Top Papers: KI in der Krebserkennung (2025)

Die 50 meistzitierten Arbeiten zu KI in der Krebserkennung aus dem Jahr 2025 (von 6.412 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.

2023 2024 2025 2026

#	Paper	Zitationen
1	Medical SAM adapter: Adapting segment anything model for medical image segmentation Junde Wu, Ziyue Wang, Mingxuan Hong et al. Medical Image Analysis	252
2	Spirit In the Shell: A Mathematically Plausible Pathway from Emotions to Metacognition in Artificial Intelligence Systems Yoshua Bengio Zenodo (CERN European Organization for Nuclear Research)	138
3	The Transformative Role of Artificial Intelligence in Dentistry: A Comprehensive Overview. Part 1: Fundamentals of AI, and its Contemporary Applications in Dentistry Lakshman P. Samaranayake, Nozimjon Tuygunov, Falk Schwendicke et al. International Dental Journal	125
4	Nationwide real-world implementation of AI for cancer detection in population-based mammography screening Nora Eisemann, Stefan Bunk, Trasias Mukama et al. Nature Medicine	123
5	A vision–language foundation model for precision oncology Jinxi Xiang, Xiyue Wang, Xiaoming Zhang et al. Nature	116
6	Deep Convolutional Neural Networks in Medical Image Analysis: A Review Ibomoiye Domor Mienye, Theo G. Swart, George Obaido et al. Information	112
7	Future of Artificial Intelligence—Machine Learning Trends in Pathology and Medicine Matthew G. Hanna, Liron Pantanowitz, Rajesh Dash et al. Modern Pathology	112
8	The Impact of Artificial Intelligence on Healthcare: A Comprehensive Review of Advancements in Diagnostics, Treatment, and Operational Efficiency Md. Faiyazuddin, Syed Jalal Q. Rahman, Gaurav Anand et al. Health Science Reports	110
9	Cellpose-SAM: superhuman generalization for cellular segmentation Marius Pachitariu, Michael Rariden, Carsen Stringer —	106
10	UltraLight VM-UNet: Parallel Vision Mamba significantly reduces parameters for skin lesion segmentation Renkai Wu, Yinghao Liu, Guochen Ning et al. Patterns	99
11	Current AI technologies in cancer diagnostics and treatment Ashutosh Tiwari, Soumya Nandan Mishra, Tsung‐Rong Kuo Molecular Cancer	92
12	A robust deep learning framework for multiclass skin cancer classification Burhanettin Özdemir, İshak Paçal Scientific Reports	90
13	Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study Veronica Hernström, Viktoria Josefsson, Hanna Sartor et al. The Lancet Digital Health	86
14	DeepSeek in Healthcare: Revealing Opportunities and Steering Challenges of a New Open-Source Artificial Intelligence Frontier Abdulrahman Temsah, Khalid Alhasan, Ibraheem Altamimi et al. Cureus	81
15	AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis Esther Ugo Alum Discover Oncology	74
16	Development and validation of an autonomous artificial intelligence agent for clinical decision-making in oncology Dyke Ferber, Omar S. M. El Nahhas, Georg Wölflein et al. Nature Cancer	71
17	U-Net V2: Rethinking the Skip Connections of U-Net for Medical Image Segmentation Yaopeng Peng, Danny Z. Chen, Milan Sonka —	70
18	DCSSGA-UNet: Biomedical image segmentation with DenseNet channel spatial and Semantic Guidance Attention Tahir Hussain, Hayaru Shouno, Mazin Abed Mohammed et al. Knowledge-Based Systems	67
19	EFFResNet-ViT: A Fusion-Based Convolutional and Vision Transformer Model for Explainable Medical Image Classification Tahir Hussain, Hayaru Shouno, Arshad Hussain et al. IEEE Access	62
20	Generative AI for synthetic data across multiple medical modalities: A systematic review of recent developments and challenges Mahmoud Ibrahim, Yasmina Al Khalil, Sina Amirrajab et al. Computers in Biology and Medicine	61
21	Multimodal generative AI for medical image interpretation Vishwanatha M. Rao, Michael Hla, Michael Moor et al. Nature	60
22	SAM-Med3D: Towards General-Purpose Segmentation Models for Volumetric Medical Images Haoyu Wang, Sizheng Guo, Ye Jin et al. Lecture notes in computer science	60
23	A systematic review of intermediate fusion in multimodal deep learning for biomedical applications Valerio Guarrasi, Fatih Aksu, Camillo Maria Caruso et al. Image and Vision Computing	54
24	Artificial Intelligence Scribe and Large Language Model Technology in Healthcare Documentation: Advantages, Limitations, and Recommendations Sarah A. Mess, Alison Mackey, David Yarowsky Plastic & Reconstructive Surgery Global Open	52
25	Privacy-preserving federated learning for collaborative medical data mining in multi-institutional settings Rahul Haripriya, Nilay Khare, Manish Pandey Scientific Reports	51
26	Medical Image Segmentation: A Comprehensive Review of Deep Learning-Based Methods Yuxiao Gao, Yang Jiang, Yanhong Peng et al. Tomography	51
27	Breast cancer classification based on hybrid CNN with LSTM model Mourad Kaddes, Yasser M. Ayid, Ahmed M. Elshewey et al. Scientific Reports	49
28	A novel hybrid ConvNeXt-based approach for enhanced skin lesion classification İbrahim Aruk, İshak Paçal, Ahmet Nusret Toprak Expert Systems with Applications	49
29	A dual-branch network for ultrasound image segmentation Zhiqin Zhu, Zimeng Zhang, Guanqiu Qi et al. Biomedical Signal Processing and Control	49
30	Navigating the landscape of multimodal AI in medicine: A scoping review on technical challenges and clinical applications Daan Schouten, Giulia Nicoletti, Bas Dille et al. Medical Image Analysis	49
31	Applications of Artificial Intelligence, Deep Learning, and Machine Learning to Support the Analysis of Microscopic Images of Cells and Tissues Muhammad Ali, Viviana Benfante, Ghazal Basirinia et al. Journal of Imaging	48
32	A clinical benchmark of public self-supervised pathology foundation models Gabriele Campanella, Shengjia Chen, Manbir Singh et al. Nature Communications	48
33	Hybrid deep learning model for automated colorectal cancer detection using local and global feature extraction İshak Paçal, Omneya Attallah Knowledge-Based Systems	47
34	Artificial intelligence for breast cancer screening in mammography (AI-STREAM): preliminary analysis of a prospective multicenter cohort study Yun‐Woo Chang, Jung Kyu Ryu, Jin Kyung An et al. Nature Communications	47
35	The integration of artificial intelligence into clinical medicine: Trends, challenges, and future directions Prasanna Sakthi Aravazhi, Padmini Gunasekaran, N. Benjamin et al. Disease-a-Month	47
36	Nnmamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space Model Haifan Gong, Luoyao Kang, Yitao Wang et al. —	47
37	InceptionNeXt-Transformer: A novel multi-scale deep feature learning architecture for multimodal breast cancer diagnosis İshak Paçal, Omneya Attallah Biomedical Signal Processing and Control	46
38	AI model using clinical images for genomic prediction and tailored treatment in patients with cancer Song‐Bin Guo, Xiuyu Cai, Meng Yuan et al. The Lancet Oncology	46
39	Explainable attention based breast tumor segmentation using a combination of UNet, ResNet, DenseNet, and EfficientNet models Shokofeh Anari, Soroush Sadeghi, Ghazaal Sheikhi et al. Scientific Reports	46
40	The generative era of medical AI L John Fahrner, Emma Chen, Eric J. Topol et al. Cell	46
41	Asymmetric Adaptive Heterogeneous Network for Multi-Modality Medical Image Segmentation Shenhai Zheng, Xin Ye, Chaohui Yang et al. IEEE Transactions on Medical Imaging	45
42	A multimodal vision foundation model for clinical dermatology Siyuan Yan, Zhen Yu, Clare Primiero et al. Nature Medicine	45
43	An amalgamation of deep neural networks optimized with Salp swarm algorithm for cervical cancer detection Omair Bilal, Sohaib Asif, Ming Zhao et al. Computers & Electrical Engineering	44
44	Towards generalist foundation model for radiology by leveraging web-scale 2D&3D medical data Chaoyi Wu, Xiaoman Zhang, Ya Zhang et al. Nature Communications	43
45	A visual–omics foundation model to bridge histopathology with spatial transcriptomics Weiqing Chen, Pengzhi Zhang, Tu Tran et al. Nature Methods	43
46	Artificial Intelligence in Clinical Medicine: Challenges Across Diagnostic Imaging, Clinical Decision Support, Surgery, Pathology, and Drug Discovery Eren Öğüt Clinics and Practice	42
47	Tuberculosis and pneumonia diagnosis in chest X-rays by large adaptive filter and aligning normalized network with report-guided multi-level alignment Siyuan Lu, Ziquan Zhu, Yudong Zhang et al. Engineering Applications of Artificial Intelligence	42
48	Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis Chaoyou Fu, Yuhan Dai, Yongdong Luo et al. —	41
49	Federated learning with differential privacy for breast cancer diagnosis enabling secure data sharing and model integrity Shubhi Shukla, Suraksha Rajkumar, Aditi Sinha et al. Scientific Reports	41
50	Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generation Hongxu Jiang, Muhammad Imran, Teng Zhang et al. IEEE Journal of Biomedical and Health Informatics	40

Top Papers: KI in der Krebserkennung (2025)

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