ReviewCancers2022
Current Trend of Artificial Intelligence Patents in Digital Pathology: A Systematic Evaluation of the Patent Landscape.
Review in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Artificial Intelligence for Diagnostic and Prognostic Support in Breast Cancer: A Literature Overview.Cancers · 2026Review
- Application and exploration of digital pathology technology in standardized residency training.BMC medical education · 2026Article
- Two-Step Ensemble Convolutional Neural Networks for Colonoscopic Biopsy Classification Resembling Pathologists' Process.Journal of Korean medical science · 2026Article
- Superior transplant recipient outcome prediction and pathology assessment using rapid deep learning applied to procurement kidney biopsies.Scientific reports · 2025Article
- Development trend of Artificial Intelligence (AI) in dentistry: exploring FDA-cleared dental devices.BMC oral health · 2025Article
- Horizon Scanning Methods for Health Care Technology Innovation Identification: Rapid Scoping Review of Patent Research Studies.Interactive journal of medical research · 2025Review
- Utility of artificial intelligence in a binary classification of soft tissue tumors.Journal of pathology informatics · 2024Article
- Artificial intelligence in digital pathology: a systematic review and meta-analysis of diagnostic test accuracy.NPJ digital medicine · 2024Review
- Digital pathology and multimodal learning on oncology data.BJR artificial intelligence · 2024Review
- Advances in NIR-Responsive Natural Macromolecular Hydrogel Assembly Drugs for Cancer Treatment.Pharmaceutics · 2023Review
- Building Automation Pipeline for Diagnostic Classification of Sporadic Odontogenic Keratocysts and Non-Keratocysts Using Whole-Slide Images.Diagnostics (Basel, Switzerland) · 2023Article
- Deep Learning-Based Computational Cytopathologic Diagnosis of Metastatic Breast Carcinoma in Pleural Fluid.Cells · 2023Article
- Biomimicry Industry and Patent Trends.Biomimetics (Basel, Switzerland) · 2023Article
- Article
- Development of quality assurance program for digital pathology by the Korean Society of Pathologists.Journal of pathology and translational medicine · 2022Article
- Recent Application of Artificial Intelligence in Non-Gynecological Cancer Cytopathology: A Systematic Review.Cancers · 2022Review
- Review
- Identification of technology frontiers of artificial intelligence-assisted pathology based on patent citation network.PloS one · 2022Review
- Deep learning methods for improving the accuracy and efficiency of pathological image analysis.Science progressArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The integration of digital pathology (DP) with artificial intelligence (AI) enables faster, more accurate, and thorough diagnoses, leading to more precise personalized treatment. As technology is advancing rapidly, it is critical to understand the current state of AI applications in DP. Therefore, a patent analysis of AI in DP is required to assess the application and publication trends, major assignees, and leaders in the field. We searched five major patent databases, namely, those of the USPTO, EPO, KIPO, JPO, and CNIPA, from 1974 to 2021, using keywords such as DP, AI, machine learning, and deep learning. We discovered 6284 patents, 523 of which were used for trend analyses on time series, international distribution, top assignees; word cloud analysis; and subject category analyses. Patent filing and publication have increased exponentially over the past five years. The United States has published the most patents, followed by China and South Korea (248, 117, and 48, respectively). The top assignees were Paige.AI, Inc. (New York City, NY, USA) and Siemens, Inc. (Munich, Germany) The primary areas were whole-slide imaging, segmentation, classification, and detection. Based on these findings, we expect a surge in DP and AI patent applications focusing on the digitalization of pathological images and AI technologies that support the vital role of pathologists.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.