quiz bu lëkkale ak tegtal · Diggante Niveau

IA ci Quiz bu méngoo ak test klinik

Saytu ni NLP di génne ay konsepti medsin, di jàngat kritërium test yi, ba noppi jàppale méngoo bi doktër yi xoolaat ci diggante malaad yi ak jàngat yi.

Yooni njiit yu jëm ciIA ci test klinik buy méngoo
Laaj 1 de 8

What task can clinical trial matching software support?

Xoolaatal laaj bu nekk8 laaj

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

  1. What task can clinical trial matching software support?
    • Compare documented patient information with trial eligibility criteria
    • Guarantee enrollment by a deadline
    • Replace all clinical judgment
    • Prove a treatment is effective before a trial
  2. Lan moo waral jàng done klinik nekk jafe-jafe bu metti ngir méngale losisel yi?
    • Done yi dañuy jaar yoon
    • Lu bari ci leeral yu am solo yi ñu ngi nekk ci notu bind bu amul benn jumtukaay
    • Malaad yi duñu musa séddoo seeni done
    • Hopitaal yépp dañuy jëfandikoo benn formaa
  3. Lan mooy 'kritëru dàq' biy yelloo?
    • Dafay garanti malaad bi
    • Dafay tëral ni xaalis biy duggu ci àtte bi
    • Dafay lim anam yiy tere malaad bi bokk ci àtte bi
    • Tur gëstukat bi jiite àtte bi
  4. Ban vocabulaire buñ yamale la IA mëna jëfandikoo ngir normalise konsepti test lab yi ci dokimaa yi?
    • HTML
    • JPEG
    • HTTP
    • LOINC
  5. Why might a team evaluate trial-matching results across patient subgroups?
    • To check whether candidate rankings or eligibility extraction differ across groups
    • To guarantee that every subgroup has equal trial access
    • To remove eligibility criteria from the protocol
    • To prove a trial has no recruitment bias
  6. Which is a reasonable human-review option in a trial-matching workflow?
    • Automatically enroll every high-scoring candidate
    • Allow a qualified clinician or study team to review candidate matches before action
    • Let a similarity score override protocol criteria
    • Treat a model match as confirmation of eligibility
  7. When an eligibility criterion is vague, what can embedding similarity contribute to a patient-trial match?
    • A final enrollment decision without a clinician
    • A new laboratory result not present in the chart
    • A semantic similarity signal to help rank possible matches for clinician review
    • A guarantee that the patient meets every inclusion criterion
  8. In the guide's matching pipeline, what is a rule engine used for after patient and trial information are normalized?
    • Generating diagnoses that are absent from the chart
    • Replacing clinical review for every uncertain match
    • Ranking hospitals by their billing totals
    • Checking hard eligibility constraints such as age or lab thresholds