Machine learning on small size samples: A synthetic knowledge synthesis

P Kokol, M Kokol, S Zagoranski - Science Progress, 2022 - journals.sagepub.com
Machine Learning is an increasingly important technology dealing with the growing
complexity of the digitalised world. Despite the fact, that we live in a 'Big data'world where …

Technology‐mediated just‐in‐time adaptive interventions (JITAIs) to reduce harmful substance use: a systematic review

O Perski, ET Hébert, F Naughton, EB Hekler… - …, 2022 - Wiley Online Library
Abstract Background and Aims Lapse risk when trying to stop or reduce harmful substance
use is idiosyncratic, dynamic and multi‐factorial. Just‐in‐time adaptive interventions (JITAIs) …

Beyond screen time: Identity development in the digital age

I Granic, H Morita, H Scholten - Psychological Inquiry, 2020 - Taylor & Francis
We are in the midst of a global transition in which digital “screens” are no longer simply
entertainment devices and distractions; rather, adolescents are currently living in a hybrid …

Precision health: the role of the social and behavioral sciences in advancing the vision

E Hekler, JA Tiro, CM Hunter… - Annals of Behavioral …, 2020 - academic.oup.com
Abstract Background In 2015, Collins and Varmus articulated a vision for precision medicine
emphasizing molecular characterization of illness to identify actionable biomarkers to …

Hybrid quantum neural network for drug response prediction

A Sagingalieva, M Kordzanganeh, N Kenbayev… - Cancers, 2023 - mdpi.com
Simple Summary This work successfully employs a novel approach in processing patient
and drug data to predict the drug response for cancer patients. The approach uses a deep …

Understanding health behaviours in context: A systematic review and meta-analysis of ecological momentary assessment studies of five key health behaviours

O Perski, J Keller, D Kale, BYA Asare… - Health psychology …, 2022 - Taylor & Francis
ABSTRACT Ecological Momentary Assessment (EMA) involves repeated, real-time
sampling of health behaviours in context. We present the state-of-knowledge in EMA …

[PDF][PDF] Predictive modeling based on small data in clinical medicine: RBF-based additive input-doubling method

I Izonin, R Tkachenko, I Dronyuk… - Mathematical …, 2021 - researchgate.net
The paper considers the problem of handling short sets of medical data. Effectively solving
this problem will provide the ability to solve numerous classification and regression tasks in …

Beyond the hype of big data and artificial intelligence: building foundations for knowledge and wisdom

J Car, A Sheikh, P Wicks, MS Williams - Bmc Medicine, 2019 - Springer
Big data, coupled with the use of advanced analytical approaches, such as artificial
intelligence (AI), have the potential to improve medical outcomes and population health …

Innovative methods for observing and changing complex health behaviors: four propositions

G Chevance, O Perski, EB Hekler - Translational Behavioral …, 2021 - academic.oup.com
Precision health initiatives aim to progressively move from traditional, group-level
approaches to health diagnostics and treatments toward ones that are individualized …

Slow down and be critical before using early warning signals in psychopathology

MA Helmich, MJ Schreuder, LF Bringmann… - Nature Reviews …, 2024 - nature.com
Early warning signals are considered to be generic indicators of a system's accumulating
instability and 'critical slowing down'prior to substantial and abrupt transitions between …