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A new computational imaging method could change how we view hidden information in scenes.

Objects are posed in varied positions and shot at odd angles to spur new AI techniques.

To make decisions in a social context, humans have to predict the behavior of others, an ability that is thought to rely on having a model of other minds known as “theory of mind.” Such a model becomes especially complex when the number of people one simultaneously interacts with is large and...

Background

Deep learning has the potential to augment the use of chest radiography in clinical radiology, but challenges include poor generalizability, spectrum bias, and difficulty comparing across studies.
Purpose

To develop and evaluate deep learning models for chest radiograph...

Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fast and accurate predictions of atomistic chemical properties, they do not explicitly capture the electronic degrees of...

From infancy, humans have expectations about how objects will move and interact. Even young children expect objects not to move through one another, teleport, or disappear. They are surprised by mismatches between physical expectations and perceptual observations, even in unfamiliar scenes with...

Data collection is one of the first steps of the data lifecycle — you need to get all the data you require in the first place. To collect the right data, you need to know where to find it and determine the effort involved in collecting it. This article answers the most basic question: where does all...

Stimuli that sound or look like gibberish to humans are indistinguishable from naturalistic stimuli to deep networks.

As natural language processing techniques improve, suggestions are getting speedier and more relevant.

In-home digital personal assistant devices are becoming increasingly popular, but their presence raises privacy concerns.

When algorithms make decisions with real-world consequences, they need to be fair.

Here are five statistical fallacies — data traps — which data scientists should be aware of and definitely avoid.

Maintenance of working memory is thought to involve the activity of prefrontal neuronal populations with strong recurrent connections. However, it was recently shown that distractors evoke a morphing of the prefrontal population code, even when memories are maintained throughout the delay. How can a...

Background: Artificial intelligence (AI) and machine learning (ML) approaches in combination with Raman spectroscopy (RS) to obtain accurate medical diagnosis and decision-making is a way forward for understanding not only the chemical pathway to the progression of disease, but also for tailor-made...

Colorectal cancer (CRC) is a common cancer with a high mortality rate and a rising incidence rate in the developed world. Molecular profiling techniques have been used to better understand the variability between tumors and disease models such as cell lines. To maximize the translatability and...

Recent studies illustrate how machine learning (ML) can be used to bypass a core challenge of molecular modeling: the trade-off between accuracy and computational cost. Here, we assess multiple ML approaches for predicting the atomization energy of organic molecules. Our resulting models learn the...

Hyperuricemia has been found to cluster with multiple components of metabolic syndrome (MetS). It is unclear whether hyperuricemia is a downstream result of MetS or may play an upstream role in MetS development. Using the Mendelian randomization (MR) method, we examined the causal relationship…

Not only can MLonCode help companies streamline their codebase and software delivery processes, but it also helps organizations better understand and manage their engineering talents.

Study: After eBay improved its translation software, international commerce increased sharply

We introduce machine learning (ML) to perform classification and quantitation of images of nuclei from human blood neutrophils. Here we assessed the use of convolutional neural networks (CNNs) using free, open source software to accurately quantitate neutrophil NETosis, a recently discovered process...