US EditionPathology AI models show demographic bias in cancer diagnosis
FAIR-Path cut diagnostic disparities by about 88 percent in four AI pathology models by focusing on disease features instead of patient demographics, researchers said.
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6 Articles
Doctors Catch Cancer-Diagnosing AI Extracting Patients' Race Data and Being Racist With It
Just when you thought you heard it all, AI systems designed to spot cancer have startled researchers with a baked-in penchant for racism. The alarming findings were published in the journal Cell Reports Medicine, showing that four leading AI-enhanced pathology diagnostic systems differ in accuracy depending on patients‘ age, gender, and race — demographic data, disturbingly, that the AI is extracting directly from pathology slides, a feat that’s…
Pathology AI models show demographic bias in cancer diagnosis
Pathology has long been the cornerstone of cancer diagnosis and treatment. A pathologist carefully examines an ultrathin slice of human tissue under a microscope for clues that indicate the presence, type, and stage of cancer.
What AI Learned From Cancer Slides Shocked Researchers
AI can spot cancer—but it can also spot who you are, and that turns out to matter. A new study finds that artificial intelligence systems used to diagnose cancer from pathology slides do not perform equally for all patients, with accuracy varying across race, gender, and age groups. Researchers uncovered three main reasons behind this [...]
AI Cancer Tools Infer Race from Slides, Fueling Health Bias
Unseen Shadows: How AI’s Hidden Biases Are Skewing Cancer Diagnoses In the rapidly evolving field of medical technology, artificial intelligence has promised to revolutionize cancer detection, offering faster and more accurate diagnoses than human pathologists alone. Yet, a growing body of research is uncovering a troubling underbelly: these AI systems are not just analyzing tissue for malignancies but are inadvertently gleaning sensitive demogr…
The models of AI for the diagnosis of cancer can infer demographic information from pathology slides, resulting in biases that reduce effectiveness in the evaluation.The post A new tool reduces the bias of pathological analyses with AI was first published in La Voz de Michoacán.
One in Three AI Cancer Diagnoses Vulnerable to Demographic Bias
Artificial intelligence systems for diagnosing cancer from pathology slides often vary in accuracy according to a patient’s age, race and sex, researchers report. The findings, in Cell Reports Medicine, stress the need to check for bias in these data-driven algorithms to ensure they enhance diagnostic accuracy even when overall performance appears strong. The AI issues may have been due to underrepresented patients in training sets, differences …
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