Artificial intelligence for digital and computational pathology
Advances in digitizing tissue slides and the fast-paced progress in artificial intelligence,
including deep learning, have boosted the field of computational pathology. This field holds …
including deep learning, have boosted the field of computational pathology. This field holds …
Explainable agents and robots: Results from a systematic literature review
Humans are increasingly relying on complex systems that heavily adopts Artificial
Intelligence (AI) techniques. Such systems are employed in a growing number of domains …
Intelligence (AI) techniques. Such systems are employed in a growing number of domains …
[HTML][HTML] Digital transformation in smart farm and forest operations needs human-centered AI: challenges and future directions
The main impetus for the global efforts toward the current digital transformation in almost all
areas of our daily lives is due to the great successes of artificial intelligence (AI), and in …
areas of our daily lives is due to the great successes of artificial intelligence (AI), and in …
Lizard: a large-scale dataset for colonic nuclear instance segmentation and classification
The development of deep segmentation models for computational pathology (CPath) can
help foster the investigation of interpretable morphological biomarkers. Yet, there is a major …
help foster the investigation of interpretable morphological biomarkers. Yet, there is a major …
What do we need to build explainable AI systems for the medical domain?
Artificial intelligence (AI) generally and machine learning (ML) specifically demonstrate
impressive practical success in many different application domains, eg in autonomous …
impressive practical success in many different application domains, eg in autonomous …
Breast cancer histopathological image classification using a hybrid deep neural network
Even with the rapid advances in medical sciences, histopathological diagnosis is still
considered the gold standard in diagnosing cancer. However, the complexity of …
considered the gold standard in diagnosing cancer. However, the complexity of …
[HTML][HTML] Artificial intelligence and digital pathology: challenges and opportunities
In light of the recent success of artificial intelligence (AI) in computer vision applications,
many researchers and physicians expect that AI would be able to assist in many tasks in …
many researchers and physicians expect that AI would be able to assist in many tasks in …
Harnessing biomedical literature to calibrate clinicians' trust in AI decision support systems
Clinical decision support tools (DSTs), powered by Artificial Intelligence (AI), promise to
improve clinicians' diagnostic and treatment decision-making. However, no AI model is …
improve clinicians' diagnostic and treatment decision-making. However, no AI model is …
Explainable AI: the new 42?
Explainable AI is not a new field. Since at least the early exploitation of CS Pierce's
abductive reasoning in expert systems of the 1980s, there were reasoning architectures to …
abductive reasoning in expert systems of the 1980s, there were reasoning architectures to …
[HTML][HTML] Explainable artificial intelligence for human decision support system in the medical domain
In this paper, we present the potential of Explainable Artificial Intelligence methods for
decision support in medical image analysis scenarios. Using three types of explainable …
decision support in medical image analysis scenarios. Using three types of explainable …