开放期刊系统

人工智能在骨肉瘤病理诊断中的研究进展

孙 涛, 唐雪 峰*

摘要

近年来,人工智能在骨肉瘤病理诊断中取得了一定的进展。传统方法受限于人力、时间和主观性,而AI技术如深度学习通过优化算法和图像分析,提高了诊断精度。特别是深度学习在肿瘤识别、预后预测等方面潜力巨大。然而,数据收集、标注和质量控制仍是挑战,算法的泛化能力、鲁棒性还有待提高。AI辅助诊断虽未完全取代传统方法,但已成为提升病理诊断精度的重要工具。随着技术的不断进步,AI将更广泛地应用于骨肉瘤的病理诊断,有望提高骨肉瘤的诊断效率,降低误诊,提高骨肉瘤病人的预后。

关键词

人工智能;骨肉瘤;病理诊断;深度学习

全文:

PDF

参考

[1]Neofytos D ,Ognjen A ,D P C .Deep Learning for Whole Slide Image Analysis: An Overview.[J].Frontiers in medicine,2019,6264.

[2]陶宇章.基于人工智能的骨肿瘤组织病理学辅助诊断研究[D].重庆医科大学,2022.DOI:10.27674/d.cnki.gcyku.2022.000160.

[3]Wang S ,Yang M D ,Rong R , et al.Artificial Intelligence in Lung Cancer Pathology Image Analysis[J].Cancers,2019,11(11):1673.

[4]A F S ,S L O ,Caroline P , et al.A Dataset for Breast Cancer Histopathological Image Classification.[J].IEEE transactions on bio-medical engineering,2016,63(7):1455-62.

[5]Liu Yun,Kohlberger Timo,Norouzi Mohammad et al. Artificial Intelligence-Based Breast Cancer Nodal Metastasis Detection: Insights Into the Black Box for Pathologists.[J] .Arch Pathol Lab Med, 2019, 143: 859-868.

[6]Ronnachai J ,Ellery W ,Narayan H , et al.Deep learning models for histologic grading of breast cancer and association with disease prognosis[J].npj Breast Cancer,2022,8(1):113-113.

[7]HAN W, JOHNSON C, GAED M, et al. Histologic tissue components provide major cues for machine learning -based prostate cancer detection and grading on prostatectomy specimens[J]. Sci Rep, 2020, 10(1): 9911.

[8]范麟龙,宋子健,邓龙昕,等.人工智能在前列腺癌病理诊断及分子分型中的研究进展[J/OL].海军军医大学学报,1-6[2024-03-31]

[9]Hiroshi Y ,Taichi S ,Tomoharu K , et al.Automated histological classification of whole-slide images of gastric biopsy specimens.[J].Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association,2018,21(2):249-257.

[10]杨冰泽,吕艳婷,何立群,等.宫颈癌智能筛查系统在宫颈病变诊断中的价值[J].浙江医学,2023,45(24):2636-2641.

[11]王凯怡,赵亚丹,谢慧君,等.人工智能辅助系统在宫颈薄层液基细胞学研究中的应用[J].浙江医学,2024,46(02):177-181.

[12]Babu H A ,Rashika M ,Ovidiu D , et al.Viable and necrotic tumor assessment from whole slide images of osteosarcoma using machine-learning and deep-learning models.[J].PloS one,2019,14(4):e0210706.

[13]Rashika M ,Ovidiu D ,Patrick L , et al.Convolutional Neural Network for Histopathological Analysis of Osteosarcoma.[J].Journal of computational biology : a journal of computational molecular cell biology,2018,25(3):313-325.

[14]Fangfang G ,Jun L ,Jun Z , et al.A Multimodal Auxiliary Classification System for Osteosarcoma Histopathological Images Based on Deep Active Learning[J].Healthcare,2022,10(11):2189-2189.

[15]D.M. A ,Hosein B ,Ling T , et al.A deep learning study on osteosarcoma detection from histological images[J].Biomedical Signal Processing and Control,2021,69

[16]Bahjat F ,ALMalaise S A A ,Mahmoud R .Optimal Deep Stacked Sparse Autoencoder Based Osteosarcoma Detection and Classification Model[J].Healthcare,2022,10(6):1040-1040.

[17]Thavavel V ,Akshya J ,Kanagaraj N , et al.Design of a Honey Badger Optimization Algorithm with a Deep Transfer Learning-Based Osteosarcoma Classification Model[J].Cancers,2022,14(24):6066-6066.

[18]A I V ,I G L ,K G M .Deep Learning Approaches to Osteosarcoma Diagnosis and Classification: A Comparative Methodological Approach.[J].Cancers,2023,15(8):

[19]于观贞,魏培莲,陈颖,等.人工智能在肿瘤病理诊断和评估中的应用与思考[J].第二军医大学学报,2017,38(11):1349-1354.

[20]李静尧,邱阳,王海东.人工智能技术在肺癌临床诊疗中的应用与展望[J/OL].重庆医学,1-8[2024-03-31].http://kns.cnki.net/kcms/detail/50.1097.r.20240307.1356.002.html.

[21]Jiang Jie,Qu Haishun,Zhan Xinli et al. Identification of osteosarcoma m6A-related prognostic biomarkers using artificial intelligence: RBM15.[J] .Sci Rep, 2023, 13: 5255.

[22]Qu H ,Jiang J ,Zhan X , et al.Integrating artificial intelligence in osteosarcoma prognosis: the prognostic significance of SERPINE2 and CPT1B biomarkers.[J].Scientific reports,2024,14(1):4318-4318.

[23]BingLi B ,ZongYi W ,SheJi W , et al.Application of interpretable machine learning algorithms to predict distant metastasis in osteosarcoma.[J].Cancer medicine,2022,12(4):5025-5034.

[24]Yang F ,Yan D ,Wang Z .Large-Scale assessment of ChatGPT's performance in benign and malignant bone tumors imaging report diagnosis and its potential for clinical applications[J].Journal of Bone Oncology,2024,44100525.


(2 摘要 Views, 5 PDF Downloads)

Refbacks

  • 当前没有refback。