Applications of artificial intelligence in dentistry: A comprehensive review

F Carrillo‐Perez, OE Pecho, JC Morales… - Journal of Esthetic …, 2022‏ - Wiley Online Library
Objective To perform a comprehensive review of the use of artificial intelligence (AI) and
machine learning (ML) in dentistry, providing the community with a broad insight on the …

Harnessing artificial intelligence for prostate cancer management

L Zhu, J Pan, W Mou, L Deng, Y Zhu, Y Wang… - Cell Reports …, 2024‏ - cell.com
Prostate cancer (PCa) is a common malignancy in males. The pathology review of PCa is
crucial for clinical decision-making, but traditional pathology review is labor intensive and …

RetCCL: Clustering-guided contrastive learning for whole-slide image retrieval

X Wang, Y Du, S Yang, J Zhang, M Wang, J Zhang… - Medical image …, 2023‏ - Elsevier
Benefiting from the large-scale archiving of digitized whole-slide images (WSIs), computer-
aided diagnosis has been well developed to assist pathologists in decision-making. Content …

AI-based pathology predicts origins for cancers of unknown primary

MY Lu, TY Chen, DFK Williamson, M Zhao, M Shady… - Nature, 2021‏ - nature.com
Cancer of unknown primary (CUP) origin is an enigmatic group of diagnoses in which the
primary anatomical site of tumour origin cannot be determined,. This poses a considerable …

Fast and scalable search of whole-slide images via self-supervised deep learning

C Chen, MY Lu, DFK Williamson, TY Chen… - Nature Biomedical …, 2022‏ - nature.com
The adoption of digital pathology has enabled the curation of large repositories of gigapixel
whole-slide images (WSIs). Computationally identifying WSIs with similar morphologic …

Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes

JA Diao, JK Wang, WF Chui, V Mountain… - Nature …, 2021‏ - nature.com
Computational methods have made substantial progress in improving the accuracy and
throughput of pathology workflows for diagnostic, prognostic, and genomic prediction. Still …

[HTML][HTML] Fine-tuning and training of densenet for histopathology image representation using tcga diagnostic slides

A Riasatian, M Babaie, D Maleki, S Kalra… - Medical image …, 2021‏ - Elsevier
Feature vectors provided by pre-trained deep artificial neural networks have become a
dominant source for image representation in recent literature. Their contribution to the …

Prediction of DNA methylation-based tumor types from histopathology in central nervous system tumors with deep learning

DT Hoang, ED Shulman, R Turakulov, Z Abdullaev… - Nature Medicine, 2024‏ - nature.com
Precision in the diagnosis of diverse central nervous system (CNS) tumor types is crucial for
optimal treatment. DNA methylation profiles, which capture the methylation status of …

Biological insights and novel biomarker discovery through deep learning approaches in breast cancer histopathology

D Mandair, JS Reis-Filho, A Ashworth - NPJ breast cancer, 2023‏ - nature.com
Breast cancer remains a highly prevalent disease with considerable inter-and intra-tumoral
heterogeneity complicating prognostication and treatment decisions. The utilization and …

Artificial intelligence in ovarian cancer histopathology: a systematic review

J Breen, K Allen, K Zucker, P Adusumilli… - NPJ Precision …, 2023‏ - nature.com
This study evaluates the quality of published research using artificial intelligence (AI) for
ovarian cancer diagnosis or prognosis using histopathology data. A systematic search of …