0.500 for keyword search. However, semantic search missed “the reading on my meter jumped since supper,” returning car5, dia5, and car2 instead of the relevant diabetes sentences. I think “meter” was ambiguous, and the model did not connect the meal reference with blood sugar. In an IT help desk, semantic search could connect “it keeps kicking me out” with “session timeout.” I would test similar phrases requiring different solutions before relying on the results.

Method and limitations

The 20 teaching sentences and 12 evaluation queries were provided in Dr. Richard Young's MIS 752 lab notebook. I used sentence-transformers/all-MiniLM-L6-v2 to create normalized embeddings, then ranked results by cosine similarity. The keyword baseline counts shared content words after removing stopwords.

Precision uses relevant results divided by the number actually returned; recall uses relevant results divided by all relevant items in the answer key. MRR uses the first relevant result within the top 3, with zero when none is found.

These results describe this small teaching corpus and its answer key. BM25 and reranking were not evaluated. The examples are course materials and do not validate a clinical search system.

The data files contain the corpus, embeddings, cosine matrix, per-query evaluation, metric summaries, and example results.

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