High-performance medicine: the convergence of human and artificial intelligence
EJ Topol - Nature medicine, 2019 - nature.com
The use of artificial intelligence, and the deep-learning subtype in particular, has been
enabled by the use of labeled big data, along with markedly enhanced computing power …
enabled by the use of labeled big data, along with markedly enhanced computing power …
Machine learning in mental health: a scoping review of methods and applications
BackgroundThis paper aims to synthesise the literature on machine learning (ML) and big
data applications for mental health, highlighting current research and applications in …
data applications for mental health, highlighting current research and applications in …
Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
Machine learning in mental health: A systematic review of the HCI literature to support the development of effective and implementable ML systems
High prevalence of mental illness and the need for effective mental health care, combined
with recent advances in AI, has led to an increase in explorations of how the field of machine …
with recent advances in AI, has led to an increase in explorations of how the field of machine …
Designing human-centered AI for mental health: Developing clinically relevant applications for online CBT treatment
A Thieme, M Hanratty, M Lyons, J Palacios… - ACM Transactions on …, 2023 - dl.acm.org
Recent advances in AI and machine learning (ML) promise significant transformations in the
future delivery of healthcare. Despite a surge in research and development, few works have …
future delivery of healthcare. Despite a surge in research and development, few works have …
Deep neural networks in psychiatry
Abstract Machine and deep learning methods, today's core of artificial intelligence, have
been applied with increasing success and impact in many commercial and research …
been applied with increasing success and impact in many commercial and research …
Product-based neural networks for user response prediction over multi-field categorical data
User response prediction is a crucial component for personalized information retrieval and
filtering scenarios, such as recommender system and web search. The data in user …
filtering scenarios, such as recommender system and web search. The data in user …
Not just privacy: Improving performance of private deep learning in mobile cloud
The increasing demand for on-device deep learning services calls for a highly efficient
manner to deploy deep neural networks (DNNs) on mobile devices with limited capacity …
manner to deploy deep neural networks (DNNs) on mobile devices with limited capacity …
Deep learning for small and big data in psychiatry
G Koppe, A Meyer-Lindenberg… - …, 2021 - nature.com
Psychiatry today must gain a better understanding of the common and distinct
pathophysiological mechanisms underlying psychiatric disorders in order to deliver more …
pathophysiological mechanisms underlying psychiatric disorders in order to deliver more …
Diagnostic accuracy of keystroke dynamics as digital biomarkers for fine motor decline in neuropsychiatric disorders: a systematic review and meta-analysis
The unmet timely diagnosis requirements, that take place years after substantial neural loss
and neuroperturbations in neuropsychiatric disorders, affirm the dire need for biomarkers …
and neuroperturbations in neuropsychiatric disorders, affirm the dire need for biomarkers …