Frontiers in digital health最新文献

{"title":"Impact on women's body satisfaction of exposure to postpartum imagery on social media.","authors":"Megan L Gow, Maddison Henderson, Amanda Henry, Lynne Roberts, Heike Roth","doi":"10.3389/fdgth.2025.1379337","DOIUrl":"10.3389/fdgth.2025.1379337","url":null,"abstract":"<p><strong>Background: </strong>Social networking sites may be a convenient, accessible and low-cost option for delivering health information at scale to postpartum women. However, social media use is associated with decreased body satisfaction and may contribute to psychological ill-health. Our study aimed to determine whether exposure to body-focused imagery, typical of imagery targeting postpartum women on Instagram, is associated with a reduction in state body satisfaction and state body appreciation. Secondly, we aimed to determine whether including postpartum-health-focused imagery, in conjunction with body-focused imagery, is associated with improving state body satisfaction/appreciation, compared with no postpartum health content.</p><p><strong>Methods: </strong>A single blinded quasi-experimental survey study, recruiting women who had given birth in the previous 2-years, asked participants about key demographic information, social media use and assessed thin-ideal internalization and media appearance pressures using validated tools. Participants were then exposed to either (1) 15 body-focused images of women with a thin-average level of adiposity; (2) as per (1) PLUS 5 postpartum-health-focused images; or (3) as per (1) PLUS 15 postpartum-health-focused images. State body satisfaction/appreciation were assessed before and after image exposure.</p><p><strong>Results: </strong>State body satisfaction/appreciation did not change from pre- to post-image exposure in any groups and measures were not different between groups at any time point.</p><p><strong>Discussion: </strong>Short-term exposure to body-focused imagery typical of Instagram content targeting postpartum women may not alter state body satisfaction or state body appreciation. Furthermore, incorporating postpartum-health-focused imagery did not alter results. Further research investigating whether an intervention providing health information to postpartum women via social media platforms improves health outcomes may be warranted.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1379337"},"PeriodicalIF":3.2,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11937002/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143722888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Responsible design of an AI system for health behavior change-an ethics perspective on the participatory design process of the STAR-C digital coach.","authors":"Helena Lindgren, Kristina Lindvall, Linda Richter-Sundberg","doi":"10.3389/fdgth.2025.1436347","DOIUrl":"10.3389/fdgth.2025.1436347","url":null,"abstract":"<p><strong>Introduction: </strong>The increased focus on the ethical aspects of artificial intelligence (AI) follows the increased use in society of data-driven analyses of personal information collected in the use of digital applications for various purposes that the individual is often not aware of. The purpose of this study is to investigate how values and norms are transformed into design choices in a participatory design process of an AI-based digital coaching application for promoting health and to prevent cardiovascular diseases, where a variety of expertise and perspectives are represented.</p><p><strong>Method: </strong>A participatory design process was conducted engaging domain professionals and potential users in co-design workshops, interviews and observations of prototype use. The design process and outcome was analyzed from a responsible design of AI systems perspective.</p><p><strong>Results: </strong>The results include deepened understanding of the values and norms underlying health coaching applications and how an AI-based intervention could provide person-tailored support in managing conflicting norms. Further, the study contributes to increased awareness of the value of participatory design in achieving value-based design of AI systems aimed at promoting health through behavior change, and the inclusion of social norms as a design material in the process.</p><p><strong>Conclusion: </strong>It was concluded that the relationship between the anticipated future users and the organization(s) or enterprises developing and implementing the health-promoting application is directing which values are manifested in the application.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1436347"},"PeriodicalIF":3.2,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11934961/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143712295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Bench to bedside: AI and remote patient monitoring.","authors":"Ramin Ramezani, Saam Iranmanesh, Arash Naeim, Peyman Benharash","doi":"10.3389/fdgth.2025.1584443","DOIUrl":"https://doi.org/10.3389/fdgth.2025.1584443","url":null,"abstract":"","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1584443"},"PeriodicalIF":3.2,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11933033/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143712231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in nursing: an integrative review of clinical and operational impacts.","authors":"Salwa Hassanein, Rabie Adel El Arab, Amany Abdrbo, Mohammad S Abu-Mahfouz, Mastoura Khames Farag Gaballah, Mohamed Mahmoud Seweid, Mohammed Almari, Husam Alzghoul","doi":"10.3389/fdgth.2025.1552372","DOIUrl":"10.3389/fdgth.2025.1552372","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Advances in digital technologies and artificial intelligence (AI) are reshaping healthcare delivery, with AI increasingly integrated into nursing practice. These innovations promise enhanced diagnostic precision, improved operational workflows, and more personalized patient care. However, the direct impact of AI on clinical outcomes, workflow efficiency, and nursing staff well-being requires further elucidation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This integrative review synthesized findings from 18 studies published through November 2024 across diverse healthcare settings. Using the PRISMA 2020 and SPIDER frameworks alongside rigorous quality appraisal tools (MMAT and ROBINS-I), the review examined the multifaceted effects of AI integration in nursing. Our analysis focused on three principal domains: clinical advancements and patient monitoring, operational efficiency and workload management, and ethical implications.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The review demonstrates that AI integration in nursing has yielded substantial clinical and operational benefits. AI-powered monitoring systems, including wearable sensors and real-time alert platforms, have enabled nurses to detect subtle physiological changes-such as early fever onset or pain indicators-well before traditional methods, resulting in timely interventions that reduce complications, shorten hospital stays, and lower readmission rates. For example, several studies reported that early-warning algorithms facilitated faster clinical responses, thereby improving patient safety and outcomes. Operationally, AI-based automation of routine tasks (e.g., scheduling, administrative documentation, and predictive workload classification) has streamlined resource allocation. These efficiencies have led to a measurable reduction in nurse burnout and improved job satisfaction, as nurses can devote more time to direct patient care. However, despite these benefits, ethical challenges remain prominent. Key concerns include data privacy risks, algorithmic bias, and the potential erosion of clinical judgment due to overreliance on technology. These issues underscore the need for robust ethical frameworks and targeted AI literacy training within nursing curricula.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;This review demonstrates that AI integration holds transformative potential for nursing practice by enhancing both clinical outcomes and operational efficiency. However, to realize these benefits fully, it is imperative to develop robust ethical frameworks, incorporate comprehensive AI literacy training into nursing education, and foster interdisciplinary collaboration. Future longitudinal studies across varied clinical contexts are essential to validate these findings and support the sustainable, equitable implementation of AI technologies in nursing. Policymakers and healthcare leaders must prioritize investments in AI solutions that complement the expertise of nursing professionals w","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1552372"},"PeriodicalIF":3.2,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926144/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of a digital blood pressure coach on hypertension management in primary care practices-a pragmatic, randomised controlled trial.","authors":"Christian Beger, Dominik Rüegger, Anna Lenz, Steffen Wagner, Kai Martin Schmidt-Ott, Dirk Volland, Florian P Limbourg","doi":"10.3389/fdgth.2025.1516600","DOIUrl":"10.3389/fdgth.2025.1516600","url":null,"abstract":"<p><strong>Importance: </strong>Smartphone medical applications (apps) may improve blood pressure (BP) control in the primary care setting in patients with hypertension. However, real-world evidence from primary care is largely lacking.</p><p><strong>Objective: </strong>To analyse, in primary care practices in Germany, the effect of a smartphone app on systolic BP compared to standard of care.</p><p><strong>Design: </strong>A pragmatic, non-blinded randomized controlled trial with patients with a diagnosis of hypertension was conducted across 23 general practices in Germany, with a follow-up period of 3 months. Recruitment occurred from January 2022 to May 2023.</p><p><strong>Intervention: </strong>The intervention group received access to the Manoa app, a smartphone coach integrating guideline-compliant home BP monitoring and lifestyle-coaching. All study participants received standard treatment for arterial hypertension at the discretion of the treating physician.</p><p><strong>Main outcomes: </strong>The primary outcome was office systolic BP (oSBP) after 90-150 days in participants with uncontrolled hypertension (oSBP ≥140 mmHg). Secondary outcomes included changes in systolic and diastolic BP, BP control and adherence to home blood pressure monitoring.</p><p><strong>Results: </strong>A total of 606 participants from 23 general practices were randomized, after data clearance and review, 249 participants were assigned to the control group and 259 to the intervention group for analysis. The mean age (SD) of participants in the intervention group was 55.9 (12.9) years. At baseline, participants with uncontrolled hypertension had a mean oSBP (SD) of 152.6 (14.2) mmHg in the intervention group (<i>n</i> = 162) and 152.6 (14.1) mmHg in the control group (<i>n</i> = 147). After 120 ± 14 days, oSBP decreased to 137.4 (14.4) mmHg in the intervention group and to 137.7 (14.5) mmHg in the control group, with a between-group mean difference of -0.2 mmHg [95% CI (-3.9,3.5); <i>P</i> =.9]. At the follow-up appointment, 69.1% of participants in the intervention group submitted a BP-diary, compared to 36.1% in the control group [OR = 3.95; 95% CI (2.73,5.72); <i>P</i> = <0.001].</p><p><strong>Conclusions and relevance: </strong>Participants with uncontrolled hypertension randomized to an app in primary care achieved similar decreases in systolic BP but higher adherence to home BP monitoring compared to standard care. In this open-label, pragmatic trial, variability in hypertension management strategies and limited standardization across practices may have confounded the precise evaluation of digital intervention benefits.</p><p><strong>Clinical trial registration: </strong>ClinicalTrials.gov, identifier, (DRKS00027964).</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1516600"},"PeriodicalIF":3.2,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11925922/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trustworthiness of the electronic health record in Germany: an exploratory, user-centered analysis.","authors":"Niklas von Kalckreuth, Marvin Kopka, Christine Schmid, Cornelia Kratzer, Anna Reptuschenko, Markus A Feufel","doi":"10.3389/fdgth.2025.1473326","DOIUrl":"10.3389/fdgth.2025.1473326","url":null,"abstract":"<p><strong>Introduction: </strong>The integration of Electronic Health Records (EHRs) offers significant potential to improve patient care and reduce costs. In Germany, every patient will be provided with an EHR starting January 2025. However, the success of EHRs depends on patient trust and usage. Understanding the factors that shape perceived trustworthiness is crucial, yet EHR-specific research remains limited.</p><p><strong>Methods: </strong>To explore key factors influencing initial trust, 30 German participants interacted with a functionally realistic EHR prototype. Semi-structured interviews were conducted to evaluate its trustworthiness and suggest improvements.</p><p><strong>Results: </strong>Thematic analysis identified five key themes: Provider Reputation, User Feedback, User Experience of Contents, User Experience of Functions, and User Data Control.</p><p><strong>Discussion: </strong>Fostering trust in the German EHR requires attention to technical features and contextual factors. Beyond provider reputation, three aspects emerged as central: (a) professional visual and user experience design to enhance usability and signal reliability; (b) accurate, clear content to foster transparency; and (c) user empowerment through intuitive data control and accessible support. Transparent communication about GDPR compliance further strengthens trust and supports adoption. In Germany's tightly regulated environment, clearly conveying EHR security standards, providing robust support, and leveraging social proof can significantly enhance trust and drive adoption of digital health solutions.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1473326"},"PeriodicalIF":3.2,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926143/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"User-centred digital solution for dentofacial deformities management: an innovative approach technology based.","authors":"Vincenzo Abbate, Emanuele Carraturo, Giulia Togo, Stefania Troise, Federica Calabrìa, Mauro Cataldi, Daniela Adamo, Guido Iaccarino, Maddalena Illario, Riccardo Nocini, Giovanni Dell'Aversana Orabona","doi":"10.3389/fdgth.2025.1502853","DOIUrl":"10.3389/fdgth.2025.1502853","url":null,"abstract":"<p><strong>Objective: </strong>Dentofacial deformities (DFD) encompass a range of conditions affecting approximately 60% of the population, varying from mild to severe cases. Managing these disorders requires a multidisciplinary approach, yet establishing a unified therapeutic protocol across different specialties often proves challenging. This underscores the necessity to understand the specific needs and demands of patients diagnosed with DFD, aiming to develop an effective treatment pathway. The objective of our study is to identify the unmet needs of patients with DFD and to propose digital solutions, based on Information and Communication Technology (ICT), that can help patients meet these needs by improving the diagnostic-therapeutic pathway.</p><p><strong>Methods: </strong>By examining the medical records of 147 patients diagnosed with DFD, a team of specialists created the profile of a hypothetical DFD patient, termed \"Persona\" by using the \"Blueprint- persona\". This Persona theoretically represents the broader DFD patient population, capturing their needs, demands, goals, problems, and challenges. Based on these findings, a comprehensive 'DFD Management Pathway' is proposed, encompassing both general and specialized preoperative and postoperative consultations required for these patients.</p><p><strong>Results: </strong>The identified unmet needs of a typical DFD patient were psychological support, nutritional support and diet recommendations, advice on oral hygiene, assistance by specialized professionals. The proposed digital solutions were the use of video tutorials and online courses, daily notifications on applications on smartphones, social media channel and multidisciplinary platform.</p><p><strong>Conclusion: </strong>This study highlights that the Blueprint methodology proves instrumental in pinpointing specific characteristics and unmet needs of various patient groups. The critical gaps in the diagnostic-therapeutic pathway for patients with dentofacial deformities and underscores the potential of digital solutions in addressing these unmet needs. By creating a detailed patient Persona, by using The Blueprint methodology, and mapping their challenges, psychological support, nutritional guidance, oral hygiene advice have been identified as unmeet needs. The proposed digital tools, including video tutorials, online courses, smartphone notifications, social media channels, and multidisciplinary platforms, provide a promising avenue to enhance patient engagement, streamline care delivery, and improve overall treatment outcomes. Future research should focus on validating these solutions in clinical settings to ensure their feasibility and effectiveness in addressing the unique demands of DFD patients.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1502853"},"PeriodicalIF":3.2,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11922915/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143671694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Noncontact evaluation of autonomic nervous system activity during exercise by using video analysis.","authors":"Kanaru Fumimoto, Shima Okada, Ryohei Tsuji, Yusuke Sakaue, Naruhiro Shiozawa, Hieyong Jeong, Masaaki Makikawa","doi":"10.3389/fdgth.2025.1536492","DOIUrl":"10.3389/fdgth.2025.1536492","url":null,"abstract":"<p><strong>Introduction: </strong>Autonomic nervous system activity (ANSA) plays a crucial role in the physical condition experienced during exercise and prolonged physical activity. In other words, ANSA is related to exercise performance and physical condition. Therefore, it is important to continuously monitor ANSA during high-intensity and sustained exercise. To this end, an uncomplicated and noncontact measurement system is preferable. Hence, in this study, we propose a method for the noncontact measurement of capillary contraction and dilation state, representative of ANSA, using a common commercial camera.</p><p><strong>Methods: </strong>Specifically, we focused on alterations in the green value of facial video images, from which we derived the green-to-blue (G/B) ratio as an indicator of blood vessel dilation and contraction, and to facilitate assessment of their activity. We performed a validation experiment involving exercise tasks using an ergometer in 10 healthy adults (23 ± 1.6 years old). The G/B ratio shows the state of contraction and expansion of facial capillaries, and it was evaluated using heart rate as ground truth data of the fluctuation of autonomic nerve activity.</p><p><strong>Results: </strong>We observed an increase in heart rate with decreased G/B ratio during exercise in all subjects. Postexercise, the heart rate decreased but the G/B ratio increased.</p><p><strong>Discussion: </strong>During exercise, characterized by dominant sympathetic NSA, the G/B ratio decreased, and recovered after exercise when parasympathetic NSA was dominant. In this way, noncontact evaluation of ASNA was achieved by using the G/B ratio. In the future, this measurement system will be applied to functional tests for heat acclimation.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1536492"},"PeriodicalIF":3.2,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11919914/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in clinical medicine: a state-of-the-art overview of systematic reviews with methodological recommendations for improved reporting.","authors":"Giovanni Morone, Luigi De Angelis, Alex Martino Cinnera, Riccardo Carbonetti, Alessio Bisirri, Irene Ciancarelli, Marco Iosa, Stefano Negrini, Carlotte Kiekens, Francesco Negrini","doi":"10.3389/fdgth.2025.1550731","DOIUrl":"10.3389/fdgth.2025.1550731","url":null,"abstract":"<p><p>Medicine has become increasingly receptive to the use of artificial intelligence (AI). This overview of systematic reviews (SRs) aims to categorise current evidence about it and identify the current methodological state of the art in the field proposing a classification of AI model (CLASMOD-AI) to improve future reporting. PubMed/MEDLINE, Scopus, Cochrane library, EMBASE and Epistemonikos databases were screened by four blinded reviewers and all SRs that investigated AI tools in clinical medicine were included. 1923 articles were found, and of these, 360 articles were examined via the full-text and 161 SRs met the inclusion criteria. The search strategy, methodological, medical and risk of bias information were extracted. The CLASMOD-AI was based on input, model, data training, and performance metric of AI tools. A considerable increase in the number of SRs was observed in the last five years. The most covered field was oncology accounting for 13.9% of the SRs, with diagnosis as the predominant objective in 44.4% of the cases). The risk of bias was assessed in 49.1% of included SRs, yet only 39.2% of these used tools with specific items to assess AI metrics. This overview highlights the need for improved reporting on AI metrics, particularly regarding the training of AI models and dataset quality, as both are essential for a comprehensive quality assessment and for mitigating the risk of bias using specialized evaluation tools.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1550731"},"PeriodicalIF":3.2,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11920125/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of AI in empowering and redefining the oncology care landscape: perspective from a developing nation.","authors":"Isha Goel, Yogendra Bhaskar, Nand Kumar, Sunil Singh, Mohammed Amanullah, Ruby Dhar, Subhradip Karmakar","doi":"10.3389/fdgth.2025.1550407","DOIUrl":"10.3389/fdgth.2025.1550407","url":null,"abstract":"<p><p>Early diagnosis and accurate prognosis play a pivotal role in the clinical management of cancer and in preventing cancer-related mortalities. The burgeoning population of Asia in general and South Asian countries like India in particular pose significant challenges to the healthcare system. Regrettably, the demand for healthcare services in India far exceeds the available resources, resulting in overcrowded hospitals, prolonged wait times, and inadequate facilities. The scarcity of trained manpower in rural settings, lack of awareness and low penetrance of screening programs further compounded the problem. Artificial Intelligence (AI), driven by advancements in machine learning, deep learning, and natural language processing, can profoundly transform the underlying shortcomings in the healthcare industry, more for populous nations like India. With about 1.4 million cancer cases reported annually and 0.9 million deaths, India has a significant cancer burden that surpassed several nations. Further, India's diverse and large ethnic population is a data goldmine for healthcare research. Under these circumstances, AI-assisted technology, coupled with digital health solutions, could support effective oncology care and reduce the economic burden of GDP loss in terms of years of potential productive life lost (YPPLL) due to India's stupendous cancer burden. This review explores different aspects of cancer management, such as prevention, diagnosis, precision treatment, prognosis, and drug discovery, where AI has demonstrated promising clinical results. By harnessing the capabilities of AI in oncology research, healthcare professionals can enhance their ability to diagnose cancers at earlier stages, leading to more effective treatments and improved patient outcomes. With continued research and development, AI and digital health can play a transformative role in mitigating the challenges posed by the growing population and advancing the fight against cancer in India. Moreover, AI-driven technologies can assist in tailoring personalized treatment plans, optimizing therapeutic strategies, and supporting oncologists in making well-informed decisions. However, it is essential to ensure responsible implementation and address potential ethical and privacy concerns associated with using AI in healthcare.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1550407"},"PeriodicalIF":3.2,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11913822/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}