[HTML][HTML] The promise of digital health: then, now, and the future

A Abernethy, L Adams, M Barrett, C Bechtel… - NAM …, 2022 - ncbi.nlm.nih.gov
Over the past several decades, the development and accelerated advancement of digital
technology has prompted change across virtually all aspects of human endeavor. The …

Leveraging physiology and artificial intelligence to deliver advancements in health care

A Zhang, Z Wu, E Wu, M Wu, MP Snyder… - Physiological …, 2023 - journals.physiology.org
Artificial intelligence in health care has experienced remarkable innovation and progress in
the last decade. Significant advancements can be attributed to the utilization of artificial …

[HTML][HTML] Medicine 2032: The future of cardiovascular disease prevention with machine learning and digital health technology

A Javaid, F Zghyer, C Kim, EM Spaulding… - American Journal of …, 2022 - Elsevier
Abstract Machine learning (ML) refers to computational algorithms that iteratively improve
their ability to recognize patterns in data. The digitization of our healthcare infrastructure is …

[HTML][HTML] The convergence of traditional and digital biomarkers through AI-assisted biosensing: A new era in translational diagnostics?

SS Arya, SB Dias, HF Jelinek, LJ Hadjileontiadis… - Biosensors and …, 2023 - Elsevier
Advances in consumer electronics, alongside the fields of microfluidics and nanotechnology
have brought to the fore low-cost wearable/portable smart devices. Although numerous …

The 2023 wearable photoplethysmography roadmap

PH Charlton, J Allen, R Bailón, S Baker… - Physiological …, 2023 - iopscience.iop.org
Photoplethysmography is a key sensing technology which is used in wearable devices such
as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to …

Assessing hemodynamics from the photoplethysmogram to gain insights into vascular age: a review from VascAgeNet

PH Charlton, B Paliakaitė, K Pilt… - American Journal …, 2022 - journals.physiology.org
The photoplethysmogram (PPG) signal is widely measured by clinical and consumer
devices, and it is emerging as a potential tool for assessing vascular age. The shape and …

Glucose metabolism-inspired catalytic patches for NIR-II phototherapy of diabetic wound infection

J Shan, X Zhang, Y Cheng, C Song, G Chen, Z Gu… - Acta Biomaterialia, 2023 - Elsevier
Medical patches hold great prospects for diabetic wound administration, while their practical
effects in diabetic wound management remain mired by the complexity of wound …

[HTML][HTML] FLIRT: A feature generation toolkit for wearable data

S Föll, M Maritsch, F Spinola, V Mishra, F Barata… - Computer Methods and …, 2021 - Elsevier
Abstract Background and Objective: Researchers use wearable sensing data and machine
learning (ML) models to predict various health and behavioral outcomes. However, sensor …

Dermal features derived from optoacoustic tomograms via machine learning correlate microangiopathy phenotypes with diabetes stage

A Karlas, N Katsouli, NA Fasoula, M Bariotakis… - Nature Biomedical …, 2023 - nature.com
Skin microangiopathy has been associated with diabetes. Here we show that skin-
microangiopathy phenotypes in humans can be correlated with diabetes stage via …

Co-design of human-centered, explainable AI for clinical decision support

C Panigutti, A Beretta, D Fadda, F Giannotti… - ACM Transactions on …, 2023 - dl.acm.org
eXplainable AI (XAI) involves two intertwined but separate challenges: the development of
techniques to extract explanations from black-box AI models and the way such explanations …