Artificial intelligence for multimodal data integration in oncology
In oncology, the patient state is characterized by a whole spectrum of modalities, ranging
from radiology, histology, and genomics to electronic health records. Current artificial …
from radiology, histology, and genomics to electronic health records. Current artificial …
The 2022 World Health Organization classification of tumors of the urinary system and male genital organs—part B: prostate and urinary tract tumors
Abstract The 2022 World Health Organization (WHO) classification of the urinary and male
genital tumors was recently published by the International Agency for Research on Cancer …
genital tumors was recently published by the International Agency for Research on Cancer …
Demystifying supervised learning in healthcare 4.0: A new reality of transforming diagnostic medicine
The global healthcare sector continues to grow rapidly and is reflected as one of the fastest-
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …
Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction
Unreliable predictions can occur when an artificial intelligence (AI) system is presented with
data it has not been exposed to during training. We demonstrate the use of conformal …
data it has not been exposed to during training. We demonstrate the use of conformal …
Scl-wc: Cross-slide contrastive learning for weakly-supervised whole-slide image classification
Weakly-supervised whole-slide image (WSI) classification (WSWC) is a challenging task
where a large number of unlabeled patches (instances) exist within each WSI (bag) while …
where a large number of unlabeled patches (instances) exist within each WSI (bag) while …
Developing image analysis methods for digital pathology
P Bankhead - The Journal of pathology, 2022 - Wiley Online Library
The potential to use quantitative image analysis and artificial intelligence is one of the
driving forces behind digital pathology. However, despite novel image analysis methods for …
driving forces behind digital pathology. However, despite novel image analysis methods for …
A review of artificial intelligence in prostate cancer detection on imaging
I Bhattacharya, YS Khandwala… - … advances in urology, 2022 - journals.sagepub.com
A multitude of studies have explored the role of artificial intelligence (AI) in providing
diagnostic support to radiologists, pathologists, and urologists in prostate cancer detection …
diagnostic support to radiologists, pathologists, and urologists in prostate cancer detection …
Deep active learning for computer vision tasks: methodologies, applications, and challenges
M Wu, C Li, Z Yao - Applied Sciences, 2022 - mdpi.com
Active learning is a label-efficient machine learning method that actively selects the most
valuable unlabeled samples to annotate. Active learning focuses on achieving the best …
valuable unlabeled samples to annotate. Active learning focuses on achieving the best …
Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology
Artificial intelligence (AI) solutions that automatically extract information from digital histology
images have shown great promise for improving pathological diagnosis. Prior to routine use …
images have shown great promise for improving pathological diagnosis. Prior to routine use …
Multi-modality artificial intelligence in digital pathology
In common medical procedures, the time-consuming and expensive nature of obtaining test
results plagues doctors and patients. Digital pathology research allows using computational …
results plagues doctors and patients. Digital pathology research allows using computational …