Seminars in Cancer Biology, Journal Year: 2022, Volume and Issue: 86, P. 146 - 159
Published: Aug. 11, 2022
Language: Английский
Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)
Published: Jan. 22, 2024
Language: Английский
Citations
729
Cell, Journal Year: 2023, Volume and Issue: 186(8), P. 1772 - 1791
Published: March 10, 2023
Language: Английский
Citations
263
Nature Cancer, Journal Year: 2022, Volume and Issue: 3(9), P. 1026 - 1038
Published: Sept. 22, 2022
Language: Английский
Citations
251
Bioengineering, Journal Year: 2024, Volume and Issue: 11(4), P. 337 - 337
Published: March 29, 2024
As healthcare systems around the world face challenges such as escalating costs, limited access, and growing demand for personalized care, artificial intelligence (AI) is emerging a key force transformation. This review motivated by urgent need to harness AI’s potential mitigate these issues aims critically assess integration in different domains. We explore how AI empowers clinical decision-making, optimizes hospital operation management, refines medical image analysis, revolutionizes patient care monitoring through AI-powered wearables. Through several case studies, we has transformed specific domains discuss remaining possible solutions. Additionally, will methodologies assessing solutions, ethical of deployment, importance data privacy bias mitigation responsible technology use. By presenting critical assessment transformative potential, this equips researchers with deeper understanding current future impact on healthcare. It encourages an interdisciplinary dialogue between researchers, clinicians, technologists navigate complexities implementation, fostering development AI-driven solutions that prioritize standards, equity, patient-centered approach.
Language: Английский
Citations
179
Radiology, Journal Year: 2023, Volume and Issue: 307(4)
Published: April 25, 2023
Background Prediction of microvascular invasion (MVI) may help determine treatment strategies for hepatocellular carcinoma (HCC). Purpose To develop a radiomics approach predicting MVI status based on preoperative multiphase CT images and to identify MVI-associated differentially expressed genes. Materials Methods Patients with pathologically proven HCC from May 2012 September 2020 were retrospectively included four medical centers. Radiomics features extracted tumors peritumor regions registration or subtraction images. In the training set, these used build five models via logistic regression after feature reduction. The tested using internal external test sets against pathologic reference standard calculate area under receiver operating characteristic curve (AUC). optimal AUC model clinical-radiologic characteristics combined hybrid model. log-rank was in outcome cohort (Kunming center) analyze early recurrence-free survival overall high versus low model-derived score. RNA sequencing data Cancer Image Archive gene expression analysis. Results A total 773 patients (median age, 59 years; IQR, 49–64 633 men) divided into set (n = 334), 142), 141), 121), analysis 35). AUCs models, respectively, 0.76 0.86 0.72 0.84 set. Early (P < .01) .007) can be categorized Differentially genes findings positive involved glucose metabolism. Conclusion showed best performance prediction MVI. © RSNA, 2023 Supplemental material is available this article. See also editorial by Summers issue.
Language: Английский
Citations
97
Radiology, Journal Year: 2022, Volume and Issue: 307(1)
Published: Dec. 13, 2022
Background Macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is an aggressive variant associated with angiogenesis and immunosuppressive tumor microenvironment, which expected to be noninvasively identified using radiomics approaches. Purpose To construct a CT model predict the MTM investigate underlying immune infiltration patterns. Materials Methods This study included five retrospective data sets one prospective set from three academic medical centers between January 2015 December 2021. The preoperative liver contrast-enhanced studies 365 adult patients resected HCC were evaluated. Third Xiangya Hospital Central South University provided training internal test set, while Yueyang Hunan Cancer external sets. Radiomic features extracted used develop machine learning in performance was verified two outcomes cohort, including 58 advanced undergoing transarterial chemoembolization antiangiogenic therapy, evaluate predictive value for progression-free survival (PFS). Bulk RNA sequencing tumors 41 Genome Atlas (TCGA) single-cell seven prospectively enrolled participants radiomics-related Area under receiver operating characteristics curve calculated, Cox proportional regression performed identify predictors PFS. Results Among (mean age, 55 years ± 10 [SD]; 319 men) modeling, 122 (33%) confirmed have subtype. 11 radiomic showed good predicting subtype, AUCs 0.84, 0.80, 0.74 respectively. A low score relative median cohort independently PFS (hazard ratio, 0.4; 95% CI: 0.2, 0.8; P = .01). dysregulated humoral immunity involving B-cell immunoglobulin synthesis. Conclusion Accurate prediction macrotrabecular-massive achieved model, also defective immunity. Published CC BY 4.0 license. Supplemental material available this article. See editorial by Yoon Kim issue.
Language: Английский
Citations
92
European Radiology, Journal Year: 2022, Volume and Issue: 33(3), P. 1884 - 1894
Published: Oct. 25, 2022
The main aim of the present systematic review was a comprehensive overview Radiomics Quality Score (RQS)-based reviews to highlight common issues and challenges radiomics research application evaluate relationship between RQS features.
Language: Английский
Citations
82
Theranostics, Journal Year: 2024, Volume and Issue: 14(10), P. 4127 - 4146
Published: Jan. 1, 2024
Biomarker-driven molecular imaging has emerged as an integral part of cancer precision radiotherapy. The use probes, including nanoprobes, have been explored in radiotherapy to precisely and noninvasively monitor spatiotemporal distribution biomarkers, potentially revealing tumor-killing mechanisms therapy-induced adverse effects during radiation treatment.
Language: Английский
Citations
78
Advanced Materials, Journal Year: 2022, Volume and Issue: 35(21)
Published: Nov. 29, 2022
Abstract Emerging as a potent anticancer treatment, subcellular targeted cancer therapy has drawn increasing attention, bringing great opportunities for clinical application. Here, two targeting strategies four main organelles (mitochondria, lysosome, endoplasmic reticulum, and nucleus), including molecule‐ nanomaterial (inorganic nanoparticles, micelles, organic polymers, others)‐based delivery or therapeutic strategies, are summarized. Phototherapy, chemotherapy, radiotherapy, immunotherapy, “all‐in‐one” combination among the covered in detail. Such materials constructed based on specific properties relevant mechanisms of organelles, enabling elimination tumors by inducing dysfunction corresponding destroying structures. The challenges faced organelle‐targeting therapies also Looking forward, paradigm with enhanced efficacy compared to current approaches is envisioned.
Language: Английский
Citations
75
arXiv (Cornell University), Journal Year: 2023, Volume and Issue: unknown
Published: Jan. 1, 2023
Medical image segmentation is a critical component in clinical practice, facilitating accurate diagnosis, treatment planning, and disease monitoring. However, current methods predominantly rely on customized models, which exhibit limited generality across diverse tasks. In this study, we present MedSAM, the inaugural foundation model designed for universal medical segmentation. Harnessing power of meticulously curated dataset comprising over one million images, MedSAM not only outperforms existing state-of-the-art but also exhibits comparable or even superior performance to specialist models. Moreover, enables precise extraction essential biomarkers tumor burden quantification. By delivering efficient wide spectrum tasks, holds significant potential expedite evolution diagnostic tools personalization plans.
Language: Английский
Citations
68