The blind application of machine learning runs the risk of amplifying biases present in data.
Such a danger is facing us with word embedding, a popular framework to represent text data …

Large-scale reference data sets of human genetic variation are critical for the medical and
functional interpretation of DNA sequence changes. Here we describe the aggregation and …

Deep learning methods are a class of machine learning techniques capable of identifying
highly complex patterns in large datasets. Here, we provide a perspective and primer on deep …

The goal of sex and gender analysis is to promote rigorous, reproducible and responsible
science. Incorporating sex and gender analysis into experimental design has enabled …

Accurate assessment of cardiac function is crucial for the diagnosis of cardiovascular
disease 1, screening for cardiotoxicity 2 and decisions regarding the clinical management of …

Echocardiography uses ultrasound technology to capture high temporal and spatial
resolution images of the heart and surrounding structures, and is the most common imaging …

In epigenome-wide association studies, cell-type composition often differs between cases
and controls, yielding associations that simply tag cell type rather than reveal fundamental …

… Computer scientists must identify sources of bias, de-bias training data and develop
artificial-intelligence algorithms that are robust to skews in the data, argue James Zou and …

The lack of annotated publicly available medical images is a major barrier for computational
research and education innovations. At the same time, many de-identified images and much …

GPT-3.5 and GPT-4 are the two most widely used large language model (LLM) services.
However, when and how these models are updated over time is opaque. Here, we evaluate the …