AI tagged posts

Researchers leverage AI to Develop Early Diagnostic Test for Ovarian Cancer

Micrograph of a mucinous ovarian tumor (Photo National Institutes of Health)
Micrograph of a mucinous ovarian tumor (Photo National Institutes of Health)

For over three decades, a highly accurate early diagnostic test for ovarian cancer has eluded physicians. Now, scientists in the Georgia Tech Integrated Cancer Research Center (ICRC) have combined machine learning with information on blood metabolites to develop a new test able to detect ovarian cancer with 93 percent accuracy among samples from the team’s study group.

John McDonald, professor emeritus in the School of Biological Sciences, founding director of the ICRC, and the study’s corresponding author, explains that the new test’s accuracy is better in detecting ovarian cancer than existing tests for women clinically classified as normal, with a particular improvement in detecting early-stage ovarian d...

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When Lab-Trained AI Meets the Real World, ‘Mistakes can Happen’

AI and pathology
When humans examine tissue on slides, they can only look at a limited field within the microscope, then move to a new field and so on.

Tissue contamination distracts AI models from making accurate real-world diagnoses. Human pathologists are extensively trained to detect when tissue samples from one patient mistakenly end up on another patient’s microscope slides (a problem known as tissue contamination). But such contamination can easily confuse artificial intelligence (AI) models, which are often trained in pristine, simulated environments, reports a new Northwestern Medicine study.

“We train AIs to tell ‘A’ versus ‘B’ in a very clean, artificial environment, but, in real life, the AI will see a variety of materials that it hasn’t trained on...

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AI discovers that Not Every Fingerprint is Unique

AI discovers that not every fingerprint is unique
Saliency map highlights areas that contribute to the similarity between the two fingerprints from the same person. Credit: Gabe Guo,/Columbia Engineering

From “Law and Order” to “CSI,” not to mention real life, investigators have used fingerprints as the gold standard for linking criminals to a crime. But if a perpetrator leaves prints from different fingers in two different crime scenes, these scenes are very difficult to link, and the trace can go cold.

It’s a well-accepted fact in the forensics community that fingerprints of different fingers of the same person—”intra-person fingerprints”—are unique and, therefore, unmatchable.

A team led by Columbia Engineering undergraduate senior Gabe Guo challenged this widely held presumption...

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Personalized Cancer Medicine: Humans make Better Treatment Decisions than AI

Organoid model of a tumor. © Ana Cristina Afonseca Pestana
Organoid model of a tumor. Unchecked cell growth and targeted treatments can be simulated in these models. © Ana Cristina Afonseca Pestana

Limits of large language models in precision medicine. Treating cancer is becoming increasingly complex, but also offers more and more possibilities. After all, the better a tumor’s biology and genetic features are understood, the more treatment approaches there are. To be able to offer patients personalized therapies tailored to their disease, laborious and time-consuming analysis and interpretation of various data is required. Researchers at Charité — Universitätsmedizin Berlin and Humboldt-Universität zu Berlin have now studied whether generative artificial intelligence (AI) tools such as ChatGPT can help with this step...

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