Multimodal machine learning in precision health: A sco** review

A Kline, H Wang, Y Li, S Dennis, M Hutch, Z Xu… - npj Digital …, 2022 - nature.com
Abstract Machine learning is frequently being leveraged to tackle problems in the health
sector including utilization for clinical decision-support. Its use has historically been focused …

AD-BERT: Using pre-trained language model to predict the progression from mild cognitive impairment to Alzheimer's disease

C Mao, J Xu, L Rasmussen, Y Li, P Adekkanattu… - Journal of Biomedical …, 2023 - Elsevier
Objective We develop a deep learning framework based on the pre-trained Bidirectional
Encoder Representations from Transformers (BERT) model using unstructured clinical notes …

Deep reinforcement learning for cost-effective medical diagnosis

Z Yu, Y Li, J Kim, K Huang, Y Luo, M Wang - ar** Using Vital Sign Trajectories
YJ Ding, Z Luo, M Szeto, Y Luo… - … on Bioinformatics and …, 2023 - ieeexplore.ieee.org
Sepsis can be life-threatening, which highlights the need to understand the condition's
diverse phenotypes to enhance treatment effectiveness. Sepsis phenotypes are derived …

Modeling Bacterial Infection Risk for Data-Driven Antibiotic De-Escalation in Critically Ill Adults

G Eickelberg - 2023 - search.proquest.com
Bacterial infections (BI) are a frequent, expensive, and life-threatening condition for critically
ill patients. For patients with serious BI, minimizing the time between admission to the …