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Hot Topics of the Day are picked by experts to capture the latest information and publications on public health genomics and precision health for various diseases and health topics. Sources include published scientific literature, reviews, blogs and popular press articles.

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43 hot topic(s) found with the query "Digital health"

Automatic, wearable-based, in-field eating detection approaches for public health research: a scoping review
BM Bell, NPJ Digital Health, March 13, 2020 (Posted: Mar-14-2020 6AM)

This scoping review highlights the current state of wearable sensors’ ability to improve upon traditional eating assessment methods by passively detecting eating activity in naturalistic settings, over long periods of time, and with minimal user interaction.


Smartphone screening for neonatal jaundice via ambient-subtracted sclera chromaticity
F Outlaw et al, PLOS One, March 2020 (Posted: Mar-05-2020 8AM)


Leveraging the health information technology infrastructure to advance federal research priorities.
Zayas-Cabán Teresa et al. Journal of the American Medical Informatics Association : JAMIA 2020 Feb (Posted: Feb-27-2020 8AM)

Use of health information technology (IT) by U.S. healthcare providers and patient access to electronic health data have increased significantly in the past decade.1–5 This has been facilitated by technological changes in information system capabilities and infrastructure,6–9 as well as legislation, governmental programs, and policies.


Our phones can now detect health problems from Parkinson’s to depression. Is that a good thing?
L Parshley, VOX, February 2020 (Posted: Feb-21-2020 9AM)


Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants
A Pratap et al, NPJ Digital Health, February 17, 2020 (Posted: Feb-18-2020 9AM)

We report the findings regarding recruitment and retention from eight remote digital health studies conducted between 2014–2019 that provided individual-level study-app usage data from more than 100,000 participants completing nearly 3.5 million remote health evaluations.


CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in stage I, II resectable non-small cell lung cancer: a retrospective multicohort study for outcome prediction
P Vaidya et al, Lancet Digital Health, February 13, 2020 (Posted: Feb-14-2020 8AM)


Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study
HE Kim et al, Lancet Digital Health, February 6, 2020 (Posted: Feb-08-2020 9AM)

An artificial intelligence (AI) algorithm developed with large-scale mammography data showed better diagnostic performance in breast cancer detection compared with radiologists. The significant improvement in radiologists' performance when aided by AI supports application of AI to mammograms as a diagnostic support tool.


Innovation without integration
AB Cohen et al, NPJ Digital Medicine, February 3, 2020 (Posted: Feb-04-2020 9AM)

We believe prevention-focused digital health technologies are currently most able to avoid integration with the existing healthcare system. This is in line with digital health trends we observe, whereby prevention products directly appeal to consumers outside their normal experience within the healthcare system.


Beyond validation: getting health apps into clinical practice
WJ Gordon et al, NPJ DIiital Medicine, February 3, 2020 (Posted: Feb-04-2020 9AM)

We propose a framework for prescribing apps and outline the key issues that need to be addressed to enable app dissemination in clinical care. This includes: education and awareness, creating digital formularies, workflow and EHR integration, payment models, and patient/provider support.


Responses to addiction help-seeking from Alexa, Siri, Google Assistant, Cortana, and Bixby intelligent virtual assistants
AL Nobles et al, NPJ Digital Medicine January 29, 2020 (Posted: Jan-30-2020 9AM)

Intelligent virtual assistants (IVA), such as Apple’s Siri, are transforming how the public seeks and finds information.1 IVAs are interfaces that enable users to interact with smart devices using spoken language in a natural way and provide a singular response to a query similar to speaking to a person


The dark side of digital health
I Kickbusch, BMJ, January 2020 (Posted: Jan-20-2020 8AM)

Fascinated as we are by digital gadgets and promises, we do not look deeply enough at the radical impact of the digital transformation on our health and life. Increasingly social scientists warn of a new phase of the organisation of health and medical knowledge which will be tailored to data extraction and will allow for a new structure of power over individuals.


Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study
JM Radin et al, Lancet Digital HEalth, January 16, 2020 (Posted: Jan-17-2020 8AM)

Activity and physiological trackers are increasingly used in the USA and globally to monitor individual health. By accessing these data, it could be possible to improve real-time and geographically refined influenza surveillance. This information could be vital for outbreak response measures.


What is the clinical value of mHealth for patients?
SP Rowland et al, NPJ Digital Medicine, January 13, 2020 (Posted: Jan-14-2020 8AM)

The study categorizes apps according to their functionality (e.g. preventative behavior change, digital self-management of a specific condition, diagnostic) and discusses evidence for effectiveness from published systematic reviews and meta-analyses and the relevance to patient care.


Genetic apps: raising more questions than they answer?
T Burki, January 1, 2020 Lancet Digital Health (Posted: Jan-06-2020 9AM)


Use of mobile health apps in low-income populations: a prospective study of facilitators and barriers
P Liu et al, MedRXIV, December 29, 2019 (Posted: Dec-29-2019 8AM)

Mobile applications (apps) are increasingly popular in healthcare. For low-income populations, barriers exist, yet limited data are available about the challenges and catalysts for adoption. The assistance of a CHW facilitated the enrollment of low-income individuals in a mobile health app by fostering trust and sustained engagement.


Desiderata for delivering NLP to accelerate healthcare AI advancement and a Mayo Clinic NLP-as-a-service implementation
A Wen et al, NPJ Digital Medicine, December 2019 (Posted: Dec-19-2019 9AM)


Why digital health has been such a disappointment, and how to change that
N Khoshla, CNBC, December 15, 2019 (Posted: Dec-16-2019 7AM)

But almost a decade in, what material change can we point to in health care costs or the experience of the average patient? Are there companies that qualify as major disruptors? To me, the answer is no. And I call this "the Digital Health Conundrum."


Digital clinical trials: creating a vision for the future
SR Steinhubl et al, NPJ Digital Medicine, December 12, 2019 (Posted: Dec-13-2019 9AM)

Digital technologies have transformed every aspect of our lives including the way we communicate, shop, and read. Digital health technologies, despite their reputation for over-promising and under-delivering, can potentially offer the solutions needed to transform clinical trial. However, this cannot be accomplished by replicating the current research processes.


Standalone smartphone apps for mental health—a systematic review and meta-analysis
KK Weisel et al, NPJ DIgital Medicine, December 2, 2019 (Posted: Dec-03-2019 8AM)

Although some trials showed potential of apps targeting mental health symptoms, using smartphone apps as standalone psychological interventions cannot be recommended based on the current level of evidence.


AI-augmented multidisciplinary teams: hype or hope?
A di Leva, The Lancet Digital Health, November 2019 (Posted: Nov-21-2019 7AM)


Reporting on deep learning algorithms in health care
M Yu et al, Lancet Digital Health, November 2019 (Posted: Nov-17-2019 7AM)

This paper discusses considerations and recommendations that might be useful to better assess the quality and potential utility of deep learning algorithms for both continuous (eg, blood pressure and weight) and binary (eg, disease vs no disease) health outcomes.


Can skin cancer diagnosis be transformed by AI?
A Esteva et al, Lancet Digital Health, November 2019 (Posted: Nov-15-2019 7AM)

Dermatology is a specialty suited for artificial intelligence (AI) research and potential incorporation in clinical practice. AI has the potential to decrease dermatologist workloads, eliminate repetitive and routine tasks, and improve access to dermatological care.


A roadmap for familial hypercholesterolemia control
AC Pereira, The Lancet Digital Health, October 2019 (Posted: Nov-04-2019 8AM)

In an era of personalized medicine, familial hypercholesterolemia is potentially one of the most tractable conditions to deliver the promised society-wide benefits of the implementation of this paradigm. Controlling the disease, however, requires a multipronged approach and the orchestrated participation of several different stakeholders.


Precision screening for familial hypercholesterolaemia: a machine learning study applied to electronic health encounter data
K Myers, Lancet Digital Health, October 21, 2019 (Posted: Oct-21-2019 10AM)

The FIND FH model successfully scans large, diverse, and disparate health-care encounter databases to identify individuals with familial hypercholesterolemia. Using a machine learning model,we flagged 1?331?759 of 170?416?201 patients in the national database and 866 of 173?733 individuals in the health-care delivery system dataset as likely to have FH.


Technology approaches to digital health literacy.
Dunn Patrick et al. International journal of cardiology 2019 Oct 294-296 (Posted: Oct-15-2019 8AM)

Digital health literacy is an extension of health literacy and uses the same operational definition. Technology solutions have the potential to promote health literacy. Technology solutions should go beyond building literacy and numeracy skills to functional and critical skills, such as navigating the healthcare system, communication and shared decision making.


Wearable technology and lifestyle management: the fight against obesity and diabetes
The Lancet Digital Health, Vol 1, Iss 6, Pe 243, October 1, 2019 (Posted: Oct-11-2019 0PM)


An awakening in medicine: the partnership of humanity and intelligent machines
LA Celi et al, Lancet Digital Health, September 27, 2019 (Posted: Sep-28-2019 8AM)

"The guidance of AI methods requires more precise definitions: eg, what is normal, what abnormalities require clinical intervention, what outcomes are we trying to achieve, and what costs are acceptable to do so?"


Digital health: From clinical trials to diagnosis and surgery, artificial intelligence has the potential to transform medicine.
R Hodson, Nature Outlook, September 25, 2019 (Posted: Sep-27-2019 10AM)

In the past decade, the use of artificial intelligence (AI) has grown to the point where there are now few areas of our lives that it does not touch. The potential of digital transformation is particularly far-reaching in medicine.


Human versus machine in medicine: can scientific literature answer the question?
TS Cook, Lancet Digital Health, September 24, 2019 (Posted: Sep-25-2019 9AM)

Can AI developed and trained in silico effectively be compared with the human physician functioning in the real world, where data are messy, elusive, and imperfect? Only a handful of studies evaluate the performance of AI models in the presence of a-priori knowledge about the patient.


Practical guidance on artificial intelligence for health-care data
M Ghassemi et al, Lancet Digital Health (Posted: Aug-19-2019 1PM)

AI models are often powered by clinical data that are generated and managed via the medical system, for which the primary purpose of data collection is to support care, rather than facilitate subsequent analysis. Thus, the direct application of AI approaches to health care is associated with both challenges and opportunities.


The “All of Us” Research Program
All of Us, NEJM, August 14, 2019 (Posted: Aug-15-2019 8AM)

The program enrolls participants 18 years of age or older from a network of more than 340 sites. The protocol includes health questionnaires, electronic health records, physical measurements, the use of digital health technology, and the collection of biospecimens. As of July 2019, >175,000 participants had contributed biospecimens.


Capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions
JN Borger et al, NPJ Digital Medicine (Posted: Jul-29-2019 1PM)

This study suggests that touchscreen interactions are widely integrated into modern sleeping habits—surrounding both sleep onset and waking-up periods—yielding a new approach to measuring sleep. Smartphone interactions can be leveraged to update the behavioral signatures of sleep with these peculiarities of modern digital behavior.


Smartphone-Based Detection of Middle Ear Fluid
Abbasi J. JAMA. 2019;322(2):107 (Posted: Jul-12-2019 1PM)


Leveraging Digital Health and Machine Learning Toward Reducing SuicideĀ—From Panacea to Practical Tool
J Torous et al, JAMA Psychiatry, July 10, 2019 (Posted: Jul-11-2019 8AM)

Because the rates of suicide attempts and deaths have recently increased to 50-year highs,1 new solutions are needed. The urgency to reverse this trend has brought attention to technology-based tools, such as text messaging, smartphone apps, smartphone sensors, electronic health records, and machine-learning algorithms.


Technology-Enabled Outreach to Patients Taking High-Risk Medications Reduces a Quality Gap in Completion of Clinical Laboratory Testing.
Raebel Marsha A et al. Population health management 2019 May (Posted: Jul-01-2019 1PM)

Technology-enabled outreach reminding patients to obtain laboratory testing can improve health care system outcomes: A case study of >3760 ambulatory adults taking antirheumatic agents who were due/overdue for laboratory testing.


Walking the tightrope of artificial intelligence guidelines in clinical practice
Lancet Digital Health editorial, July 2019 (Posted: Jun-29-2019 5PM)

Artificial Intelligence approaches in medical practice needs to be lawful, ethical, and robust. According to the EU guidelines for trustworthy AI, there are seven key requirements for ethical AI: human agency and oversight; technical robustness and safety; privacy and data governance; transparency; diversity, non-discrimination, and fairness; societal and environmental wellbeing; and accountability


Digital Medicine: Digital Health, Plus Evidence, Plus Humility
D Shaywitz, Forbes, May 18, 2019 (Posted: May-21-2019 11AM)


A Contrarian View of Digital Health
J Mandrola, Quillette, May 17, 2019 (Posted: May-20-2019 8AM)


Digital health: a path to validation
SC Matthews et al, Nature NPJ Digital Medicine, May 13, 2019 (Posted: May-13-2019 1PM)


Healthcare technology: Seven trends that may shape the future
Digital Health Age, March 26, 2019 (Posted: Mar-28-2019 8AM)


The Alluring Mirage Of Digital Health
J Osborne, Forbes, February 18, 2019 (Posted: Feb-19-2019 8AM)


Digital Health: From Science to Application
Keystone Symposium Video, January 30, 2019 (Posted: Jan-31-2019 9AM)


Digital health - a new medical cosmology? The case of 23andMe online genetic testing platform.
Saukko Paula et al. Sociology of health & illness 2018 Nov (8) 1312-1326 (Posted: Nov-25-2018 8AM)



Disclaimer: Articles listed in Hot Topics of the Day are selected by the CDC Office of Public Health Genomics to provide current awareness of the scientific literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the Clips, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.
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