ALGORITHMIC BIAS IN ENDOMETRIAL CANCER SCREENING

A new study published in JAMA Oncology reveals that a common algorithm using transvaginal ultrasound to check for endometrial cancer is unreliable for Black women. The study, led by Dr. Kemi Doll from the University of Washington School of Medicine, analyzed ultrasound data from 1,500 Black women and found that nearly 10% of those with endometrial cancer had an endometrial thickness below the common cut-off point of 4 millimeters. This highlights the need for a tissue biopsy, rather than relying solely on ultrasound, to accurately diagnose endometrial cancer in Black women. Endometrial cancer, the most common gynecological cancer in the U.S., is on the rise, particularly among Black women who are often diagnosed at later stages.

1

Quiz Ten

1 / 5

How can healthcare providers address algorithmic bias in endometrial cancer screening?

By avoiding the use of algorithms altogether

By limiting access to screening

By incorporating diverse datasets and regular algorithm evaluations

By using biased algorithms

2 / 5

What is a potential consequence of algorithmic bias in endometrial cancer screening?

More effective treatment options

Decreased screening costs

Reduced need for further testing

Increased false negatives in certain populations

3 / 5

Which of the following can be a source of algorithmic bias in cancer screening?

Standardized patient care protocols

Regular updates to the algorithm

Accurate diagnostic algorithms

Unrepresentative training data

4 / 5

How can algorithmic bias impact endometrial cancer screening outcomes?

By ensuring uniform results across all patients

By eliminating the need for human review

By disproportionately affecting certain patient demographics

By improving overall accuracy

5 / 5

What is algorithmic bias in the context of endometrial cancer screening?

Bias in patient treatment options

Bias in patient selection

Bias introduced by the screening algorithm affecting accuracy

Bias in the doctor's diagnosis

Your score is

LinkedIn Facebook Twitter VKontakte

Read More