Top Papers: KI in der Krebserkennung (2023)

Die 50 meistzitierten Arbeiten zu KI in der Krebserkennung aus dem Jahr 2023 (von 11.488 insgesamt).

Krebs frühzeitig zu erkennen kann Leben retten – und genau hier setzt KI an. Deep-Learning-Modelle erreichen inzwischen bei bestimmten Tumorarten eine Erkennungsgenauigkeit, die mit der erfahrener Pathologen vergleichbar ist. Die Forschung umfasst Hautkrebs-Screening, Brustkrebs-Mammographie, Lungennoduli-Erkennung und vieles mehr. Hier finden Sie die einflussreichsten und neuesten Studien zu diesem Thema.

2021 2022 2023 2024

#	Paper	Zitationen
1	Transformers in medical imaging: A survey Fahad Shamshad, Salman Khan, Syed Waqas Zamir et al. Medical Image Analysis	1.054
2	MedMNIST v2 - A large-scale lightweight benchmark for 2D and 3D biomedical image classification Jiancheng Yang, Rui Shi, Donglai Wei et al. Scientific Data	764
3	Segment anything model for medical image analysis: An experimental study Maciej A. Mazurowski, Haoyu Dong, Hanxue Gu et al. Medical Image Analysis	652
4	Diffusion models in medical imaging: A comprehensive survey Amirhossein Kazerouni, Ehsan Khodapanah Aghdam, Moein Heidari et al. Medical Image Analysis	595
5	A visual–language foundation model for pathology image analysis using medical Twitter Zhi Huang, Federico Bianchi, Mert Yüksekgönül et al. Nature Medicine	538
6	From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment Kyle Swanson, Eric Q. Wu, Angela Zhang et al. Cell	519
7	MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques Soheila Saeedi, Sorayya Rezayi, Hamidreza Keshavarz et al. BMC Medical Informatics and Decision Making	512
8	A Study of CNN and Transfer Learning in Medical Imaging: Advantages, Challenges, Future Scope Ahmad Waleed Salehi, Shakir Khan, Gaurav Gupta et al. Sustainability	492
9	Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI): a clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study Kristina Lång, Viktoria Josefsson, Anna-Maria Larsson et al. The Lancet Oncology	465
10	Sentinel Lymph Node Biopsy vs No Axillary Surgery in Patients With Small Breast Cancer and Negative Results on Ultrasonography of Axillary Lymph Nodes Oreste Gentilini, Edoardo Botteri, Claudia Sangalli et al. JAMA Oncology	446
11	ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge Yunxiang Li, Zihan Li, Kai Zhang et al. Cureus	430
12	Segment anything model for medical images? Yuhao Huang, Xin Yang, Lian Liu et al. Medical Image Analysis	416
13	Medical image analysis using deep learning algorithms Mengfang Li, Yuanyuan Jiang, Yanzhou Zhang et al. Frontiers in Public Health	400
14	The Current and Future State of AI Interpretation of Medical Images Pranav Rajpurkar, Matthew P. Lungren New England Journal of Medicine	391
15	DCSAU-Net: A deeper and more compact split-attention U-Net for medical image segmentation Qing Xu, Zhicheng Ma, Na He et al. Computers in Biology and Medicine	385
16	Self-supervised learning for medical image classification: a systematic review and implementation guidelines Shih-Cheng Huang, Anuj Pareek, Malte Jensen et al. npj Digital Medicine	380
17	Medical image data augmentation: techniques, comparisons and interpretations Evgin Göçeri Artificial Intelligence Review	377
18	Advances in medical image analysis with vision Transformers: A comprehensive review Reza Azad, Amirhossein Kazerouni, Moein Heidari et al. Medical Image Analysis	373
19	Evaluation of artificial intelligence techniques in disease diagnosis and prediction Nafiseh Ghaffar Nia, Erkan Kaplanoğlu, Ahad Nasab Discover Artificial Intelligence	360
20	ResNet and its application to medical image processing: Research progress and challenges Wanni Xu, You-Lei Fu, Dongmei Zhu Computer Methods and Programs in Biomedicine	327
21	Multimodal data fusion for cancer biomarker discovery with deep learning Sandra Steyaert, Marija Pizurica, Divya Nagaraj et al. Nature Machine Intelligence	325
22	Medical Image Segmentation via Cascaded Attention Decoding Md. Mostafijur Rahman, Radu Mărculescu 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)	317
23	HiFuse: Hierarchical multi-scale feature fusion network for medical image classification Xiangzuo Huo, Gang Sun, Shengwei Tian et al. Biomedical Signal Processing and Control	303
24	Artificial intelligence for breast cancer detection in screening mammography in Sweden: a prospective, population-based, paired-reader, non-inferiority study Karin Dembrower, Alessio Crippa, Eugenia Colón et al. The Lancet Digital Health	299
25	A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories Davide Placido, Bo Yuan, Jessica Xin Hjaltelin et al. Nature Medicine	297
26	Deep learning-enabled virtual histological staining of biological samples Bijie Bai, Xilin Yang, Yuzhu Li et al. Light Science & Applications	296
27	Machine Learning and AI in Cancer Prognosis, Prediction, and Treatment Selection: A Critical Approach Bo Zhang, Huiping Shi, Hongtao Wang Journal of Multidisciplinary Healthcare	285
28	Cross-level Feature Aggregation Network for Polyp Segmentation Tao Zhou, Yi Zhou, Kelei He et al. Pattern Recognition	283
29	Large-scale pancreatic cancer detection via non-contrast CT and deep learning Kai Cao, Yingda Xia, Jiawen Yao et al. Nature Medicine	282
30	Deep Learning for Medical Image-Based Cancer Diagnosis Xiaoyan Jiang, Zuojin Hu, Shuihua Wang‎ et al. Cancers	279
31	Learning with limited annotations: A survey on deep semi-supervised learning for medical image segmentation Rushi Jiao, Yichi Zhang, Le Ding et al. Computers in Biology and Medicine	278
32	Denoising diffusion probabilistic models for 3D medical image generation Firas Khader, Gustav Müller‐Franzes, Soroosh Tayebi Arasteh et al. Scientific Reports	276
33	Artificial intelligence in lung cancer diagnosis and prognosis: Current application and future perspective Shigao Huang, Jie Yang, Na Shen et al. Seminars in Cancer Biology	262
34	Artificial intelligence for digital and computational pathology Andrew H. Song, Guillaume Jaume, Drew F. K. Williamson et al. Nature Reviews Bioengineering	262
35	Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review Arsela Prelaj, V. Miskovic, Michele Zanitti et al. Annals of Oncology	261
36	MedNeXt: Transformer-Driven Scaling of ConvNets for Medical Image Segmentation Saikat Roy, Gregor Koehler, Constantin Ulrich et al. Lecture notes in computer science	259
37	Artificial intelligence in clinical medicine: catalyzing a sustainable global healthcare paradigm Gokul Krishnan, Shiana Singh, Monika Pathania et al. Frontiers in Artificial Intelligence	255
38	EGE-UNet: An Efficient Group Enhanced UNet for Skin Lesion Segmentation Jiacheng Ruan, Mingye Xie, Jingsheng Gao et al. Lecture notes in computer science	253
39	Artificial intelligence in diagnostic pathology Saba Shafi, Anil V. Parwani Diagnostic Pathology	250
40	Deep Learning Attention Mechanism in Medical Image Analysis: Basics and Beyonds Xiang Li, Minglei Li, Pengfei Yan et al. International Journal of Network Dynamics and Intelligence	246
41	Automation Bias in Mammography: The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance Thomas Dratsch, Xue Chen, Mohammad Hosein Rezazade Mehrizi et al. Radiology	242
42	Multistain deep learning for prediction of prognosis and therapy response in colorectal cancer Sebastian Foersch, Christina Glasner, Ann-Christin Woerl et al. Nature Medicine	241
43	A comprehensive review of deep neural networks for medical image processing: Recent developments and future opportunities Pawan Kumar Mall, Pradeep Kumar Singh, Swapnita Srivastav et al. Healthcare Analytics	240
44	Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study Sophia J. Wagner, Daniel Reisenbüchler, Nicholas P. West et al. Cancer Cell	229
45	A review of deep learning-based multiple-lesion recognition from medical images: classification, detection and segmentation Huiyan Jiang, Zhaoshuo Diao, Tianyu Shi et al. Computers in Biology and Medicine	229
46	Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review Aghiles Kebaili, Jérôme Lapuyade‐Lahorgue, Su Ruan Journal of Imaging	227
47	On the challenges and perspectives of foundation models for medical image analysis Shaoting Zhang, Dimitris Metaxas Medical Image Analysis	224
48	Artificial intelligence in dentistry—A review Hao Ding, Jiamin Wu, Wuyuan Zhao et al. Frontiers in Dental Medicine	224
49	Artificial intelligence assists precision medicine in cancer treatment Jinzhuang Liao, Xiaoying Li, Yu Gan et al. Frontiers in Oncology	222
50	Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging Shekoofeh Azizi, Laura Culp, Jan Freyberg et al. Nature Biomedical Engineering	219

Top Papers: KI in der Krebserkennung (2023)

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