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Applications of artificial intelligence in dentistry: A comprehensive review
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 …
machine learning (ML) in dentistry, providing the community with a broad insight on the …
Harnessing artificial intelligence for prostate cancer management
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 …
crucial for clinical decision-making, but traditional pathology review is labor intensive and …
RetCCL: Clustering-guided contrastive learning for whole-slide image retrieval
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 …
aided diagnosis has been well developed to assist pathologists in decision-making. Content …
AI-based pathology predicts origins for cancers of unknown primary
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 …
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
The adoption of digital pathology has enabled the curation of large repositories of gigapixel
whole-slide images (WSIs). Computationally identifying WSIs with similar morphologic …
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
Computational methods have made substantial progress in improving the accuracy and
throughput of pathology workflows for diagnostic, prognostic, and genomic prediction. Still …
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
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 …
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
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 …
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 …
heterogeneity complicating prognostication and treatment decisions. The utilization and …
Artificial intelligence in ovarian cancer histopathology: a systematic review
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 …
ovarian cancer diagnosis or prognosis using histopathology data. A systematic search of …