NPJ Digital Medicine最新文献_第2页

Predicting response to neoadjuvant chemotherapy in muscle-invasive bladder cancer via interpretable multimodal deep learning

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2025-03-22 DOI: 10.1038/s41746-025-01560-y

Zilong Bai, Mohamed Osman, Matthew Brendel, Catherine M. Tangen, Thomas W. Flaig, Ian M. Thompson, Melissa Plets, M. Scott Lucia, Dan Theodorescu, Daniel Gustafson, Siamak Daneshmand, Joshua J. Meeks, Woonyoung Choi, Colin P. N. Dinney, Olivier Elemento, Seth P. Lerner, David J. McConkey, Bishoy M. Faltas, Fei Wang

{"title":"Predicting response to neoadjuvant chemotherapy in muscle-invasive bladder cancer via interpretable multimodal deep learning","authors":"Zilong Bai, Mohamed Osman, Matthew Brendel, Catherine M. Tangen, Thomas W. Flaig, Ian M. Thompson, Melissa Plets, M. Scott Lucia, Dan Theodorescu, Daniel Gustafson, Siamak Daneshmand, Joshua J. Meeks, Woonyoung Choi, Colin P. N. Dinney, Olivier Elemento, Seth P. Lerner, David J. McConkey, Bishoy M. Faltas, Fei Wang","doi":"10.1038/s41746-025-01560-y","DOIUrl":"https://doi.org/10.1038/s41746-025-01560-y","url":null,"abstract":"Building accurate prediction models and identifying predictive biomarkers for treatment response in Muscle-Invasive Bladder Cancer (MIBC) are essential for improving patient survival but remain challenging due to tumor heterogeneity, despite numerous related studies. To address this unmet need, we developed an interpretable Graph-based Multimodal Late Fusion (GMLF) deep learning framework. Integrating histopathology and cell type data from standard H&E images with gene expression profiles derived from RNA sequencing from the SWOG S1314-COXEN clinical trial (ClinicalTrials.gov NCT02177695 2014-06-25), GMLF uncovered new histopathological, cellular, and molecular determinants of response to neoadjuvant chemotherapy. Specifically, we identified key gene signatures that drive the predictive power of our model, including alterations in TP63, CCL5, and DCN. Our discovery can optimize treatment strategies for patients with MIBC, e.g., improving clinical outcomes, avoiding unnecessary treatment, and ultimately, bladder preservation. Additionally, our approach could be used to uncover predictors for other cancers.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"25 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Synthetic bone marrow images augment real samples in developing acute myeloid leukemia microscopy classification models

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2025-03-22 DOI: 10.1038/s41746-025-01563-9

Jan-Niklas Eckardt, Ishan Srivastava, Zizhe Wang, Susann Winter, Tim Schmittmann, Sebastian Riechert, Miriam Eva Helena Gediga, Anas Shekh Sulaiman, Martin M. K. Schneider, Freya Schulze, Christian Thiede, Katja Sockel, Frank Kroschinsky, Christoph Röllig, Martin Bornhäuser, Karsten Wendt, Jan Moritz Middeke

{"title":"Synthetic bone marrow images augment real samples in developing acute myeloid leukemia microscopy classification models","authors":"Jan-Niklas Eckardt, Ishan Srivastava, Zizhe Wang, Susann Winter, Tim Schmittmann, Sebastian Riechert, Miriam Eva Helena Gediga, Anas Shekh Sulaiman, Martin M. K. Schneider, Freya Schulze, Christian Thiede, Katja Sockel, Frank Kroschinsky, Christoph Röllig, Martin Bornhäuser, Karsten Wendt, Jan Moritz Middeke","doi":"10.1038/s41746-025-01563-9","DOIUrl":"https://doi.org/10.1038/s41746-025-01563-9","url":null,"abstract":"High-quality image data is essential for training deep learning (DL) classifiers, yet data sharing is often limited by privacy concerns. We hypothesized that generative adversarial networks (GANs) could synthesize bone marrow smear (BMS) images suitable for classifier training. BMS from 1251 patients with acute myeloid leukemia (AML), 51 patients with acute promyelocytic leukemia (APL), and 236 stem cell donors were digitized, and synthetic images were generated using StyleGAN2-Ada. In a blinded visual Turing test, eight hematologists achieved 63% accuracy in identifying synthetic images, confirming high image quality. DL classifiers trained on real data achieved AUROCs of 0.99 across AML, APL, and donor classifications, with performance remaining above 0.95 even when incrementally substituting real data for synthetic samples. Adding synthetic data to real training data offered performance gains for an exceptionally rare disease (APL). Our study demonstrates the usability of synthetic BMS data for training highly accurate image classifiers in microscopy.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"20 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Wearable AI to enhance patient safety and clinical decision-making 加强患者安全和临床决策的可穿戴人工智能

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2025-03-22 DOI: 10.1038/s41746-025-01554-w

Arjun Mahajan, Kimia Heydari, Dylan Powell

引用次数: 0

A systematic review and meta-analysis of diagnostic performance comparison between generative AI and physicians 生成式人工智能与医生诊断性能比较的系统回顾和荟萃分析

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2025-03-22 DOI: 10.1038/s41746-025-01543-z

Hirotaka Takita, Daijiro Kabata, Shannon L. Walston, Hiroyuki Tatekawa, Kenichi Saito, Yasushi Tsujimoto, Yukio Miki, Daiju Ueda

{"title":"A systematic review and meta-analysis of diagnostic performance comparison between generative AI and physicians","authors":"Hirotaka Takita, Daijiro Kabata, Shannon L. Walston, Hiroyuki Tatekawa, Kenichi Saito, Yasushi Tsujimoto, Yukio Miki, Daiju Ueda","doi":"10.1038/s41746-025-01543-z","DOIUrl":"https://doi.org/10.1038/s41746-025-01543-z","url":null,"abstract":"While generative artificial intelligence (AI) has shown potential in medical diagnostics, comprehensive evaluation of its diagnostic performance and comparison with physicians has not been extensively explored. We conducted a systematic review and meta-analysis of studies validating generative AI models for diagnostic tasks published between June 2018 and June 2024. Analysis of 83 studies revealed an overall diagnostic accuracy of 52.1%. No significant performance difference was found between AI models and physicians overall (p = 0.10) or non-expert physicians (p = 0.93). However, AI models performed significantly worse than expert physicians (p = 0.007). Several models demonstrated slightly higher performance compared to non-experts, although the differences were not significant. Generative AI demonstrates promising diagnostic capabilities with accuracy varying by model. Although it has not yet achieved expert-level reliability, these findings suggest potential for enhancing healthcare delivery and medical education when implemented with appropriate understanding of its limitations.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"86 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143675205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital pathways connecting social and biological factors to health outcomes and equity

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2025-03-20 DOI: 10.1038/s41746-025-01564-8

Yan Cui

引用次数: 0

Interpretable personalized surgical recommendation with joint consideration of multiple decisional dimensions

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2025-03-19 DOI: 10.1038/s41746-025-01509-1

Zhe Du, Zhaoyang Liu, Linru Fu, Che Wang, Zhijing Sun, Lan Zhu, Ke Deng

引用次数: 0

Credibility assessment of a mechanistic model of atherosclerosis to predict cardiovascular outcomes under lipid-lowering therapy

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2025-03-19 DOI: 10.1038/s41746-025-01557-7

Yishu Wang, Eulalie Courcelles, Emmanuel Peyronnet, Solène Porte, Alizée Diatchenko, Evgueni Jacob, Denis Angoulvant, Pierre Amarenco, Franck Boccara, Bertrand Cariou, Guillaume Mahé, Philippe Gabriel Steg, Alexandre Bastien, Lolita Portal, Jean-Pierre Boissel, Solène Granjeon-Noriot, Emmanuelle Bechet

{"title":"Credibility assessment of a mechanistic model of atherosclerosis to predict cardiovascular outcomes under lipid-lowering therapy","authors":"Yishu Wang, Eulalie Courcelles, Emmanuel Peyronnet, Solène Porte, Alizée Diatchenko, Evgueni Jacob, Denis Angoulvant, Pierre Amarenco, Franck Boccara, Bertrand Cariou, Guillaume Mahé, Philippe Gabriel Steg, Alexandre Bastien, Lolita Portal, Jean-Pierre Boissel, Solène Granjeon-Noriot, Emmanuelle Bechet","doi":"10.1038/s41746-025-01557-7","DOIUrl":"https://doi.org/10.1038/s41746-025-01557-7","url":null,"abstract":"Demonstrating cardiovascular (CV) benefits with lipid-lowering therapy (LLT) requires long-term randomized clinical trials (RCTs) with thousands of patients. Innovative approaches such as in silico trials applying a disease computational model to virtual patients receiving multiple treatments offer a complementary approach to rapidly generate comparative effectiveness data. A mechanistic computational model of atherosclerotic cardiovascular disease (ASCVD) was built from knowledge, describing lipoprotein homeostasis, LLT effects, and the progression of atherosclerotic plaques leading to myocardial infarction, ischemic stroke, major acute limb event and CV death. The ASCVD model was successfully calibrated and validated, and reproduced LLT effects observed in selected RCTs (ORION-10 and FOURIER for calibration; ORION-11, ODYSSEY-OUTCOMES and FOURIER-OLE for validation) on lipoproteins and ASCVD event incidence at both population and subgroup levels. This enables the future use of the model to conduct the SIRIUS programme, which intends to predict CV event reduction with inclisiran, an siRNA targeting hepatic PCSK9 mRNA.<figure></figure>","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"34 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143661298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cross sectional pilot study on clinical review generation using large language models

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2025-03-19 DOI: 10.1038/s41746-025-01535-z

Zining Luo, Yang Qiao, Xinyu Xu, Xiangyu Li, Mengyan Xiao, Aijia Kang, Dunrui Wang, Yueshan Pang, Xing Xie, Sijun Xie, Dachen Luo, Xuefeng Ding, Zhenglong Liu, Ying Liu, Aimin Hu, Yixing Ren, Jiebin Xie

{"title":"Cross sectional pilot study on clinical review generation using large language models","authors":"Zining Luo, Yang Qiao, Xinyu Xu, Xiangyu Li, Mengyan Xiao, Aijia Kang, Dunrui Wang, Yueshan Pang, Xing Xie, Sijun Xie, Dachen Luo, Xuefeng Ding, Zhenglong Liu, Ying Liu, Aimin Hu, Yixing Ren, Jiebin Xie","doi":"10.1038/s41746-025-01535-z","DOIUrl":"https://doi.org/10.1038/s41746-025-01535-z","url":null,"abstract":"As the volume of medical literature accelerates, necessitating efficient tools to synthesize evidence for clinical practice and research, the interest in leveraging large language models (LLMs) for generating clinical reviews has surged. However, there are significant concerns regarding the reliability associated with integrating LLMs into the clinical review process. This study presents a systematic comparison between LLM-generated and human-authored clinical reviews, revealing that while AI can quickly produce reviews, it often has fewer references, less comprehensive insights, and lower logical consistency while exhibiting lower authenticity and accuracy in their citations. Additionally, a higher proportion of its references are from lower-tier journals. Moreover, the study uncovers a concerning inefficiency in current detection systems for identifying AI-generated content, suggesting a need for more advanced checking systems and a stronger ethical framework to ensure academic transparency. Addressing these challenges is vital for the responsible integration of LLMs into clinical research.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"183 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143661258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Wearable data reveals distinct characteristics of individuals with persistent symptoms after a SARS-CoV-2 infection

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2025-03-19 DOI: 10.1038/s41746-025-01456-x

Katharina Ledebur, Marc Wiedermann, Christian Puta, Stefan Thurner, Peter Klimek, Dirk Brockmann

{"title":"Wearable data reveals distinct characteristics of individuals with persistent symptoms after a SARS-CoV-2 infection","authors":"Katharina Ledebur, Marc Wiedermann, Christian Puta, Stefan Thurner, Peter Klimek, Dirk Brockmann","doi":"10.1038/s41746-025-01456-x","DOIUrl":"https://doi.org/10.1038/s41746-025-01456-x","url":null,"abstract":"Understanding the factors associated with persistent symptoms after SARS-CoV-2 infection is critical to improving long-term health outcomes. Using a wearable-derived behavioral and physiological dataset (n = 20,815), we identified individuals characterized by self-reported persistent fatigue and shortness of breath after SARS-CoV-2 infection. Compared with symptom-free COVID-19 positive (n = 150) and negative controls (n = 150), these individuals (n = 50) had higher resting heart rates (mean difference 2.37/1.49 bpm) and lower daily step counts (mean 3030/2909 steps fewer), even at least three weeks prior to SARS-CoV-2 infection. In addition, persistent fatigue and shortness of breath were associated with a significant reduction in mean quality of life (WHO-5, EQ-5D), even before infection. Here we show that persistent symptoms after SARS-CoV-2 infection may be associated with pre-existing lower fitness levels or health conditions. These findings additionally highlight the potential of wearable devices to track health dynamics and provide valuable insights into long-term outcomes of infectious diseases.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"90 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143653387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Examining human-AI interaction in real-world healthcare beyond the laboratory

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2025-03-19 DOI: 10.1038/s41746-025-01559-5

Magdalena Katharina Wekenborg, Stephen Gilbert, Jakob Nikolas Kather

引用次数: 0