Why do errors arise in artificial intelligence diagnostic tools in histopathology and how can we minimize them?
H Evans, D Snead - Histopathology, 2024 - Wiley Online Library
Artificial intelligence (AI)‐based diagnostic tools can offer numerous benefits to the field of
histopathology, including improved diagnostic accuracy, efficiency and productivity. As a …
histopathology, including improved diagnostic accuracy, efficiency and productivity. As a …
Holding AI to account: challenges for the delivery of trustworthy AI in healthcare
The need for AI systems to provide explanations for their behaviour is now widely
recognised as key to their adoption. In this article, we examine the problem of trustworthy AI …
recognised as key to their adoption. In this article, we examine the problem of trustworthy AI …
Understanding the errors made by artificial intelligence algorithms in histopathology in terms of patient impact
H Evans, D Snead - NPJ Digital Medicine, 2024 - nature.com
An increasing number of artificial intelligence (AI) tools are moving towards the clinical realm
in histopathology and across medicine. The introduction of such tools will bring several …
in histopathology and across medicine. The introduction of such tools will bring several …
[HTML][HTML] Social network analysis of cell networks improves deep learning for prediction of molecular pathways and key mutations in colorectal cancer
N Zamanitajeddin, M Jahanifar, M Bilal… - Medical Image …, 2024 - Elsevier
Colorectal cancer (CRC) is a primary global health concern, and identifying the molecular
pathways, genetic subtypes, and mutations associated with CRC is crucial for precision …
pathways, genetic subtypes, and mutations associated with CRC is crucial for precision …
基于深度学习的医学多模态数据融合方法在肿瘤学中的进展和挑战
蔡程飞, 李军, 焦一平, 王向学, 郭冠辰, 徐军 - 数据与计算发展前沿, 2024 - jfdc.cnic.cn
[目的] 在肿瘤学中, 患者有一系列的临床数据, 从放射学, 组织学, 基因组学到电子健康记录.
不同数据模式的整合为提高诊断和预后模型的稳健性和准确性提供了机会 …
不同数据模式的整合为提高诊断和预后模型的稳健性和准确性提供了机会 …
Progress and Challenges of Medical Multimodal Data Fusion Methods Based on Deep Learning in Oncology
CAI Chengfei, LI Jun, J Yiping, W Xiangxue… - Frontiers of Data and …, 2024 - jfdc.cnic.cn
[Objective] In oncology, patients have a range of clinical data spanning radiology, histology,
genomics, and electronic health records. Integrating diverse data modalities presents an …
genomics, and electronic health records. Integrating diverse data modalities presents an …