The fourth volume of Innovations in Digital Health, Diagnostics, and Biomarkers (IDDB) marks another milestone in advancing technology and healthcare. The current issue showcases a diverse array of innovative research and reviews, underscoring the journal's commitment to exploring the intersection of digital health, diagnostic innovation, and biomarker discovery. The studies highlight significant advancements and ongoing challenges in this rapidly evolving field, from artificial intelligence (AI) and machine learning (ML) applications to crowdsourcing and biobanking initiatives. Key contributions and their relevance to the journal's scope are outlined as follows.

The editorial by Karine Sargsyan[1] discussed the significant transformative impact of AI and ML on healthcare, including how these technologies are reshaping patient care, expediting drug discovery, and advancing biomedical research. Key applications include disease diagnosis and prognosis, laboratory medicine, drug discovery and development, precision medicine, virtual health assistants, predictive analytics for preventive care, robotics in surgery, and continuous monitoring for chronic disease management. Sargsyan[1] advocates for a collaborative effort among stakeholders to further explore and expand the potential of digital biomedicine, aiming for improved health outcomes in the future.

The application of an AI subfield, deep learning, was thoroughly explored in the review by Muhammed Yaman Swied et al,[2] which investigated the diagnosis of gastrointestinal diseases. Given the nonspecific nature of these conditions, radiologic imaging plays a crucial role in diagnosis. Findings illustrated that AI-based radiologic imaging can improve diagnostic efficiency, reduce interpretation errors, and optimize the imaging workflow. Data quality, clinical integration, and ethical considerations remain key challenges that might hinder the broader adoption of such tools in clinical practice.[2] Swied et al[3] also explored the groundbreaking advances of AI in the field of endoscopy. Their review identified several applications of AI from recognizing esophageal pathologies to diagnosing Helicobacter pylori infections.[3]

Holley and colleagues[4] published a study on the potential of digital cognitive behavioral therapy to extend, standardize, and complement clinicians’ work beyond the practice. Their retrospective database analysis demonstrated that such approaches hold significant promise in improving access to behavioral healthcare. Their strategy may fill important gaps in the delivery of traditional behavioral healthcare by utilizing digital tools to guarantee more standardized and scalable mental health services.[4] In a related study, a team from NeuroFlow and The Villages Health[5] investigated digital tools to assess mental health issues in communities. The findings demonstrate the utility of remote assessments in identifying at-risk individuals early, offering valuable insights into the prevalence of mental health conditions.[5]

The effectiveness of natural language processing, a branch of computer science that combines ML, statistics, and linguistics to analyze ingested text, was evaluated by NeuroFlow in another retrospective database study that used a digital behavioral health platform to detect suicidal ideation.[6] Conventional techniques, such as Patient Health Questionnaire-9 screenings, often fail to identify at-risk individuals. The platform succeeded in sending crisis support emails to flagged patients within 2 minutes of detection. The authors highlighted the potential of incorporating technology into initiatives to prevent suicide by facilitating prompt, scalable, and tailored interventions.[6]

Okoye et al[7] reviewed the uptake and implementation of digital solutions for medication adherence in major depressive disorder and explored potential barriers to access. The review addressed the critical issue of nonadherence, which exacerbates symptoms and increases the risk of relapse. The review also outlined the most recent data supporting the use of several digital health technologies, including mobile apps, telehealth platforms, wearable devices, tailored and personalized interventions, and online support communities for this patient population. Okoye et al[7] also shed light on the challenges of integrating digital health into practice.

Piduri et al[8] introduced a novel emergency alert system that uses an electroencephalography headset device and brain-computer interface technology. Equipped with Bluetooth functionality and a dedicated software application, patients can use their thoughts to select a predefined command within the app, which is then communicated to others. The authors demonstrated an initial success rate of up to 98%. Such innovations represent a breakthrough for a wide range of individuals with disabilities, offering new avenues for communication.[8] This student-led project was presented at the annual Advancing Healthcare Innovation Summit (AHIS) in 2023. The 2023 conference emphasized the integration of technology, data, and interdisciplinary collaboration as critical drivers of global healthcare.[9] Recorded presentations from AHIS 2023 are available on InnoScholar.com.[10]

Two studies explored Macau's initiatives in establishing its regional biobank. The first study presented the findings of a survey to assess feasibility of establishing a digitally integrated biobank in Macau.[11] Cheong and colleagues[11] identified key determinants that are critical to the success of the biobank’s initiative. Macau’s experience in establishing its first regional biobank was demonstrated in the second paper, a review by the same research team.[12] The authors emphasized the importance of addressing several challenges, including the need for improved biosafety standards, updated regulations, and improved digital technology integration. Despite these challenges, several opportunities exist for regional cooperation, economic diversification, and improvements in healthcare innovation with the planned biobank. Leveraging its strategic location and involving stakeholders, Macau has the potential to play a significant role in regional biomedical research.

Although digital health services have the potential to improve treatment, well-being, and self-management, several structural, technological, and sustainability challenges remain significant obstacles. In the healthcare industry, crowdsourcing has emerged as a useful strategy that facilitates data integration and exchange between hospitals, academic institutions, businesses, and patients. But its full potential is hampered by obstacles like regulatory restrictions and the requirement for international standards and interoperability. The research of Ivanova and colleagues[13] emphasized the importance of secure data transfers, a robust information technology architecture, and adherence to legal and ethical requirements. Although the back-end system ensures the secure management of private data, the user-friendly front end is customized to meet patient needs.

We extend our gratitude to the journal staff for their outstanding efforts and support throughout this fourth year (including their contributions to social media outreach via @EditorsIDDB). We also thank the full editorial board for their unwavering encouragement and scientific guidance, which have been instrumental in the journal's continued progress and success.

1.
Sargsyan
K.
Artificial intelligence and machine learning: technologies revolutionizing the healthcare sector and biomedical research
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Innov Dig Health Diagn Bio
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2024
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4
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50
52
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2.
Swied
MY,
Abou Shaar
B,
Rajab Basha
N.
Exploring the current role of deep learning in radiologic imaging of gastrointestinal diseases
.
Innov Dig Health Diagn Bio
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2024
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4
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68
80
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3.
Swied
MY,
Alom
M,
Daaboul
O,
Swied
A.
Screening and diagnostic advances of artificial intelligence in endoscopy
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Innov Dig Health Diagn Bio
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2024
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4
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31
43
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4.
Holley
D,
Lubkin
S,
Brooks
A,
et al.
Digital CBT interventions predict robust improvements in anxiety and depression symptoms: a retrospective database study
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Innov Dig Health Diagn Bio
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2024
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4
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53
55
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5.
Holley
D,
Brooks
A,
Zaubler
T,
et al.
Remote behavioral health screenings can surface population risk of anxiety and depression: a retrospective database study
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Innov Dig Health Diagn Bio
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2024
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4
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59
61
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6.
Hartz
M,
Hickey
D,
Acosta
L,
et al.
Using natural language processing to detect suicidal ideation and prompt urgent interventions: a retrospective database study
.
Innov Dig Health Diagn Bio
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2024
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4
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6
8
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7.
Okoye
V,
Okoye
G,
Appiah
D.
Harnessing digital health solutions to enhance medication adherence in patients with depression
.
Innov Dig Health Diagn Bio
.
2024
;
4
:
9
14
.
8.
Piduri
N,
Piduri
A,
Haque
A,
et al.
Using brain waves and computer interface technology as a communication system
.
Innov Dig Health Diagn Bio
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2024
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4
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62
67
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9.
Pyne-Geithman
G.
2023 Advancing Healthcare Innovation Summit (AHIS): executive summary
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Innov Dig Health Diagn Bio
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2024
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4
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2
5
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10.
2023 Advancing Healthcare Innovation Summit
. Nov 11,
2023
. Accessed Dec 27, 2024. innoscholar.com/modules/2023-advancing-healthcare-innovation-summit-ahis
11.
Cheong
IH,
Garcia
DL,
Kozlakidis
Z,
et al.
Developing a new, digitally integrated research infrastructure: results of the Macau biobank survey
.
Innov Dig Health Diagn Bio
.
2024
;
4
:
25
30
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12.
Cheong
IH,
Garcia
DL,
Kozlakidis
Z,
et al.
Challenges, rewards, and digital aspects in establishing Macau’s first regional biobank
.
Innov Dig Health Diagn Bio
.
2024
;
4
:
44
49
.
13.
Ivanova
D,
Katsaounis
P,
Votis
K.
Increasing the value of real-world crowdsourcing health data with e-MetaBio, a novel patient-centric IT infrastructure
.
Innov Dig Health Diagn Bio
.
2024
;
4
:
15
24
.

Competing Interests

Source of Support: None. Conflict of Interest: None.

This work is published under a CC-BY-NC-ND 4.0 International License.