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Cancers
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Digital Health Technologies in Oncology
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Digital Health Technologies in Oncology

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Survivorship and Quality of Life".

Deadline for manuscript submissions: 10 October 2025 | Viewed by 8136

Special Issue Editor

Prof. Dr. Sorana D. BOLBOACĂ

E-Mail Website
Guest Editor
Department of Medical Informatics and Biostatistics, “Iuliu Haţieganu” University of Medicine and Pharmacy, Louis Pasteur Str., No. 6, 400349 Cluj-Napoca, Romania
Interests: applied and computational statistics; molecular modeling; genetic analysis; statistical modeling in medicine; integrated health informatics system; medical diagnostic research; statistical inference; medical imaging analysis; assisted decision systems; research ethics; social media and health information; evidence-based medicine
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Digital health technologies have started to play a fundamental role in healthcare by enhancing patient diagnosis and (remote) monitoring, streamlining processes, enabling precision medicine with data analytics, and improving healthcare access through telemedicine. As the healthcare landscape evolves, digital innovations are transforming cancer care, from early detection to precision treatment, monitoring and patient support.

We invite researchers, clinicians, and technologists to share their insights, studies, and innovations in digital health technologies applied in cancer management. Topics of interest include but are not limited to AI-driven diagnostics, telemedicine, wearable devices, and data analytics.

Do not miss this opportunity to contribute to the advancement of cancer care through digital health technologies. Submit your cutting-edge research today and shape the future of oncology.

Prof. Dr. Sorana D. BOLBOACĂ
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital healthcare
  • digital health technologies
  • diagnosis
  • wearable devices
  • rehabilitation technologies
  • assistive technologies
  • robotic surgery
  • (remote) monitoring
  • precision medicine
  • data analytics
  • healthcare teleassistance
  • AI-driven diagnostics and monitoring
  • AI-driven analytics

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Published Papers (6 papers)

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Research

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14 pages, 2113 KiB  
Article
Immersive Virtual Reality for Enabling Patient Experience and Enrollment in Oncology Clinical Trials: A Feasibility Study
by Frank Tsai, Landon Gray, Amy Mirabella, Margaux Steinbach, Jacqueline M. Garrick, Nadine J. Barrett, Nelson Chao and Frederic Zenhausern
Cancers 2025, 17(7), 1148; https://doi.org/10.3390/cancers17071148 - 29 Mar 2025
Viewed by 350
Abstract
Background/Objectives: Informed consent is a crucial part of the clinical trial enrollment process in which patients are asked to understand and provide approval for medical interventions. Consent forms can be complex and hinder patient comprehension, highlighting the need for novel tools to [...] Read more.
Background/Objectives: Informed consent is a crucial part of the clinical trial enrollment process in which patients are asked to understand and provide approval for medical interventions. Consent forms can be complex and hinder patient comprehension, highlighting the need for novel tools to improve the patient enrollment experience. This feasibility study aimed to develop an immersive technology to enroll human subjects in oncology clinical trials and provide 3D avatar-based informed consent in a virtual reality (VR) environment. Methods: Clinical feasibility and the effects of head-mounted VR devices on motion sickness and educational quality were evaluated in adult oncology patients enrolled in an intravenous (IV) port placement intervention study. Participants received before- and after-questionnaires to measure their understanding of the information received in VR. A follow-up questionnaire was given four weeks post-consent to measure knowledge retention. Results: Clinical staff reported that VR technology was manageable to use. Among 16 adult participants, all reported that VR was well tolerated with no motion sickness. The mean pre-intervention knowledge score was 64.6%, with an immediate post-intervention knowledge score of 97.9%. A mean knowledge score of 93.3% four-weeks post-consent was observed among 10/16 participants who completed a follow-up questionnaire. Conclusions: These findings support that VR is well tolerated and effective at delivering information during the informed consent process for oncology clinical trials. Key limitations include the small sample size and single clinical population. Further trials are warranted to compare efficacy over traditional consenting mechanisms and include more diverse clinical populations among a wider participant pool. Full article
(This article belongs to the Special Issue Digital Health Technologies in Oncology)
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15 pages, 1511 KiB  
Article
Transfer Learning-Based Integration of Dual Imaging Modalities for Enhanced Classification Accuracy in Confocal Laser Endomicroscopy of Lung Cancer
by Mircea-Sebastian Șerbănescu, Liliana Streba, Alin Dragoș Demetrian, Andreea-Georgiana Gheorghe, Mădălin Mămuleanu, Daniel-Nicolae Pirici and Costin-Teodor Streba
Cancers 2025, 17(4), 611; https://doi.org/10.3390/cancers17040611 - 11 Feb 2025
Viewed by 925
Abstract
Background/Objectives: Lung cancer remains the leading cause of cancer-related mortality, underscoring the need for improved diagnostic methods. This study seeks to enhance the classification accuracy of confocal laser endomicroscopy (pCLE) images for lung cancer by applying a dual transfer learning (TL) approach that [...] Read more.
Background/Objectives: Lung cancer remains the leading cause of cancer-related mortality, underscoring the need for improved diagnostic methods. This study seeks to enhance the classification accuracy of confocal laser endomicroscopy (pCLE) images for lung cancer by applying a dual transfer learning (TL) approach that incorporates histological imaging data. Methods: Histological samples and pCLE images, collected from 40 patients undergoing curative lung cancer surgeries, were selected to create 2 balanced datasets (800 benign and 800 malignant images each). Three CNN architectures—AlexNet, GoogLeNet, and ResNet—were pre-trained on ImageNet and re-trained on pCLE images (confocal TL) or using dual TL (first re-trained on histological images, then pCLE). Model performance was evaluated using accuracy and AUC across 50 independent runs with 10-fold cross-validation. Results: The dual TL approach statistically significant outperformed confocal TL, with AlexNet achieving a mean accuracy of 94.97% and an AUC of 0.98, surpassing GoogLeNet (91.43% accuracy, 0.97 AUC) and ResNet (89.87% accuracy, 0.96 AUC). All networks demonstrated statistically significant (p < 0.001) improvements in performance with dual TL. Additionally, dual TL models showed reductions in both false positives and false negatives, with class activation mappings highlighting enhanced focus on diagnostically relevant regions. Conclusions: Dual TL, integrating histological and pCLE imaging, results in a statistically significant improvement in lung cancer classification. This approach offers a promising framework for enhanced tissue classification. and with future development and testing, iy has the potential to improve patient outcomes. Full article
(This article belongs to the Special Issue Digital Health Technologies in Oncology)
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13 pages, 1540 KiB  
Article
Digital Rehabilitation Program for Breast Cancer Survivors on Adjuvant Hormonal Therapy: A Feasibility Study
by Wing-Lok Chan, Yat-Lam Wong, Yin-Ling Tai, Michelle Liu, Bryan Yun, Yuning Zhang, Holly Li-Yu Hou, Dora Kwong, Victor Ho-Fun Lee and Wendy Wing-Tak Lam
Cancers 2024, 16(23), 4084; https://doi.org/10.3390/cancers16234084 - 5 Dec 2024
Viewed by 1231
Abstract
Background: Breast cancer survivors often face physical and psychological challenges, including weight gain, metabolic syndrome, and reduced quality of life. To address these concerns, a mobile app-based rehabilitation program called “THRIVE” was developed to improve physical activity, medication adherence, and health-related quality [...] Read more.
Background: Breast cancer survivors often face physical and psychological challenges, including weight gain, metabolic syndrome, and reduced quality of life. To address these concerns, a mobile app-based rehabilitation program called “THRIVE” was developed to improve physical activity, medication adherence, and health-related quality of life (HRQoL) in this population. Methods: This prospective, single-arm study assessed the feasibility and effectiveness of the “THRIVE” app among breast cancer survivors undergoing hormonal therapy. Participants were recruited from Queen Mary Hospital in Hong Kong between December 2022 and June 2023. Eligible survivors had completed treatment within the last five years or had stable advanced disease on hormonal therapy. Participants monitored their exercise, medication adherence, and self-care via the app and a Fitbit activity tracker for 16 weeks. Primary outcomes included recruitment, dropout, adherence rates, and safety. Secondary outcomes, measured at baseline and week 16, included physical activity intensity, HRQoL, psychological stress, body composition, and app satisfaction. Results: A total of 50 participants, with a median age of 53 years, completed the study. The recruitment rate was 70.4% with no dropouts. The adherence rate, measured by completing exercises recommended in the mobile app at least three times per week, was 74%. No severe adverse events were reported. While physical activity intensity showed no significant changes from baseline to week 16 (p = 0.24), cognitive function (p = 0.021), future perspective (p = 0.044), arm symptoms (p = 0.042), depression (p = 0.01), and anxiety (p = 0.004) improved. All participants reported perfect medication compliance (100%). Satisfaction with the app was high. Conclusions: This mobile app-based rehabilitation program demonstrated good feasibility, with satisfactory recruitment, adherence, and safety, providing valuable insights into future definitive studies. Full article
(This article belongs to the Special Issue Digital Health Technologies in Oncology)
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13 pages, 1090 KiB  
Article
Introduction of an Educational Video to Enhance the Informed Consent Process in Postoperative Radiation Therapy of Breast Cancer Patients
by Samuel M. Vorbach, Martin Pointner, Jens Lehmann, Julian Mangesius, Tilmann Hart, Claudia Gstir, Theresa Rändler, Thomas Seppi, Ute Ganswindt and Siegfried Kollotzek
Cancers 2024, 16(20), 3552; https://doi.org/10.3390/cancers16203552 - 21 Oct 2024
Viewed by 1075
Abstract
Background/Objectives: Informed consent is crucial in medical practice, especially for complex treatments such as postoperative radiotherapy for patients with breast cancer. Conventional consent procedures are often based on verbal declarations with a highly condensed but nevertheless large amount of information, which can exceed [...] Read more.
Background/Objectives: Informed consent is crucial in medical practice, especially for complex treatments such as postoperative radiotherapy for patients with breast cancer. Conventional consent procedures are often based on verbal declarations with a highly condensed but nevertheless large amount of information, which can exceed the recording capacity of patients and lead to misunderstandings. The aim of this study was to develop and test an educational video on breast cancer patients to enhance the informed consent process by improving patients’ understanding and reducing the duration of the subsequent consultation. Methods: The educational video was created after the underlying content was determined by a modified Delphi method in which a panellist of radiation oncologists, nurses, radiation therapists, and former patients participated in successive rounds of topic scoring. After achieving content consent, the video included 19 items to cover key aspects of postoperative radiotherapy in a patient-friendly manner. Fifty breast cancer patients scheduled for postoperative radiotherapy were randomised to watch the video prior to their verbal consultation (n = 25) or to the control group participating in the traditional informed consent process only (n = 25). The duration of the informed consent processes in both arms was recorded. To assess the educational effect of the video, a multiple-choice test was created. In addition, patients’ satisfaction was recorded using a separate questionnaire. Both questionnaires were completed by the patients one to two hours after signing the consent form. Results: The patients in the video group evidenced significantly higher knowledge scores than those who received standard verbal explanations (median number of correct answers 9 vs. 8 out of 10, p = 0.0039). The whole informed consent process was also completed faster in the video group (mean duration 34.7 vs. 46.2 min, p < 0.001). Median satisfaction scores were high in both groups (34 vs. 33 out of 35 points), with no significant differences observed (p > 0.05). Conclusion: The educational video effectively improved patient understanding and streamlined the informed consent process without compromising patients’ satisfaction. This approach also helps to standardise the delivery of complex medical information, and it can also be adapted to improve the informed consent process for other cancer treatments. Full article
(This article belongs to the Special Issue Digital Health Technologies in Oncology)
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10 pages, 1302 KiB  
Article
Internet Access and Use by Patients with Gynecologic Malignancies: A Cross-Sectional Study
by Frederik Bach, David Engelhardt, Christoph A. Mallmann, Sina Tamir, Lars Schröder, Christian M. Domröse and Michael R. Mallmann
Cancers 2024, 16(9), 1677; https://doi.org/10.3390/cancers16091677 - 26 Apr 2024
Cited by 1 | Viewed by 1142
Abstract
The influence of digitalization on information-seeking, decision-making properties of patients, therapy monitoring, and patient–physician interactions has and will change the global health sector tremendously. With this study, we add knowledge on the degree of digitalization, digital device availability, the use and availability of [...] Read more.
The influence of digitalization on information-seeking, decision-making properties of patients, therapy monitoring, and patient–physician interactions has and will change the global health sector tremendously. With this study, we add knowledge on the degree of digitalization, digital device availability, the use and availability of home and mobile internet access, and the willingness to use novel forms of patient–physician interactions in a group of gynecologic cancer patients. From July 2017 to March 2022, 150 women with a diagnosis of gynecologic malignancy at the University Hospital of Cologne participated in this questionnaire-based cohort study. Any one of three potential internet access devices (stationary computer, smartphone, or tablet) is owned by 94% of patients and the only patient intrinsic factor that is significantly associated with the property of any one of these internet access devices is age. The Internet is used daily or several times per week to assess information on their disease by 92.8%, 90.1% use the Internet for communicational purposes and 71.9% and 93.6% are willing to communicate with their treating physicians via E-Mail or even novel forms of communication, respectively. In conclusion, the predominant majority of gynecologic cancer patients can be reached by modern internet-based E-Health technologies. Full article
(This article belongs to the Special Issue Digital Health Technologies in Oncology)
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Review

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27 pages, 1560 KiB  
Review
Advancing Precision Oncology with Digital and Virtual Twins: A Scoping Review
by Sebastian Aurelian Ștefănigă, Ariana Anamaria Cordoș, Todor Ivascu, Catalin Vladut Ionut Feier, Călin Muntean, Ciprian Viorel Stupinean, Tudor Călinici, Maria Aluaș and Sorana D. Bolboacă
Cancers 2024, 16(22), 3817; https://doi.org/10.3390/cancers16223817 - 13 Nov 2024
Cited by 1 | Viewed by 2082
Abstract
Digital twins (DTHs) and virtual twins (VTHs) in healthcare represent emerging technologies towards precision medicine, providing opportunities for patient-centric healthcare. Our scoping review aimed to map the current DTH and VTH technologies in oncology, summarize their technical solutions, and assess their credibility. A [...] Read more.
Digital twins (DTHs) and virtual twins (VTHs) in healthcare represent emerging technologies towards precision medicine, providing opportunities for patient-centric healthcare. Our scoping review aimed to map the current DTH and VTH technologies in oncology, summarize their technical solutions, and assess their credibility. A systematic search was conducted in the main bibliographic databases, identifying 441 records, of which 30 were included. The studies covered a wide range of cancers, including breast, lung, colorectal, and gastrointestinal malignancies, with DTH and VTH applications focusing on diagnosis, therapy, and monitoring. The results revealed heterogeneity in targeted topics, technical approaches, and outcomes. Most twining solutions use synthetic or limited real-world data, raising concerns regarding their reliability. Few studies have integrated real-time data and machine learning for predictive modeling. Technical challenges include data integration, scalability, and ethical considerations, such as data privacy and security. Moreover, the evidence lacks sufficient clinical validation, with only partial credibility in most cases. Our findings underscore the need for multidisciplinary collaboration among end-users and developers to address the technical and ethical challenges of DTH and VTH systems. Although promising for the future of personalized oncology, substantial steps are required to move beyond experimental frameworks and to achieve clinical implementation. Full article
(This article belongs to the Special Issue Digital Health Technologies in Oncology)
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