Search

The ability to evaluate sperm at the microscopic level, at high-throughput, would be useful for assisted reproductive technologies (ARTs), as it can allow specific selection of sperm cells for in vitro fertilization (IVF). The tradeoff between intrinsic imaging and external contrast agents is...

If you are splitting your dataset into training and testing data you need to keep some things in mind. This discussion of 3 best practices to keep in mind when doing so includes demonstration of how to implement these particular considerations in Python.

Machine learning system from MIT CSAIL can look at chest X-rays to diagnose pneumonia — and also knows when to defer to a radiologist.

Reliable estimates of abundance are critical in effectively managing threatened species, but the feasibility of integrating data from wildlife surveys completed using advanced technologies such as remotely piloted aircraft systems (RPAS) and machine learning into abundance estimation methods...

Background

Deep learning has emerged as a versatile approach for predicting complex biological phenomena. However, its utility for biological discovery has so far been limited, given that generic deep neural networks provide little insight into the biological mechanisms that underlie a successful...

Density functional theory calculations are combined with machine learning to investigate the coverage‐dependent charge transfer at the tetracyanoethylene/Cu(111) hybrid organic/inorganic interface. The study finds two different monolayer phases, which exhibit a qualitatively different charge...

Storage tool developed at MIT CSAIL adapts to what its datasets’ users want to search.

An artificial intelligence tool lets users edit generative adversarial network models with simple copy-and-paste commands.

This study combines an artificial neural network (ANN) and a random search to develop a system to recommend process conditions for injection molding. Both simulation and experimental results are collected using a mixed sampling method that combines Taguchi and random sampling. The dataset consists...

Slow slip events result from the spontaneous weakening of the subduction megathrust and bear strong resemblance to earthquakes, only slower. This resemblance allows us to study fundamental aspects of nucleation that remain elusive for classic, fast earthquakes. We rely on machine learning algorithms...

Neuropsychiatric disorders are diagnosed based on behavioral criteria, which makes the diagnosis challenging. Objective biomarkers such as neuroimaging are needed, and when coupled with machine learning, can assist the diagnostic decision and increase its reliability. Sixty-four schizophrenia, 36...

Various data privacy threats can result from the usual process of building and constructing data and AI-based systems. Avoiding these challenges can be supported by utilizing state-of-the-art technologies in the domain of privacy-preserving AI.

Algorithms workers can’t see are increasingly pulling the management strings

Data pre-processing is not only the largest time sink for most Data Scientists, but it is also the most crucial aspect of the work. Learn more about training data and data processing tasks from 5 leading academic papers.

Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo continuous degradation. RBC storage lesions are often assessed by microscopic examination or biochemical and biophysical assays, which are complex, time-consuming, and destructive to fragile cells. Here we...

The continuously growing amount of seismic data collected worldwide is outpacing our abilities for analysis, since to date, such datasets have been analyzed in a human-expert-intensive, supervised fashion. Moreover, analyses that are conducted can be strongly biased by the standard models employed...

Liquid-phase transmission electron microscopy (TEM) has been recently applied to materials chemistry to gain fundamental understanding of various reaction and phase transition dynamics at nanometer resolution. However, quantitative extraction of physical and chemical parameters from the liquid-phase...

All is not well with artificial intelligence-based systems during the coronavirus pandemic. No, the virus does not impact AI – however, it does impact humans, without whom AI and ML systems cannot function properly. Surprised?

Researchers train a model to reach human-level performance at recognizing abstract concepts in video.

A major challenge in materials design is how to efficiently search the vast chemical design space to find the materials with desired properties. One effective strategy is to develop sampling algorithms that can exploit both explicit chemical knowledge and implicit composition rules embodied in the...