Enhancing Healthcare Accessibility with Cloud Computing: Bridging the Gap for a Healthier Future In an era where technology shapes nearly every facet of our lives, healthcare stands as a critical domain ripe for transformation. One of the most significant challenges facing healthcare systems g...

Enhancing Healthcare Accessibility with Cloud Computing: Bridging the Gap for a Healthier Future
www.ekascloud.com/our-blog/enh...
#CloudComputing #HealthcareInnovation #DigitalHealth #HealthTech #Telemedicine #CloudInHealthcare #FutureOfHealthcare #AIinHealthcare #DataDrivenCare

Predictors of Engagement with a Dietary #DigitalHealth Intervention: A Large-Scale, Real-World Observational #Study Date Submitted: Apr 10, 2026. Open Peer Review Period: Apr 10, 2026 - Jun 5, 2026.

Reminder>> Predictors of Engagement with a Dietary #DigitalHealth Intervention: A Large-Scale, Real-World Observational #Study (preprint) #openscience #PeerReviewMe #PlanP

Application of the Technology Acceptance Model to Predict Nursing Students’ Intention to Use Informatics: Cross-Sectional Study Background: Nursing informatics is essential for digital health transformation; however, the technology acceptance of undergraduate #nursing students in Saudi Arabia remains underexplored. Objective: This study examined factors influencing #nursing students’ intention to use informatics technologies using the technology acceptance model. Methods: A cross-sectional survey was conducted with 132 undergraduate #nursing students. Data were analyzed using descriptive, correlational, and hierarchical regression analyses. Results: Perceived usefulness (mean 3.68, SD 1.22) and perceived ease of use (mean 3.64, SD 1.32) were the strongest predictors of acceptance, together explaining 87% of the variance (²=0.87; =0.323 for usefulness,

New in JMIR Nursing: Application of the Technology Acceptance Model to Predict Nursing Students’ Intention to Use Informatics: Cross-Sectional Study #NursingInformatics #DigitalHealth #HealthTech #NursingStudents #TechnologyAcceptance

AI-powered heart diagnostics expand into Vietnam, bringing faster, more accessible cardiac screening beyond hospital walls.
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#longevity #ai #healthspan #cardiology #digitalhealth

Charité und LMU – wie Kliniken eigene KI-Institute aufbauen Die rasante Entwicklung der Künstlichen Intelligenz hat dazu geführt, dass Krankenhäuser zentrale Stellen für ihre KI-Kompetenzen schaffen. Anwendungen sollen so schneller in die Versorgung gebracht...

"Charité und LMU – wie Kliniken KI systematisch integrieren" — German university hospitals expand AI institutes to connect research, improve workflows, and bring innovations faster into patient care. #AI #Healthcare #DigitalHealth #Germany

Every patient visit starts with intake and patients feel it when that process is broken.

This new 2026 guide breaks down what intake really is, where traditional workflows go wrong..
👉 Read more: buff.ly/cjqpVkm

#PatientIntake #PatientExperience #HealthcareAutomation #DigitalHealth

Co-Design of a Depression Self-Management Tool for Adolescent and Young Adult #Cancer Survivors: Rapid Qualitative Analysis of Interview Feedback on a Prototype Background: Over 2.1 million adolescent and young adult #Cancer survivors (AYACS) live in the United States. Recent estimates suggest that up to one-third of AYACS experience major depressive disorder. Although several efficacious evidence-based interventions are available to manage symptoms of depression, these interventions are often inaccessible to AYACS who have many competing commitments. Digital mental health tools hold promise for this population; however, only a few have been tailored to meet the unique needs of AYACS, and findings to date have yielded mixed results. Objective: This study aims to obtain feedback from AYACS on a mid-fidelity prototype of a depression self-management tool being tailored for AYACS. Methods: Individuals with a history of #Cancer diagnosed at age 12 or older who were between the ages of 15 and 39 and had completed primary treatment were identified through a review of medical records from a comprehensive #Cancer center in the Southeastern United States. Potentially eligible participants were contacted by study staff to conduct additional screening and obtain informed consent via REDCap (Research Electronic Data Capture; Vanderbilt University). Upon enrollment, participants provided demographic and clinical information, as well as their availability for an interview. The principal investigator (KMI) conducted semistructured individual interviews with consented AYACS. Most of the interview was dedicated to showing participants the mid-fidelity prototype of the tool, explaining how the prototype might work, and requesting targeted feedback. Demographic and clinical characteristics, as well as some aspects of feedback on the prototype, were summarized using descriptive statistics. Interviews were audio- and video-recorded and transcribed. The transcriptions underwent rapid qualitative analysis guided by the Rigorous and Accelerated Data Reduction technique. Results: A total of 14 AYACS (n=9, 64%, female; n=9, 64%, white; ages 15-38) completed an individual interview. Participant preferences for mood tracking, content presentation, user input, and duration of use were captured qualitatively but analyzed quantitatively. For example, most participants (n=10, 71%) indicated that they preferred a mood-tracking option that included emojis and would be willing to track their mood at least once per day (n=11, 79%). Participant preferences captured qualitatively fell into 4 themes: (1) features to promote user engagement (eg, the use of gamification); (2) tailored content presentation (eg, authenticity in the portrayal of the #Cancer experience); (3) perceived #usability (eg, simplifying user input); and (4) interface design (eg, implementing a coherent design theme and color scheme). Conclusions: Findings indicated that AYACS highly value personalization, flexibility, and peer support in digital interventions. Based on insights obtained during individual interviews, a working prototype was developed by reprogramming an existing digital tool. Qualitative and quantitative findings informed modifications to the existing digital tool. The working prototype will next undergo evaluation as part of a pilot full-factorial trial.

JMIR Formative Res: Co-Design of a Depression Self-Management Tool for Adolescent and Young Adult #Cancer Survivors: Rapid Qualitative Analysis of Interview Feedback on a Prototype #MentalHealth #Depression #CancerSurvivors #AYACancer #DigitalHealth

Original post on social.heise.de

Interview: Puraite will Evidenzsynthese mit erklärbarer KI beschleunigen

Puraite will die manuelle Literaturrecherche in den Lebenswissenschaften mit erklärbarer KI deutlich verkürzen. Über die Pläne des Start-ups […]

Submit your abstract for AI in Medicine Conference (AIIM 2026)

May 04–05, 2026 | Boston, USA
Showcase your research to a global audience in AI-driven healthcare.

🔗 ai-medicalcongress.com/abstract-sub...

#AIIM2026 #AIinMedicine #HealthcareAI #MedicalImaging #DigitalHealth

Can AI decode cognitive states from EEG?🧠🤖

Using our #Enobio, researchers achieved up to 93% accuracy in classifying attention, interest, and mental effort with hybrid deep learning models.

Full study: www.researchgate.net/publication/...
#EEG #AI #DeepLearning #DataScience #BCI #DigitalHealth

London-based digital health and engagement platform JAAQ has raised £12.8mn to accelerate its entry into the US market and fast-track the development of its AI-native mental health content library.

healthcaretoday.com/article/jaaq...

#Healthcare #MentalHealth #DigitalHealth #Acquisition

In the first of a two-part interview, Amanda Randles, director of the Duke University Center for Computational and Digital Health Innovation, explains why duration matters.

healthcaretoday.com/article/aman...

#Healthcare #DigitalTwins #DigitalHealth #PatientSafety

Hard truth: Hardware logistics are the silent killer of RPM profit margins. 📉 RE.DOCTOR Vitals flips the script. Lower overhead (no shipping/refurbishing) Faster scaling Higher patient retention Boost your platform's ROI while delivering elite care. 🏥✨ Do the math: https://re.doctor #HealthBiz #ROI #DigitalHealth #MedTechStartup #Efficiency

Hard truth: Hardware logistics are the silent killer of RPM profit margins. 📉

RE.DOCTOR Vitals flips the script.

Lower overhead (no shipping/refurbishing)
Higher patient retention
Boost your platform's ROI while delivering elite care. 🏥✨

Do math: https://re.doctor

#HealthBiz #DigitalHealth

Moving Care Beyond the Clinic Walls with RPM The shift toward value-based care is accelerating the adoption of Remote Patient Monitoring (RPM). By leveraging real-time data, providers can monitor chronic conditions more effectively, reduce hospital readmissions, and intervene before a crisis occurs. However, the success of an RPM program depends on more than just the devices. It requires seamless integration into the Electronic Health Record (EHR) and a clear workflow for data analysis. We provide the technical expertise to ensure your remote care solutions are both effective and sustainable. Discover how to optimize your RPM strategy: https://healthitconsult.com/ #RPM #RemotePatientMonitoring #Telehealth #DigitalHealth #ValueBasedCare #HealthIT

Moving Care Beyond the Clinic Walls with RPM

The shift toward value-based care is accelerating the adoption of Remote Patient Monitoring (RPM).

Discover how to optimize your RPM strategy: healthitconsult.com

#RPM #RemotePatientMonitoring #Telehealth #DigitalHealth #ValueBasedCare #HealthIT

Is Your Digital Health Roadmap Built for Scalability? Digital transformation in healthcare is no longer just about adopting new software; it is about creating a cohesive ecosystem that improves patient outcomes and operational efficiency. Many organizations face the challenge of fragmented systems that don't communicate, leading to data silos and clinician burnout. At Health IT Consult, we specialize in bridging the gap between complex technology and clinical workflows. A successful strategy requires a deep dive into your current infrastructure to identify bottlenecks and implement scalable solutions that grow with your practice. Ready to modernize your healthcare delivery? Let’s build a roadmap that works. Read more: https://healthitconsult.com/ #HealthIT #DigitalHealth #HealthcareInnovation #DigitalTransformation #HealthTech

Is Your Digital Health Roadmap Built for Scalability?

Ready to modernize your healthcare delivery? Let’s build a roadmap that works.

Read more: healthitconsult.com
#HealthIT #DigitalHealth #HealthcareInnovation #DigitalTransformation #HealthTech

Beyond the Sleep Lab Webinar: Wearables, the Present and the Future of Sleep Research 14 April 2026 16:00–17:00 CEST Featuring: Dr. Yue Leng (Speaker) Dr. Kiran Ravindran (Speaker) Dr. Stijn Massar (Panelist) Moderated by Dr. Laura Stankeviciute

🔬💤 Beyond the Sleep Lab: Wearables, the Present and the Future of Sleep Research

Join the ESRS Early Career Network for an engaging webinar TOMORROW!

👉 Register now and be part of the discussion! esrs.eu/e-sleep/webi...

#SleepResearch #Wearables #DigitalHealth #EarlyCareerResearchers #ESRS

#Health system- and payer-level decision-making processes influencing the adoption and sustainability of #Patient-facing #DigitalHealth tools Date Submitted: Apr 8, 2026. Open Peer Review Period: Apr 9, 2026 - Jun 4, 2026.

Reminder>> #Health system- and payer-level decision-making processes influencing the adoption and sustainability of #Patient-facing #DigitalHealth tools (preprint) #openscience #PeerReviewMe #PlanP

Original post on social.heise.de

Montag: 2-Nanometer-Chips aus Japan, Apples verschiedene Smartglasses-Designs

Rapidus-Förderung Japans + Designs neuer Apple-Brillen + Händler-Kritik an DSGVO + Stand heutiger LED-Birnen + Rückblick auf Datennetz + Digital-Health-Podcast […]

Original post on social.heise.de

Digital-Health-Podcast: Mehr Tempo bei Daten und KI – aber zu welchem Preis?

Mehr Daten, mehr KI, mehr Tempo: Der Druck im Gesundheitswesen wächst, Digitalisierung soll es richten. Doch unter welchen Bedingungen? […]

Digital Health 2026 & Beyond: From Predictive AI to Hyper-Personalized Medicine In 2026, your morning health scan won't be in a doctor's office—it'll happen while you brush your teeth. Subscribe Zeeglobalvision Youtube For More.

And it’s already here 👇
www.zeeglobalvision.com/2026/01/digi...

#DigitalHealth #Healthcare #AI #Innovation #Future

Healthcare is evolving fast.

🏥 AI + Telemedicine + Wearables

That’s the future.

And it’s already here 👇
www.zeeglobalvision.com/2026/01/digi...

#DigitalHealth #Healthcare #AI #Innovation #Future

DiGA-report.de - market dashboard Interactive DiGA market analysis dashboard with data from GKV-Spitzenverband and SVDGV reports.

"DiGA Report" provides an overview of annual analyses on Germany’s digital health applications market, covering prescriptions, activations, revenue, and trends. diga-report.de #DiGA #DigitalHealth #HealthcareData #Germany

"Beyond human ears: navigating the uncharted risks of AI scribes in clinical practice" examines benefits and risks of AI documentation tools, highlighting concerns about accuracy, bias, transparency, and regulation. #AI #PatientSafety #DigitalHealth

Public comfort with AI in health care falls, Ohio State survey finds Artificial intelligence seems to be everywhere – on our jobs, in our homes and at the doctor’s office. While the use of AI grows, a new survey commissioned by The Ohio State University Wexner Medical...

Ohio State survey shows declining trust in #AI in #healthcare (42% in 2026 vs. 52% in 2024), yet 51% still use it for key decisions without doctors. Highlights risks and role of AI as support tool. wexnermedical.osu.edu/mediaroom/pr... #DigitalHealth

Genelife Perspective of Best Practices in Study Management At Genelife, Our approach is designed to ensure that every clinical trial is conducted with precision, integrity, and measurable value.

#clinicalresearch #ClinicalTrials #pharma #biotech #healthcare #CRO #GCP #ichguidelines #decentralizedtrials
#digitalhealth #InnovationInHealthcare #RiskBasedMonitoring
#patientcentricity #GeneLife #genelife
genelifecr.blogspot.com/2026/04/gene...

Read full article brief on : Encodedemotion.org

I’m obsessing over why high-stakes experts might be rejecting 'perfect AI', and I don't think it's because they are tech-phobic.

#SurgicalMedicine #Surgery #ArtificialIntelligence #Surgeon #AcademicSky #Technology #MedicalAI #DigitalHealth

Just how bad are generative AI chatbots for our mental health? | The-14 Study finds AI chatbots may affect mental health, but media often exaggerates risks. Experts call for better evidence, safeguards, and responsible use.

Just how bad are generative AI chatbots for our mental health?
#AI #ArtificialIntelligence #Tech #MentalHealth #Chatbots #Media #TechEthics #DigitalHealth #Teens #Psychology #AIrisks #Suicide #SocialMedia #Innovation #AIethics #PublicHealth #Psychosis
the-14.com/just-how-bad...

Balancing innovation and risk: AI's expanding role in NHS patient safety (30 March 2026) Forgot your password?

Balancing innovation and risk: AI's expanding role in NHS patient safety - a blog from Public Policy Projects available via the hub. www.pslhub.org/learn/digita... #AI #patientsafety #digitalhealth

Predictors of Engagement with a Dietary #DigitalHealth Intervention: A Large-Scale, Real-World Observational #Study Date Submitted: Apr 10, 2026. Open Peer Review Period: Apr 10, 2026 - Jun 5, 2026.

Predictors of Engagement with a Dietary #DigitalHealth Intervention: A Large-Scale, Real-World Observational #Study (preprint) #openscience #PeerReviewMe #PlanP

Facilitators and Barriers to Digital Self-Management in Older Adults With Depression: COM-B and Theoretical Domain Framework Qualitative Study Background: Depression in older adults presents unique challenges in self-management. Digital tools, such as mobile health (mHealth) apps, have the potential to support this population. This study explored the facilitators and barriers to digital self-management in older adults with depression to inform the design of effective mHealth apps. Objective: This study aims to explore the facilitators and barriers to digital self-management in older patients with depression with the aim of informing the design and development of mHealth apps for older adults. Methods: A purposive sampling method was used to recruit 25 older patients with depression from July to September 2024. Semistructured interviews were conducted to capture real-life experiences. Directed content analysis ensured objective and accurate data interpretation, and the Capability, Opportunity, Motivation, and Behavior (COM-B) model and the Theoretical Domains Framework were applied to identify facilitators and barriers related to behavior. Results: Six themes were identified based on the COM-B model and the Theoretical Domains Framework: perception of illness and accumulation of personal experience; dual challenges of cognitive abilities and physical limitations; integration of digital technologies and acceptance differences; social influences and access to and utilization of support resources; environmental constraints and accommodations; and intertwined influences of beliefs, emotions, and motivation. A total of 13 barriers and 11 facilitators were identified. Conclusions: Digital self-management in older adults with depression is complex and influenced by multiple interrelated factors. Effective mHealth apps must integrate the cognitive, emotional, and social contexts of patients to provide user-friendly, personalized solutions.

New in JMIR Aging: Facilitators and Barriers to Digital Self-Management in Older Adults With Depression: COM-B and Theoretical Domain Framework Qualitative Study #MentalHealth #OlderAdults #Depression #SelfManagement #DigitalHealth