A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection rates. The study, which emphasizes AI confidence, was published in Radiology, a journal of the Radiological Society of North America (RSNA).

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies.

After training a machine-learning model to analyze thousands of existing delivery particles, the researchers used it to predict new materials that would work even better.

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA).

Using generative AI algorithms, the research team designed more than 36 million possible compounds and computationally screened them for antimicrobial properties.

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School of Medicine and the Wharton School at the University of Pennsylvania can analyze kidney disease at the cellular level to match the most effective treatments and speed up solutions.

The introduction of artificial intelligence (AI) to assist colonoscopies is linked to a reduction in the ability of endoscopists (health professionals who perform colonoscopies) to detect precancerous growths (adenomas) in the colon without AI assistance, according to a paper published in The Lancet Gastroenterology & Hepatology journal.

AI is detecting tumors more often and earlier in the Dutch breast cancer screening program. Those tumors can then be treated at an earlier stage. This has been demonstrated by researchers led by Radboud university medical center in a study published in The Lancet Digital Health. The use of AI could reduce workload and save millions of euros annually.

Algorithms submitted for an AI Challenge hosted by the Radiological Society of North America (RSNA) have shown excellent performance for detecting breast cancers on mammography images, increasing screening sensitivity while maintaining low recall rates, according to a study published today in Radiology, the premier journal of the RSNA.

The RSNA Screening Mammography Breast Cancer Detection AI Challenge was a crowdsourced competition that took place in 2023, with more than 1,500 teams participating.