Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You and Your Team.

Learn More →

Physicians, Probabilities, and Populations—Estimating the Likelihood of Disease for Common Clinical Scenarios

Physicians, Probabilities, and Populations—Estimating the Likelihood of Disease for Common... Physicians, Probabilities, and Populations—Estimating the Likelihood of Disease Invited Commentary Invited Commentary Physicians, Probabilities, and Populations—Estimating the Likelihood of Disease for Common Clinical Scenarios Arjun K. Manrai, PhD An enviably close and influential collaboration during the 1970s without specific risk factors or symptoms for breast cancer. The between the psychologists Amos Tversky and Daniel Kahneman median (IQR) pretest probability estimate of breast cancer reshaped our beliefs about intuitive probabilistic reasoning. One was 5% (1%-10%), while the authors’ literature-based esti- of their many contributions was a demonstration of the base- mate was 0.2% to 0.3%. After a positive finding on mammog- rate fallacy, the tendency for raphy, the median (IQR) posttest probability estimate was 50% (30%-80%) among respondents, whereas the authors people to neglect prior prob- Related article abilities, or “base rates,” when computed a literature-based range of 3% to 9%. Probability calculating the chances of an event given more specific data. estimates for 2 other scenarios involving pneumonia and For example, the chances that a patient has a disease being urinary tract infection similarly differed starkly from the lit- tested reflects not only the test result and the test’s sensitivity erature-based estimates. Positive and negative likelihood ra- and specificity, http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JAMA Internal Medicine American Medical Association

Physicians, Probabilities, and Populations—Estimating the Likelihood of Disease for Common Clinical Scenarios

JAMA Internal Medicine , Volume 181 (6) – Jun 5, 2021

Loading next page...
 
/lp/american-medical-association/physicians-probabilities-and-populations-estimating-the-likelihood-of-vzXfXASYDJ
Publisher
American Medical Association
Copyright
Copyright 2021 American Medical Association. All Rights Reserved.
ISSN
2168-6106
eISSN
2168-6114
DOI
10.1001/jamainternmed.2021.0240
Publisher site
See Article on Publisher Site

Abstract

Physicians, Probabilities, and Populations—Estimating the Likelihood of Disease Invited Commentary Invited Commentary Physicians, Probabilities, and Populations—Estimating the Likelihood of Disease for Common Clinical Scenarios Arjun K. Manrai, PhD An enviably close and influential collaboration during the 1970s without specific risk factors or symptoms for breast cancer. The between the psychologists Amos Tversky and Daniel Kahneman median (IQR) pretest probability estimate of breast cancer reshaped our beliefs about intuitive probabilistic reasoning. One was 5% (1%-10%), while the authors’ literature-based esti- of their many contributions was a demonstration of the base- mate was 0.2% to 0.3%. After a positive finding on mammog- rate fallacy, the tendency for raphy, the median (IQR) posttest probability estimate was 50% (30%-80%) among respondents, whereas the authors people to neglect prior prob- Related article abilities, or “base rates,” when computed a literature-based range of 3% to 9%. Probability calculating the chances of an event given more specific data. estimates for 2 other scenarios involving pneumonia and For example, the chances that a patient has a disease being urinary tract infection similarly differed starkly from the lit- tested reflects not only the test result and the test’s sensitivity erature-based estimates. Positive and negative likelihood ra- and specificity,

Journal

JAMA Internal MedicineAmerican Medical Association

Published: Jun 5, 2021

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$499/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month