[HTML][HTML] Data preprocessing techniques for ai and machine learning readiness: Sco** review of wearable sensor data in cancer care

BL Ortiz, V Gupta, R Kumar, A Jalin, X Cao… - JMIR mHealth and …, 2024 - mhealth.jmir.org
Background: Wearable sensors are increasingly being explored in health care, including in
cancer care, for their potential in continuously monitoring patients. Despite their growing …

Machine learning for catalysing the integration of noncoding RNA in research and clinical practice

D de Gonzalo-Calvo, K Karaduzovic-Hadziabdic… - …, 2024 - thelancet.com
The human transcriptome predominantly consists of noncoding RNAs (ncRNAs), transcripts
that do not encode proteins. The noncoding transcriptome governs a multitude of …

Generative ai for synthetic data generation: Methods, challenges and the future

X Guo, Y Chen - ar**: A systematic literature review and taxonomy
MP dos Santos, WF Heckler, RS Bavaresco… - Computers in Human …, 2024 - Elsevier
Health conditions, encompassing both physical and mental aspects, hold an influence that
extends beyond the individual. These conditions affect personal well-being, relationships …

Unveiling the secrets: How masking strategies shape time series imputation

L Qian, Z Ibrahim, W Du, Y Yang… - arxiv preprint arxiv …, 2024 - arxiv.org
In this study, we explore the impact of different masking strategies on time series imputation
models. We evaluate the effects of pre-masking versus in-mini-batch masking, normalization …

Automated machine learning with interpretation: a systematic review of methodologies and applications in healthcare

H Yuan, K Yu, F **e, M Liu, S Sun - Medicine Advances, 2024 - Wiley Online Library
Abstract Machine learning (ML) has achieved substantial success in performing healthcare
tasks in which the configuration of every part of the ML pipeline relies heavily on technical …