{"title":"Integrating personalized shape prediction, biomechanical modeling, and wearables for bone stress prediction in runners.","authors":"Liangliang Xiang,Yaodong Gu,Kaili Deng,Zixiang Gao,Vickie Shim,Alan Wang,Justin Fernandez","doi":"10.1038/s41746-025-01677-0","DOIUrl":"https://doi.org/10.1038/s41746-025-01677-0","url":null,"abstract":"Running biomechanics studies the mechanical forces experienced during running to improve performance and prevent injuries. This study presents the development of a digital twin for predicting bone stress in runners. The digital twin leverages a domain adaptation-based Long Short-Term Memory (LSTM) algorithm, informed by wearable sensor data, to dynamically simulate the structural behavior of foot bones under running conditions. Data from fifty participants, categorized as rearfoot and non-rearfoot strikers, were used to create personalized 3D foot models and finite element simulations. Two nine-axis inertial sensors captured three-axis acceleration data during running. The LSTM neural network with domain adaptation proved optimal for predicting bone stress in key foot bones-specifically the metatarsals, calcaneus, and talus-during the mid-stance and push-off phases (RMSE < 8.35 MPa). This non-invasive, cost-effective approach represents a significant advancement for precision health, contributing to the understanding and prevention of running-related fracture injuries.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"35 1","pages":"276"},"PeriodicalIF":15.2,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143945241","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}
{"title":"Scaling enterprise AI in healthcare: the role of governance in risk mitigation frameworks","authors":"Andreea Bodnari, John Travis","doi":"10.1038/s41746-025-01700-4","DOIUrl":"https://doi.org/10.1038/s41746-025-01700-4","url":null,"abstract":"<p>This perspective article examines the role of governance frameworks in mitigating risks and building trust in AI implementations within healthcare organizations. As AI technologies rapidly evolve, robust governance is essential to manage potential adverse incidents and ensure fair, equitable, and effective innovation. This article highlights key risks associated with AI deployments and proposes enhancements to enterprise AI governance to better address these challenges posed by AI and digital health innovations.</p>","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"1 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143940050","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}
Ashley C. Griffin, Meagan F. Moyer, Arash Anoshiravani, Sondra Hornsey, Christopher D. Sharp
{"title":"A sociotechnical approach to defining clinical responsibilities for patient-generated health data","authors":"Ashley C. Griffin, Meagan F. Moyer, Arash Anoshiravani, Sondra Hornsey, Christopher D. Sharp","doi":"10.1038/s41746-025-01680-5","DOIUrl":"https://doi.org/10.1038/s41746-025-01680-5","url":null,"abstract":"The proliferation of health devices and apps has led to an abundance of patient-generated health data (PGHD), which has raised concerns about integration within clinical settings. We describe one health system’s sequential focus group approach for developing guiding principles to inform clinical responsibilities of PGHD. These principles center around (1) setting expectations; (2) preparing staffing and workflows; (3) delivering high-quality experiences; and (4) considerations for health information management of PGHD.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"51 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143940202","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}
Jacqueline M. Beltrán, Yael Jacob, Marishka M. Mehta, Tasnim Hossain, Abigail Adams, Samantha Fontaine, John Torous, Catherine McDonough, Matthew Johnson, Andrew D. Delgado, James W. Murrough, Laurel S. Morris
{"title":"Digital measures of activity and motivation impact depression and anxiety in the real world","authors":"Jacqueline M. Beltrán, Yael Jacob, Marishka M. Mehta, Tasnim Hossain, Abigail Adams, Samantha Fontaine, John Torous, Catherine McDonough, Matthew Johnson, Andrew D. Delgado, James W. Murrough, Laurel S. Morris","doi":"10.1038/s41746-025-01669-0","DOIUrl":"https://doi.org/10.1038/s41746-025-01669-0","url":null,"abstract":"<p>Mood and anxiety disorders are highly comorbid, with symptom severity varying over time. Individuals with and without these disorders completed 30-days of ecological momentary assessment (EMAs) of depression, anxiety and distress, developed based on the established Mood and Anxiety Symptom Questionnaire (MASQ). These electronic MASQ (eMASQ) EMAs were collected alongside novel intrinsic and extrinsic motivation EMAs, and physical/digital activity measures (steps/screentime) across <i>N</i> = 70–101 participants. Each eMASQ-EMA significantly related to its corresponding MASQ measure. Extrinsic and intrinsic motivation negatively related to each eMASQ-EMA and had the greatest influence on patients’ overall symptom profile. Physical, but not digital activity, was negatively associated with concurrent and 1-week lagged anxiety and depression, highlighting the temporally delayed benefits of physical activity on depression and anxiety symptoms in psychiatric groups. Collectively, this study suggests cognitive constructs related to drive and physical activity, may be useful in predicting continuous and transient psychiatric symptoms in the real-world.</p>","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"9 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143932477","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}
Elizabeth Geena Woo, Michael C. Burkhart, Emily Alsentzer, Brett K. Beaulieu-Jones
{"title":"Synthetic data distillation enables the extraction of clinical information at scale","authors":"Elizabeth Geena Woo, Michael C. Burkhart, Emily Alsentzer, Brett K. Beaulieu-Jones","doi":"10.1038/s41746-025-01681-4","DOIUrl":"https://doi.org/10.1038/s41746-025-01681-4","url":null,"abstract":"<p>Large-language models (LLMs) show promise for clinical note information extraction, but deployment challenges include high computational costs and privacy concerns. We used synthetic data distillation to fine-tune smaller, open-source LLMs to achieve performance comparable to larger models while enabling local hardware deployment or reduced cloud costs. Using Llama-3.1-70B-Instruct, we generated synthetic question-answer training pairs to fine-tune smaller Llama models. We evaluated performance across three tasks: synthetic clinical trial criteria, the i2b2 2018 Clinical Trial Eligibility Challenge, and apixaban trial criteria questions. The 8B-parameter model achieved high accuracy across all tasks and sometimes outperformed the 70B-Instruct teacher model. Fine-tuning with only the most challenging questions still improved performance, demonstrating the value of targeted training. Results from 3B- and 1B-parameter models showed a clear size-performance tradeoff. This work demonstrates synthetic data distillation’s potential for enabling scalable clinical information extraction.</p>","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"50 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143932483","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}
Jürgen Barth, Sonja Schläpfer, Fabian Schneider, Prabhakaran Santhanam, Tobias Kowatsch, Priska Heinz, Ulrike Held, Manuela Eicher, Claudia M. Witt
{"title":"Mobile health intervention CanRelax reduces distress in people with cancer in a randomized controlled trial","authors":"Jürgen Barth, Sonja Schläpfer, Fabian Schneider, Prabhakaran Santhanam, Tobias Kowatsch, Priska Heinz, Ulrike Held, Manuela Eicher, Claudia M. Witt","doi":"10.1038/s41746-025-01688-x","DOIUrl":"https://doi.org/10.1038/s41746-025-01688-x","url":null,"abstract":"<p>Mindfulness and relaxation exercises are effective face-to-face interventions for reducing distress in people with cancer. Their effectiveness in mobile health settings has yet to be investigated. This study evaluated the effectiveness of the CanRelax 2 app in reducing distress in people with cancer. German-speaking adults diagnosed with cancer within the last five years with elevated distress levels (Distress Thermometer ≥5) were recruited. Participants were randomized to the CanRelax 2 app or a waitlist control group. The primary endpoint was the Patient Health Questionnaire Anxiety and Depression Scale (PHQ-ADS) after 10 weeks (210 participants). We observed a clinically meaningful larger reduction in PHQ-ADS scores in the intervention group compared to the control group (−3.7, 95%-CI from −5.7 to −1.6; <i>p</i> = 0.0005). Similar effects were found for distress, well-being, and self-regulation. Our results confirm the effectiveness of a mobile health app in reducing distress in people with cancer. Registration: German Clinical Trials Register (DRKS00027546) on 23.02.2022</p>","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"21 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143932475","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}
Sarah E. Polk, Fredrik Öhman, Jason Hassenstab, Alexandra König, Kathryn V. Papp, Michael Schöll, David Berron
{"title":"A scoping review of remote and unsupervised digital cognitive assessments in preclinical Alzheimer’s disease","authors":"Sarah E. Polk, Fredrik Öhman, Jason Hassenstab, Alexandra König, Kathryn V. Papp, Michael Schöll, David Berron","doi":"10.1038/s41746-025-01583-5","DOIUrl":"https://doi.org/10.1038/s41746-025-01583-5","url":null,"abstract":"<p>Characterizing subtle cognitive changes in preclinical Alzheimer’s disease (AD) is difficult using traditional neuropsychological assessments. Remote and unsupervised digital assessments can improve scalability, measurement reliability, and ecological validity, enabling the capture of subtle changes. We evaluate such tools for use in preclinical AD, or cognitively unimpaired individuals with abnormal levels of AD pathology. We screened 1904 reports for studies remotely assessing cognition in preclinical AD samples. Twenty-three tools were identified, and their usability, reliability, and validity, including construct and criterion validity based on in-person neuropsychological and Aβ/tau measures, was reported. We present a necessary update to a rapidly evolving field, following our previous review (Öhman et al., 2021) and address open questions of feasibility and reliability of remote testing in older adults. Future applications of such tools are discussed, including longitudinal monitoring of cognition, scalable case finding, and individualized prognostics in both clinical trials and healthcare contexts.</p>","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"50 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930955","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}
George S. Liu, Soraya Fereydooni, Melissa Chaehyun Lee, Srinidhi Polkampally, Jeffrey Huynh, Sravya Kuchibhotla, Mihir M. Shah, Noel F. Ayoub, Robson Capasso, Michael T. Chang, Philip C. Doyle, F. Christopher Holsinger, Zara M. Patel, Jon-Paul Pepper, C. Kwang Sung, Francis X. Creighton, Nikolas H. Blevins, Konstantina M. Stankovic
{"title":"Scoping review of deep learning research illuminates artificial intelligence chasm in otolaryngology-head and neck surgery","authors":"George S. Liu, Soraya Fereydooni, Melissa Chaehyun Lee, Srinidhi Polkampally, Jeffrey Huynh, Sravya Kuchibhotla, Mihir M. Shah, Noel F. Ayoub, Robson Capasso, Michael T. Chang, Philip C. Doyle, F. Christopher Holsinger, Zara M. Patel, Jon-Paul Pepper, C. Kwang Sung, Francis X. Creighton, Nikolas H. Blevins, Konstantina M. Stankovic","doi":"10.1038/s41746-025-01693-0","DOIUrl":"https://doi.org/10.1038/s41746-025-01693-0","url":null,"abstract":"<p>Clinical validation studies are important to translate artificial intelligence (AI) technology in healthcare but may be underperformed in Otolaryngology - Head & Neck Surgery (OHNS). This scoping review examined deep learning publications in OHNS between 1996 and 2023. Searches on MEDLINE, EMBASE, and Web of Science databases identified 3236 articles of which 444 met inclusion criteria. Publications increased exponentially from 2012–2022 across 48 countries and were most concentrated in otology and neurotology (28%), most targeted extending health care provider capabilities (56%), and most used image input data (55%) and convolutional neural network models (63%). Strikingly, nearly all studies (99.3%) were in silico, proof of concept early-stage studies. Three (0.7%) studies conducted offline validation and zero (0%) clinical validation, illuminating the “AI chasm” in OHNS. Recommendations to cross this chasm include focusing on low complexity and low risk tasks, adhering to reporting guidelines, and prioritizing clinical translation studies.</p>","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"9 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930954","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}
Krzysztof Bronowicki, Justyna Antoniuk-Majchrzak, Iwona Malesza, Wiktor Możarowski, Agnieszka Szymborska, Bartosz Pachuta, Tomasz Walenta, Wojciech Jasica, Maciej Stanuch, Andrzej Skalski, Anna Raciborska
{"title":"An attempt to evaluate the use of mixed reality in surgically treated pediatric oncology patients","authors":"Krzysztof Bronowicki, Justyna Antoniuk-Majchrzak, Iwona Malesza, Wiktor Możarowski, Agnieszka Szymborska, Bartosz Pachuta, Tomasz Walenta, Wojciech Jasica, Maciej Stanuch, Andrzej Skalski, Anna Raciborska","doi":"10.1038/s41746-025-01638-7","DOIUrl":"https://doi.org/10.1038/s41746-025-01638-7","url":null,"abstract":"<p>Mixed reality (MR) technology is increasingly used in surgical procedures, particularly in pediatric oncological surgery. The CarnaLife Holo system (MedApp S.A., Poland) converts medical imaging data into interactive 3D holograms for preoperative planning and intraoperative use. This study presents a preliminary evaluation of MR’s impact on surgical procedure (SP) duration and hospitalization (H) time. A retrospective analysis of patients treated between 2023 and 2024 compared outcomes of surgeries performed with (<i>n</i> = 9) and without MR. Diagnoses included pulmonary metastases, sacrococcygeal tumor, clavicle tumor, aneurysmal bone cyst, soft tissue tumors, femoral and chest wall tumors. SP duration in the MR group was generally comparable to conventional methods, with hospitalization times remaining within typical ranges. Although a slight increase in procedure time was observed in a few cases, MR did not significantly prolong SP or H. MR appears to be a promising tool in pediatric oncological surgery. Further research on larger cohorts is warranted.</p>","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"10 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143927323","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}
Lisa Moseley, Anna Laws, Michael Allen, Gary A. Ford, Martin James, Stephen McCarthy, Graham McClelland, Laura J. Park, Kerry Pearn, Daniel Phillips, Christopher Price, Lisa Shaw, Phil White, David Wilson, Peter McMeekin, Jason Scott
{"title":"Usability testing a web application to support evidence-based commissioning decisions for implementing mobile stroke units","authors":"Lisa Moseley, Anna Laws, Michael Allen, Gary A. Ford, Martin James, Stephen McCarthy, Graham McClelland, Laura J. Park, Kerry Pearn, Daniel Phillips, Christopher Price, Lisa Shaw, Phil White, David Wilson, Peter McMeekin, Jason Scott","doi":"10.1038/s41746-025-01691-2","DOIUrl":"https://doi.org/10.1038/s41746-025-01691-2","url":null,"abstract":"<p>Commissioning of innovations in healthcare is a complex socio-technical process, ideally informed by high quality evidence. However, evidence is not always prepared and presented in a format usable for commissioning decisions. Agile methodology, combined with qualitative co-design, were used to develop a digital web application incorporating machine learning models of stroke outcomes to inform commissioning decisions for the implementation of mobile stroke units (MSUs) in England, followed by usability testing using think aloud methodology. Sixteen stakeholders involved in developing consensus on model parameters and pathways participated with data thematically analysed. Required improvements to the web application were identified and novel insights into the complexity of context-specific commissioning decisions were generated, which also informed participants’ views on the viability of MSUs. This study provides empirical evidence in support of developing innovative and accessible digital dissemination methods to engage with commissioning processes and prospectively understand commissioning challenges.</p>","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"25 1","pages":""},"PeriodicalIF":15.2,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930956","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}