The future of bioimage analysis is increasingly defined by the development and use of tools that rely on deep learning and artificial intelligence (AI). For this trend to continue in a way most useful for stimulating scientific progress, it will require our multidisciplinary community to work together, establish FAIR data sharing and deliver usable, reproducible analytical tools.Comment: 5 pages, 1 figure, opinio
The rapid development of artificial intelligence (AI) technology is leading many innovations in the ...
Improvements in technology often drive scientific discovery. Therefore, research requires sustained ...
Public data archives are the backbone of modern biological research. Biomolecular archives are well ...
In the past decade, enormous progress has been made in advancing the state-of-the-art in bioimage an...
Validation metrics are key for the reliable tracking of scientific progress and for bridging the cur...
Using multiple human annotators and ensembles of trained networks can improve the performance of dee...
The application of machine learning in sciences has seen exciting advances in recent years. As a wid...
With an increase in deep learning-based methods, the call for explainability of such methods grows, ...
Advances in microscopy have led to an unprecedented surge in image data production, resulting in dat...
Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from...
Artificial intelligence (AI)-powered algorithms are now influencing many aspects of our day-to-day l...
The increasing availability of large-scale, complex data has made research into how human genomes de...
NEUBIAS, the European Network of Bioimage Analysts, was created in 2016 with the goal of improving t...
The BIOSCAN project, led by the International Barcode of Life Consortium, seeks to study changes in ...
Life sciences are experiencing a historical shift towards a quantitative, data-rich regime. This tra...
The rapid development of artificial intelligence (AI) technology is leading many innovations in the ...
Improvements in technology often drive scientific discovery. Therefore, research requires sustained ...
Public data archives are the backbone of modern biological research. Biomolecular archives are well ...
In the past decade, enormous progress has been made in advancing the state-of-the-art in bioimage an...
Validation metrics are key for the reliable tracking of scientific progress and for bridging the cur...
Using multiple human annotators and ensembles of trained networks can improve the performance of dee...
The application of machine learning in sciences has seen exciting advances in recent years. As a wid...
With an increase in deep learning-based methods, the call for explainability of such methods grows, ...
Advances in microscopy have led to an unprecedented surge in image data production, resulting in dat...
Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from...
Artificial intelligence (AI)-powered algorithms are now influencing many aspects of our day-to-day l...
The increasing availability of large-scale, complex data has made research into how human genomes de...
NEUBIAS, the European Network of Bioimage Analysts, was created in 2016 with the goal of improving t...
The BIOSCAN project, led by the International Barcode of Life Consortium, seeks to study changes in ...
Life sciences are experiencing a historical shift towards a quantitative, data-rich regime. This tra...
The rapid development of artificial intelligence (AI) technology is leading many innovations in the ...
Improvements in technology often drive scientific discovery. Therefore, research requires sustained ...
Public data archives are the backbone of modern biological research. Biomolecular archives are well ...