The transformer architecture extended its reach to a variety of new domains.What happened: Originally developed for natural language processing, transformers are becoming the Swiss Army Knife of deep learning.

In 2021, transformers were harnessed to discover drugs, recognize speech, and paint pictures — and much more.

Classical machine learning techniques could help children with autism receive treatment earlier in life. Researchers led by Ishanu Chattopadhyay at University of Chicago developed a system that classified autism in young children based on data collected during routine checkups.

Deep learning can predict how patients will respond to two antidepressant medicines.

Isomorphic aims to build its business on AlphaFold 2, an ensemble of neural networks that finds the shapes of protein molecules.

An epidemic of opioid abuse in the U.S. killed 93,000 people in 2020 alone. An algorithm intended to help doctors prescribe the drugs responsibly may be barring worthy patients from pain relief.

Researchers from Emory University, MIT, Purdue University, and other institutions found that deep learning systems trained to interpret x-rays and CT scans also were able to identify their subjects as Asian, Black, or White.

DeepMind opened access to AlphaFold, a model that finds the shapes of proteins, and to its output so far — a potential cornucopia for biomedical research. The research lab, a division of Google’s parent company Alphabet, made AlphaFold freely available.

A new report assessed how AI has helped address Covid-19 and where it has fallen short.

AI lately has achieved dazzling success interpreting X-rays and other medical imagery in the lab. Now it’s catching on in the clinic. Roughly one-third of U.S. radiologists use AI in some form in their work.

Transformer models trained on sequences of amino acids that form proteins have had success classifying and generating viable sequences. New research shows that they also capture information about protein structure.

The U.S. government aims to turbocharge biomedical AI research. The National Institutes of Health, which invests $41.7 billion annually in medical research, announced a program called Bridge to Artificial Intelligence (Bridge2AI) to promote machine learning in human biology and medicine.

Researchers unveiled competition for the reigning large language model GPT-3. Four models collectively called Wu Dao were described by Beijing Academy of Artificial Intelligence, a research collective funded by the Chinese government, according to Synced Review.

Some doctors don’t trust a second opinion when it comes from an AI system. A team at MIT and Regensburg University investigated how physicians responded to diagnostic advice they received from a machine learning model versus a human expert.

When you lack labeled training data, pretraining a model on unlabeled data can compensate. New research pretrained a model three times to boost performance on a medical imaging task.