NPJ Digital Medicine最新文献_第3页

From compliance to competence: a multi-level model for AI governance in undergraduate medical education. 从服从到胜任：本科医学教育人工智能治理的多层次模型

IF 18 1区医学

NPJ Digital Medicine Pub Date : 2026-10-14 DOI: 10.1038/s41746-026-03390-y

Juan José Gualda-Gea, Lourdes Estefanía Barón-Miras, Maria Jesús Bertran, Alberto L Garcia-Basteiro, Guillermo Mena, Marta Aldea, Gemina Santana, Jaume Grau, Andrés Prat Marin, Isabel Torá-Rocamora, Antoni Trilla

引用次数: 0

From research to clinical practice: Expert consensus on Neuroimaging AI tools for the Memory clinic (Neuro-AIM) 从研究到临床实践：记忆临床神经成像人工智能工具（neuroaim）专家共识

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2026-10-14 DOI: 10.1038/s41746-026-03296-9

Natasha Clarke,Mathias Huybrechts,Jay Amin,Lewis Hotchkiss,James Leighs,Matthew Leming,Usman Saeed,Catherine J. Scott,Dirk Smeets,Angela Tam,Stefano Tamburin,Geert Vanhooren,Meike W. Vernooij,Jennifer Camaradou,David J. Llewellyn,Timothy Rittman,Rose Bruffaerts

{"title":"From research to clinical practice: Expert consensus on Neuroimaging AI tools for the Memory clinic (Neuro-AIM)","authors":"Natasha Clarke,Mathias Huybrechts,Jay Amin,Lewis Hotchkiss,James Leighs,Matthew Leming,Usman Saeed,Catherine J. Scott,Dirk Smeets,Angela Tam,Stefano Tamburin,Geert Vanhooren,Meike W. Vernooij,Jennifer Camaradou,David J. Llewellyn,Timothy Rittman,Rose Bruffaerts","doi":"10.1038/s41746-026-03296-9","DOIUrl":"https://doi.org/10.1038/s41746-026-03296-9","url":null,"abstract":"Abstract Although AI tools for neuroimaging show considerable promise in the diagnosis, prognosis, and management of neurodegenerative disorders, their uptake in memory clinics has been limited. A key barrier is lack of consensus on their effective design and implementation. Here we establish expert consensus on the specific goals, usage and challenges of AI tools for neuroimaging in the memory clinic using a Delphi process. Sixteen experts from clinical, academic, and industry backgrounds participated in three rounds of questionnaires, coordinated by the Imaging Working Group of the Deep Dementia Phenotyping (DEMON) network, with support from a patient and public involvement representative. Consensus was reached on eight statements covering four themes: purpose, quality, interactions with clinicians and memory clinics, and privacy and ethics. Implementation of these recommendations will further the adoption of AI neuroimaging tools from research to clinical practice, improving diagnostic and care pathways for patient benefit.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"8 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149208659","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

FedFound: Federated Foundation Model for GI endoscopy imaging FedFound：用于胃肠道内镜成像的联邦基金会模型

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2026-10-14 DOI: 10.1038/s41746-026-03281-2

Alina Devkota,Annahita Amireskandari,Joel Palko,Soban Maan,Shyam Thakkar,Tapan Khan,Xiajun Jiang,Donald Adjeroh,Binod Bhattarai,Prashnna Gyawali

引用次数: 0

Author Correction: Large language models are powerful electronic health record encoders. 作者更正：大型语言模型是功能强大的电子健康记录编码器。

IF 18 1区医学

NPJ Digital Medicine Pub Date : 2026-10-14 DOI: 10.1038/s41746-026-03220-1

Stefan Hegselmann, Georg von Arnim, Tillmann Rheude, Noel Kronenberg, David Sontag, Gerhard Hindricks, Roland Eils, Benjamin Wild

引用次数: 0

Electronic health record developer adherence to federal AI risk transparency requirements 电子健康记录开发人员遵守联邦人工智能风险透明度要求

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2026-10-14 DOI: 10.1038/s41746-026-03152-w

Nidhi Manikkoth,Ngan Vo,Jessica Handley,Josh Biro,Jordan Everson,Raj Ratwani,Kristen Miller

引用次数: 0

Model-dependent prompt effects challenge reliable deployment of medical LLMs in traditional Chinese medicine 模型依赖的提示效应对中医医学llm的可靠部署提出了挑战

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2026-10-13 DOI: 10.1038/s41746-026-03397-5

Liang-Wei Tseng,Yi-Chin Lu,Liang-Chi Tseng,Yu-Chun Chen,Hsing-Yu Chen

引用次数: 0

Exploring PET and MRI brain networks across healthy controls, mild cognitive impairment, and Alzheimer’s disease 在健康对照、轻度认知障碍和阿尔茨海默病中探索PET和MRI脑网络

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2026-10-13 DOI: 10.1038/s41746-026-03354-2

Bingjie Wang,Sheng Bi,Xuetong Tao,Feng Wang,Haiyan Wang,Runxiang Huang,Xiaoyin Xu,Hairong Zheng,Dong Liang,Greta S. P. Mok,Shaozhen Yan,Zhanli Hu

引用次数: 0

Realizing the value of the divergence event in clinical human-AI interaction. 实现分歧事件在临床人机交互中的价值。

IF 18 1区医学

NPJ Digital Medicine Pub Date : 2026-10-13 DOI: 10.1038/s41746-026-03394-8

Florence X Doo, Gabriel A Brat, Sarah C Rossetti, Robert Klitzman, Charles E Binkley

引用次数: 0

Multidimensional continuous glucose monitoring metrics enable digital risk stratification across the diabetes spectrum 多维连续血糖监测指标可实现糖尿病谱系的数字化风险分层

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2026-10-13 DOI: 10.1038/s41746-026-03368-w

Jiali Lu,Yudan Ding,Bin Zhao,Fang Fang,Ben Lu,Jiaqi Huang

{"title":"Multidimensional continuous glucose monitoring metrics enable digital risk stratification across the diabetes spectrum","authors":"Jiali Lu,Yudan Ding,Bin Zhao,Fang Fang,Ben Lu,Jiaqi Huang","doi":"10.1038/s41746-026-03368-w","DOIUrl":"https://doi.org/10.1038/s41746-026-03368-w","url":null,"abstract":"Abstract Although continuous glucose monitoring (CGM) provides high-dimensional data, the usefulness of multimodal and diurnal glycemic profiles for disease characterization and risk stratification remains unknown. Here, in the iCanNet cohort of 90,757 participants, we examined the associations of 48 CGM-derived metrics with prediabetes, T2D, and T1D, compared to normoglycemia. We further employed Gaussian Mixture Model to define glycemic phenotypes and established digital glycemic risk score (DGRS) to quantify complication risks in T2D. Participants with prediabetes, T2D, or T1D exhibited distinct CGM signatures compared to normoglycemic individuals (all P < 0.001). Integration of top five metrics significantly improved diabetes classification, and calibration analyses showed agreement between predicted and observed risks. Four glycemic phenotypes were identified in T2D, with sustained hyperglycemia associated with a 59% increased risk of acute complications, and high glycemic variability associated with 75% and 41% higher risks of acute and chronic complications, respectively. The DGRS identified residual risk among patients achieving time in range ≥70%, reclassifying 25.0% and 22.3% of these individuals to high-risk groups for acute and chronic complications, respectively. In summary, this study revealed distinct CGM-derived signatures across diabetes statuses and established a multimodal framework for identifying high-risk individuals with T2D who may be overlooked by conventional biomarkers.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"159 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149208664","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

A “growth mindset of mental health” intervention increases the likelihood of initiating self-help on a mental health app: a randomized controlled trial 一项“心理健康成长心态”干预增加了在心理健康应用程序上启动自助的可能性：一项随机对照试验

IF 15.2 1区医学

NPJ Digital Medicine Pub Date : 2026-10-13 DOI: 10.1038/s41746-026-03322-w

Sean H. Y. Toh,E. J. Horberg,Feodora R. Kosasih,Oliver Sündermann,Paul A. O’Keefe

{"title":"A “growth mindset of mental health” intervention increases the likelihood of initiating self-help on a mental health app: a randomized controlled trial","authors":"Sean H. Y. Toh,E. J. Horberg,Feodora R. Kosasih,Oliver Sündermann,Paul A. O’Keefe","doi":"10.1038/s41746-026-03322-w","DOIUrl":"https://doi.org/10.1038/s41746-026-03322-w","url":null,"abstract":"Abstract Mental health apps hold potential to improve access to treatment, but engagement remains low. One barrier may be the belief that mental health cannot be meaningfully improved. In a randomized controlled trial ( N = 252), we examined whether a brief growth-mindset-of-mental-health intervention—portraying mental health as improvable, not fixed—can initiate mental health app engagement among people with mental health needs. Participants completed baseline well-being measures (stress, anxiety and depression, and positive mental well-being) and were randomly assigned to the growth-mindset-of-mental-health or active control condition. Over the subsequent three months, we tracked whether they re-engaged with the app overall (i.e., completed at least a second self-help feature), and with features categorized as low-, moderate-, and high-intensity. Analyses revealed that participants in the growth-mindset condition (vs. control) with poorer baseline mental well-being (i.e., higher stress, anxiety and depressive symptoms, and lower positive mental well-being) were significantly more likely to show repeat app engagement. Moreover, those with higher anxiety and depressive symptoms were more likely to show repeat engagement with moderate-intensity features, while those experiencing higher stress and lower positive mental well-being were more likely to do so with both low- and moderate-intensity features. Together, these findings demonstrate the benefits of the growth-mindset intervention for successful initiation of self-help on a mental health app. Trial Registration: The trial was registered on ClinicalTrials.gov (Identifier: NCT07071311) on July 25, 2025.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"11 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149208661","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